| Accepted Posters |
| Category 'C'- Chemical and Pharmaceutical Informatics' |
| Poster A01 |
| A Bayesian Regression Model with Variable Selection for Genome-Wide Association Studies: Detection of Epistasis Effects |
| Carla Chen- Queensland University of Technology |
| Jonathan Keith (Queensland University of Technology, School of Mathematical Sciences); Peter Visscher (Queensland Institute of Medical Research, Genetic Epidemiology, Molecular Epidemiology and Queensland Statistical Genetics Laboratories); Kerrie Mengersen (Queensland University of Technology, School of Mathematical Sciences); |
| Short Abstract: In this poster, we extend a Bayesian method for detecting disease-related loci. Firstly, the model allows inclusion of multiple types of covariate in addition to marker data. Secondly, we extend the method to identify two-way interaction effects. We demonstrate our model using the Genica data set. |
| Long Abstract: Click Here |
| Poster A02 |
| Nonlinear Mixture Models with Applications to Clinical Pharmacokinetics and Gene Expression Analysis |
| Tatiana Tatarinova- Loyola Marymount University |
| Alan Schumitzky (University of Southern California, Mathematics); |
| Short Abstract: We describe applications of mixture models to pharmacokinetics, gene expression analysis and pharmacogenomics. We present methods for the simultaneous analysis of gene expression and pharmacokinetic data that lay the groundwork for personalized medicine. Our focus is to combine rigorous mathematical and statistical methods with realistic applications. |
| Long Abstract: Click Here |
| Poster A03 |
| Knowledge management in a Systems Biology approach to translational medicine. |
| Dieter Maier- Biomax Informatics AG |
| Miguel Hernandez (Universitat Pompeu Fabra, Research Group on Biomedical Informatics (GRIB)); Jordi Villà i Freixa (Universitat Pompeu Fabra, Research Group on Biomedical Informatics (GRIB)); Sascha Losko (Biomax Informatics AG, ); |
| Short Abstract: Systems Biology promises better understanding of complex phenotypes, like chronic obstructive pulmonary disease. Within the EU BioBridge project the BioXMTM knowledge management environment integrates COPD specific molecular networks with clinical and experimental data. Combined with modelling/simulation (MathModelica/IsoDyn/ByoDyn) and network inference tools (Banjo/ARACNE) existing networks are expanded and deterministic models simulated. |
| Long Abstract: Click Here |
| Poster A04 |
| A Bayesian network framework for integrating high throughput/high dimensional data to model the regulatory networks behind cancer outcomes. |
| Olivier Gevaert- ESAT/SCD (SISTA) |
| Olivier Gevaert (KU Leuven, Electrical Engineering); Bart De Moor (KU Leuven, Electrical Engineering); |
| Short Abstract: Many microarray studies have been performed where clinically relevant outcomes are predicted. However most of these models are black box models. We are developing a Bayesian network framework for data integration (i.e. clinical, microarray and proteomics data) to predict clinically relevant outcomes in cancer while keeping the model interpretable. |
| Long Abstract: Click Here |
| Poster A05 |
| Network analysis of differential expression for the identification of disease-causing genes |
| Daniela Nitsch- KU Leuven |
| No additional authors |
| Short Abstract: We have developed a novel gene prioritization approach that substitutes expression data to prior knowledge of the molecular basis of the disease, as required by existing methods. Our method ranks candidate genes by their differentially expressed neighborhoods. Candidate genes with highly differentially expressed neighbors are strong candidates. |
| Long Abstract: Click Here |
| Poster A06 |
| Genome-Wide Detection of Putative Oncofetal Genes in Human Hepatocellular Carcinoma by Splicing Pattern Comparison |
| Chia-Hung Liu- National Taiwan University |
| Chia-Hung Liu (National Taiwan University, Graduate Institute of Biomedical Electronic and Bioinformatics); Kuan-Ting Lin (National Yang-Ming University, Institute of Biomedical Informatics); Chi-Ying F Huang (National Yang-Ming University, Institute of Clinical Medicine); Yu-Shi Lin (National Taiwan University, Department of Computer Science and Information Engineering); Yih-Jyh Shann (National Yang-Ming University, Institute of Clinical Medicine); Cheng-Yan Kao (National Taiwan University, Graduate Institute of Biomedical Electronic and Bioinformatics); Chun-Nan Hsu (Academia Sinica, Institute of Information Science); |
| Short Abstract: We design a method to identify potential oncofetal genes in HCC by splicing patterns comparison.With the characteristics of long isoforms in fetal/tumor liver, these genes may boost some domains.They are participated in proliferation function linking to the tumor formation,suggesting potential utility of using AS signatures for diagnostic and prognostic purposes. |
| Long Abstract: Click Here |
| Poster A07 |
| Continuous Time Bayesian Networks for diagnosis of heart disease |
| Elena Gatti- Università degli Studi di Milano Bicocca |
| Enrico Fagiuoli (Università degli Studi di Milano Bicocca, Department of Informatics, Systems and Communication (DISCo)); Davide Luciani (Istituto Mario Negri, Public Health); Fabio Pioltini (Università degli Studi di Milano Bicocca, Department of Informatics, Systems and Communication (DISCo)); Fabio Stella (Università degli Studi di Milano Bicocca, Department of Informatics, Systems and Communication (DISCo)); |
| Short Abstract: Over the last years, several research programs have been developed to assist physicians in reasoning about cardiovascular disorders. In this contribution, the authors propose a Continuous Time Bayesian Network (CTBN), a modeling language for structured stochastic processes that evolve over continuous time, to diagnose cardiac diseases. |
| Long Abstract: Click Here |
| Poster A08 |
| Prioritizing Disease Genes based on Functional Similarity |
| Andreas Schlicker- Max Planck Institute for Informatics |
| Thomas Lengauer (Max Planck Institute for Informatics, Computational Biology and Applied Algorithmics); Mario Albrecht (Max Planck Institute for Informatics, Computational Biology and Applied Algorithmics); |
| Short Abstract: We introduce MedSim, a new method for disease gene prioritization. MedSim compares phenotypes and candidates based on automatically derived functional profiles. We validated our approach with known disease genes using artificial quantitative trait loci. MedSim achieved an AUC of up to 0.90 and a sensitivity of over 70 %. |
| Long Abstract: Click Here |
| Poster A09 |
| Describing complex sequence variants by extending HGVS sequence variation nomenclature |
| Peter Taschner- LUMC |
| Johan den Dunnen (LUMC, Human Genetics); |
| Short Abstract: The sequence variation nomenclature guidelines of the HumanGenome Variation Society focus on simple variants. Unambiguous description of complex sequence variants identified by NGS can be facilitated by extending these guidelines and allowing: nested changes within inversions and duplications;composite changes supporting concatenation of inserted sequences; newduplication types describing changes in orientation. |
| Long Abstract: Click Here |
| Poster A10 |
| Bioinformatics tools for the analysis of foodborne bacteria |
| Robert Stones- Food & Environment Research Agency |
| No additional authors |
| Short Abstract: To enable better understanding of the biology/evolution of foodborne bacterial strains, we are developing a standalone software application to identify and compare strain-specific biomarkers from heterogeneous datasets. Including LC-MS protein data, gene expression data and next generation DNA data. Employing novel analytical/visualisation methods to correlate across diverse datasets. |
| Long Abstract: Click Here |
| Poster A11 |
| Focusing on Function: Gene-wide Analysis of Genome-wide Association Studies |
| Benjamin Lehne- King's College London |
| Cathryn Lewis (King's College London, MRC SGDP Centre, Insistute of Psychiatry); Thomas Schlitt (King's College London, Medical & Molecular Genetics); |
| Short Abstract: Genome-Wide-Association-Studies (GWAS) focus on the 20-50 most significant Single-Nucleotide-Polymorphisms (SNPs) ignoring thousands of suggestive p-values. To overcome this limitation we analysed GWAS data on a gene-level. Based on the WTCCC data we assigned SNPs to genes according to their relative genomic position and statistically combined all p-values within a gene. |
| Long Abstract: Click Here |
| Poster A12 |
| www.spatialepidemiology.net and EpiCollect – A global data collection and mapping framework for infectious disease eipdemiology |
| Derek Huntley- Imperial College London |
| David Aanensen (Imperial College London, 1Department of Infectious Disease Epidemiology); Brian Spratt (Imperial College London, Department of Infectious Disease Epidemiology); |
| Short Abstract: Spatialepidemiology.net is a web based data collection and mapping system that allows the collection, mapping and modelling of infectious diseases. Data can be entered into the system and monitored within the field using a novel mobile phone-based collection tool, EpiCollect. |
| Long Abstract: Click Here |
| Poster A13 |
| PocketInflator: Designing Ligand Binding Pockets on Protein Surfaces |
| Susanne Eyrisch- Saarland University |
| No additional authors |
| Short Abstract: Proteins involved in protein-protein interactions often lack appropriate ligand binding pockets. We present a new approach that accounts for backbone and side chain flexibility to open potential ligand binding pockets based on the PASS algorithm. We successfully designed binding pockets on the proteins BCL-XL, IL-2, and MDM2. |
| Long Abstract: Click Here |
| Poster A14 |
| A computational biology approach to analyse disease-related protein mutations |
| Anna Marabotti- National Research Council |
| Angelo Facchiano (National Research Council (CNR), Institute of Food Science); Antonio d'Acierno (National Research Council (CNR), Institute of Food Science); |
| Short Abstract: A fully computational approach has been used to characterize the structural and functional effectsof mutations on the enzyme galactose-1-phosphate uridyltransferase (GALT), causing the geneticdisease classical galactosemia. The data and analyses for all mutants are stored in a Web-accessible database hosted at http://bioinformatica.isa.cnr.it/GALT freely accessible to all people. |
| Long Abstract: Click Here |
| Poster A15 |
| Illuminating alterations in tumor transcriptomes by ultra-high throughput sequencing |
| Brian Tuch- Applied Biosystems |
| Asim Siddiqui (Applied Biosystems, R&D); Matthew Muller (Applied Biosystems, R&D); Catalin Barbacioru (Applied Biosystems, R&D); Christina Bormann-Chung (Applied Biosystems, R&D); Cinna Monighetti (Applied Biosystems, R&D); Jian Gu (Applied Biosystems, R&D); Scott Kuersten (Applied Biosystems, R&D); Robert Setterquist (Applied Biosystems, R&D); Yongming Sun (Applied Biosystems, R&D); Xing Xu (Applied Biosystems, R&D); Fiona Hyland (Applied Biosystems, R&D); Chunlin Xiao (Applied Biosystems, R&D); Heather Peckham (Applied Biosystems, R&D); Melissa Barker (Applied Biosystems, R&D); Francisco De La Vega (Applied Biosystems, R&D); Ali Bashir (UCSD, Computer Science); Vineet Bafna (UCSD, Computer Science); Rebecca Laborde (Mayo Clinic, Laboratory Medicine and Pathology); Eric Moore (Mayo Clinic, Laboratory Medicine and Pathology); Jan Kasperbauer (Mayo Clinic, Laboratory Medicine and Pathology); David Smith (Mayo Clinic, Laboratory Medicine and Pathology); |
| Short Abstract: We have developed a tool to align short sequences generated from ultra-high throughput sequencing of RNA samples to a reference genome. The tool was applied to 60 GB of sequence from matched tumor/normal tissue samples from three patients with tongue cancer, thereby illuminating the full transcriptional landscape of this cancer. |
| Long Abstract: Click Here |
| Poster A16 |
| Comprehensive view of pathways related to complex diseases and their cross-talks |
| Anna Bauer-Mehren- Research Unit on Biomedical Informatics (GRIB) |
| Laura Furlong (Research Unit on Biomedical Informatics (GRIB), IMIM-Hospital del Mar, Universitat Pompeu Fabra); Ferran Sanz (Research Unit on Biomedical Informatics (GRIB), IMIM-Hospital del Mar, Universitat Pompeu Fabra); |
| Short Abstract: We present a strategy to integrate biological pathways from public databases with curated current knowledge on gene-disease associations in order to obtain a comprehensive view of all pathways related to a disease and their cross-talks. The integrated network could subsequently be used to study the mechanisms underlying complex diseases. |
| Long Abstract: Click Here |
| Poster A17 |
| S2G – Candidate gene finder and OMIM search utility |
| Rapahel Cohen- Ben-Gurion University |
| Avitan Gefen (BGU, CS); Ohad S. Birk (BGU, Health); |
| Short Abstract: The web based S2G tool provides clinicians with an efficient tool for diagnosis and researchers with a disease candidate gene prediction tool, based on phenotypic data and an integration of a wide range of gene data resources from 17 data bases. |
| Long Abstract: Click Here |
| Poster A18 |
| Gene prioritization using text mining and protein-protein interaction in livestock |
| Li Jiang- Faculty Of Agricultural Sciences, Aarhus University |
| Peter Sørensen (Faculty of Agricultural Sciences, Aarhus University, Department of Genetics and Biotechnology); Christopher Workman (Technical University of Denmark, Center for Biological Sequence Analysis, Department of Systems Biology); Axel Skarman (Faculty of Agricultural Sciences, Aarhus University, Department of Genetics and Biotechnology); |
| Short Abstract: A gene prioritization approach for livestock diseases is presented. It prioritizes genes based on protein-protein interactions, association of proteins with diseases and phenotypic similarities of diseases. Phenotypic similarities were determined by text mining of PubMed abstracts which helped the gene prioritizations in livestock species. |
| Long Abstract: Click Here |
| Poster A19 |
| Analyzing differentially regulated metabolic enzymes taking pathway topology into account |
| Gunnar Schramm- IPMB, University of Heidelberg |
| Stefan Wiesberg (Institute of Computer Science, University of Heidelberg, Combinatorial Optimization); Nicolle Diessl (IPMB, Bioquant, Bioinformatics and Functional Genome Analyses); Vitalia Sagulenko (DKFZ Heidelberg, Tumor Genetics); Marcus Oswald (Institute of Computer Science, University of Heidelberg, Combinatorial Optimization); Gerhard Reinelt (Institute of Computer Science, University of Heidelberg, Combinatorial Optimization); Frank Westermann (DKFZ Heidelberg, Tumor Genetics); Roland Eils (DKFZ Heidelberg, TBI Bioinformatics); Rainer Koenig (IPMB, University of Heidelberg, Bioinformatics and Functional Genome Analyses); |
| Short Abstract: We investigated neuroblastoma tumor metabolism and developed a tool to detect regulatory shifts the metabolic network. We took network topology into account by applying adjusted wavelet transforms on an elaborated two-dimensional grid representation. We found significant patterns of regulatory shifts needed for increased proliferation. |
| Long Abstract: Click Here |
| Poster A20 |
| Comparative and functional genomic characterization of the Toxoplasma gondii rhoptry kinase family (ROPK) of and its role in host-gene regulation |
| Lucia Peixoto- University of Pennsylvania |
| Paul H. Davis (University of Pennsylvania, Department of Biology and Penn Genomics Frontiers Institute); Dinkorma Ouloguem (University of Pennsylvania, Department of Biology and Penn Genomics Frontiers Institute); David S. Roos (University of Pennsylvania, Department of Biology and Penn Genomics Frontiers Institute); |
| Short Abstract: Eukaryotic kinases are typically cytoplasmic, consistent with their involvement in intracellular signaling. We have exploited comparative and functional genomic data to explore the evolution and function of a distinct family of secreted kinases in the protozoan parasite Toxoplasma gondii, including their role in the modulation/manipulation of host responses and pathogenesis. |
| Long Abstract: Click Here |
| Poster A21 |
| Data Combinability in GWAS Meta-Analysis |
| Hugo Naya- Institut Pasteur de Montevideo |
| Lorena Etcheverry (Facultad de Ingeniería - UdelaR, Instituto de Computación); Martín Graña (Institut Pasteur de Montevideo, Bioinformatics Unit); Víctor Raggio (Institut Pasteur de Montevideo, Bioinformatics Unit); Adriana Marotta (Facultad de Ingeniería - UdelaR, Instituto de Computación); Agustín Gonzalez (Institut Pasteur de Montevideo, Bioinformatics Unit); Inés Abin (Institut Pasteur de Montevideo, Bioinformatics Unit); Valentina Ramos del Campo (Facultad de Ingeniería - UdelaR, Instituto de Computación); Flavia Serra (Facultad de Ingeniería - UdelaR, Instituto de Computación); Raúl Ruggia (Facultad de Ingeniería - UdelaR, Instituto de Computación); |
| Short Abstract: Meta-Analysis on GWAS seems highly promising as it enables quality and reliability improvement of studies, reducing complexities and costs. This task faces a variety of problems, including syntactic and semantic heterogeneity of sources.Our work provides the GWAS Meta-Analyst with conceptual and practical tools to pursue an effective Data Integration. |
| Long Abstract: Click Here |
| Poster A22 |
| Metagenomic analysis of human respiratory tract viral communities in Cystic Fibrosis and Non-Cystic Fibrosis individuals |
| Dana Willner- San Diego State University |
| Mike Furlan (SDSU, Biology); Matt Haynes (SDSU, Biology); Florent Angly (SDSU, Computational Sciences); Robert Schimieder (SDSU, Computational Sciences); Douglas Conrad (UCSD Medical School, Pulmonary Medicine); Forest Rohwer (SDSU, Biology); |
| Short Abstract: We obtained metagenomic sequences from viral communities in the respiratory tract of 5 CF and 5 Non-CF individuals. Using bioinformatics and statistics, we determine that while viral taxonomy is variable between individuals, the diseased and non-diseased states are clearly defined by viral metabolic functions. |
| Long Abstract: Click Here |
| Poster A23 |
| Toward computational prediction of demethylation-induced gene reactivation in cancer. |
| Jill Rubinstein- Yale University |
| Michael Krauthammer (Yale University, Pathology); Nam Tran (Yale University, Pathology); Ruth Halaban (Yale University, Dermatology); |
| Short Abstract: Reactivation of silenced tumor suppressor genes using demethylating agents such as Decitabine holds promise in cancer treatment, yet it is unclear why the drug acts preferentially at certain loci. We use genome-wide methylation and expression data from melanoma cell lines to explore promoter qualities that define drug susceptibility. |
| Long Abstract: Click Here |
| Poster A24 |
| A Systematic Approach to Identify Drug Targets for Human Cells Infected with Hepatitis C Virus by Using siRNA Screening Images |
| Apichat Suratanee- University of Heidelberg |
| Ilka Wörz (University of Heidelberg, Molecular Virology); Nathalie Harder (University of Heidelberg, Bioinformatics and Functional Genomic, IPMB, BIOQUANT); Petr Matula (University of Heidelberg, Bioinformatics and Functional Genomic, IPMB, BIOQUANT); Markus Gipp (University of Heidelberg, Institute of Computer Science V, Scientific Computing Group); Guillermo Marcus (University of Heidelberg, Institute of Computer Science V, Scientific Computing Group); Maik Lehmann (UniversitätsKlinikum Heidelberg, Virology); Kathleen Börner (UniversitätsKlinikum Heidelberg, Virology); Johannes Hermle (UniversitätsKlinikum Heidelberg, Virology); Reinhard Männer (University of Heidelberg, Institute of Computer Science V, Scientific Computing Group); Karl Rohr (University of Heidelberg, Bioinformatics and Functional Genomic, IPMB, BIOQUANT); Ralf Bartenschlager (University of Heidelberg, Molecular Virology); Roland Eils (University of Heidelberg, Bioinformatics and Functional Genomic, IPMB, BIOQUANT); Rainer König (University of Heidelberg, Bioinformatics and Functional Genomic, IPMB, BIOQUANT); |
| Short Abstract: Images from siRNA knock down screens of cells infected with hepatitis C virus are analyzed. By using the image processing approaches and statistical analysis, we identify genes that are essential to virus replication. The poster shows and overview of the methodology and our progress to date. |
| Long Abstract: Click Here |
| Poster A25 |
| Support Vector Machine Methods for Predicting Allergenicity of Food Based Proteins |
| Hong Qu- Peking University |
| Zhongping Lin (Peking University, College of Life Sciences); Dacheng Qu (Beijing Institute of Technology, School of Computer Science & Technology); |
| Short Abstract: Allergy inducing elements within food based proteins are tested by using the support vector machine method. First, Allergenic proteins are put through a human digestion simulation. The sequence alignment method is then used to extract the specific fragments. Further, based on the surface fragments a classifier is constructed. |
| Long Abstract: Click Here |
| Poster A26 |
| TOXPO: The polymorphism database for systems toxicology |
| Yunju Jo- KyungHee University |
| No additional authors |
| Short Abstract: Now, genetic polymorphism is also considered in toxicogenomics because polymorphism information can be used to explain the individual specific toxicity and/or individual specific side effects |
| Long Abstract: Click Here |
| Poster A27 |
| Meta-analysis of “omics” data |
| Angelo Facchiano- Istituto di Scienze dell Alimentazione - CNR |
| Anna Marabotti (Istituto di Scienze dell Alimentazione - CNR , Lab. of Bioinformatics and Computational Biology); Francesco Facchiano (Istituto Superiore di Sanità , Dip. Ematologia,Oncologia e Medicina Molecolare ); |
| Short Abstract: A suite of tools has been developed with the aim of helping researches in oncology and, more in general, human disease fields which generate large amount of data by omics analyses. The tools are aimed to search for relationships among proteins and genes, identified by experimental data, and literature reports. |
| Long Abstract: Click Here |
| Poster A28 |
| Identification and Analysis of Common Features of Cysteine Proteases of Malaria Parasites for the Development of Novel Parasitic Protease Inhibitors |
| Ozlem Tastan Bishop- University of Pretoria |
| Matthys Kroon (University of Pretoria, Biochemistry); |
| Short Abstract: Cysteine proteases are essential in the life cycle of malaria parasites. This work constructs homology models of various 3-D structures and identifies important evolutionary features of papain-family cysteine proteases from malaria parasites, with the intention of designing drugs that are unlikely to lose effectiveness due to a parasite evolving resistance. |
| Long Abstract: Click Here |
| Poster A29 |
| How to efficiently efficiently hunt the disease causing gene |
| Leon-Charles Tranchevent- Katholieke Universiteit Leuven (K.U.L.), Leuven, Belgium |
| Stein Aerts (VIB, Leuven, Belgium, Laboratory of Neurogenetics, Department of Molecular and Developmental Genetics & Department of Human Genetics, Katholieke Universiteit Leuven School of Medicine); Peter Van Loo (Katholieke Universiteit Leuven & VIB, Leuven, Belgium, Department of Electrical Engineering ESAT-SCD & Human Genome Laboratory, Department of Molecular and Developmental Genetics & Department of Human Genetics, Katholieke Universiteit Leuven School of Medicine); Bert Coessens (Katholieke Universiteit Leuven, Leuven, Belgium, Department of Electrical Engineering ESAT-SCD); Bassem A. Hassan (VIB, Leuven, Belgium, Laboratory of Neurogenetics, Department of Molecular and Developmental Genetics & Department of Human Genetics, Katholieke Universiteit Leuven School of Medicine); Yves Moreau (Katholieke Universiteit Leuven, Leuven, Belgium, Department of Electrical Engineering ESAT-SCD); |
| Short Abstract: Endeavour, a web resource for the prioritization of genes, indicates which genes are the most promising candidates among large list of candidates. |
| Long Abstract: Click Here |
| Poster A30 |
| Large-scale meta-analysis of leukemia microarray data to build a novel diagnostic machine |
| Andrea Gaarz- University of Bonn |
| Therese Inhester (University of Bonn, Laboratory for Genomics and Immunoregulation, Life and Medical Sciences); Andrea Staratschek-Jox (University of Bonn, Laboratory for Genomics and Immunoregulation, Life and Medical Sciences); Joachim L. Schultze (University of Bonn, Laboratory for Genomics and Immunoregulation, Life and Medical Sciences); |
| Short Abstract: Current leukemia diagnosis involves multiple time-intensive techniques. We investigated the use of large-scale gene expression analysis for diagnosis and prognosis in a systematic and comprehensive evaluation of different classification methods. We developed a robust and accurate diagnostic tool for AML based on meta-analysis of microarrays. |
| Long Abstract: Click Here |
| Poster A31 |
| Markov Blanket discovery algorithm for elucidating gene-gene interactions and clinical outcome prediction |
| Peter Clerinx- KU Leuven |
| Olivier Gevaert (KU Leuven, ESAT / SCD); Bart De Moor (KU Leuven, ESAT / SCD); |
| Short Abstract: A novel MB discovery algorithm based on fast Mutual Information and Conditional Mutual Information testing is proposed. This method has been compared to performance of state-of-the-art algorihms such as ARACNE on synthetic data. Results for two microarray datasets are presented to demonstrate feasibility in oncological decision support. |
| Long Abstract: Click Here |
| Poster A32 |
| Italia |
| Matteo Floris- University of Rome La Sapienza |
| Maria Valentini (CRS4, Bioinformatics Lab.); Nicola Carboni (Centro Sclerosi Multipla, Ospedale Binaghi, Università di CA, Dipartimento di Scienze Cardiovascolari e Neurologiche); Eleonora Cocco (Centro Sclerosi Multipla, Ospedale Binaghi, Università di CA, Dipartimento di Scienze Cardiovascolari e Neurologiche); |
| Short Abstract: We studied the effect on a molecular level of a novel LMNA gene mutation. Computational predictions suggest a disruption of the dimer stability, due to the shift from an hydrophobic to a polar residue in the “rod” domain, This hypothesis was further investigated performing MD simulations. |
| Long Abstract: Click Here |
| Poster A33 |
| Maxlink |
| Gabriel Östlund- Stockholm University |
| Erik Sonnhammer (Stockholm University, Stockholm Bioinformatics Center); |
| Short Abstract: The development of new therapeutics and diagnostics relies on understanding disease mechanisms, and identification of novel disease-associated genes is a key step in that process. We have developed an application using known cancer genes to screen a protein interaction network in order to find genes not previously associated with cancer. |
| Long Abstract: Click Here |
| Poster A34 |
| Impact of changeable protein environment on disease-related mutations |
| Allegra Via- Sapienza Universita' di Roma |
| Loredana Le Pera (Sapienza Universita' di Roma, Biochemical Science - Biocomputing Unit); Enrico Ferraro (Sapienza Universita' di Roma, Biochemical Science - Biocomputing Unit); Daniel Carbajo (Sapienza Universita' di Roma, Biochemical Science - Biocomputing Unit); |
| Short Abstract: We characterized, both at the primary and at the tertiary structure levels, disease-related mutations (DRMs), DRM-hosting proteins and DRM protein environments in terms of polymorphisms, other DRMs, functional sites and alternative splicing events. Our results are being organized in a platform for the retrieval of DRM data and the annotation of user-submitted data. |
| Long Abstract: Click Here |
| Poster A35 |
| Modeling and docking of the galanin receptors GalR1, GalR2, and GalR3 |
| Wiktor Jurkowski- Stockholm University |
| Samira Yazdi (Stockholm University, Department of Biochemistry and Biophysics); Arne Elofsson (Stockholm University, Department of Biochemistry and Biophysics); |
| Short Abstract: The galanin receptor family comprises of 3 members all belonging GPCR superfamily. On the basis of generated 3D models and molecular docking calculations we found significant differences in organization of binding pocket among the three receptor types, which might be key for specific molecular recognition of ligands. |
| Long Abstract: Click Here |
| Poster A36 |
| Genetic signaling pathway signatures of multiple human cancers cluster in embryonic developmental layers |
| Andreas Teufel- Johannes Gutenberg Univ |
| Markus Krupp (Johannes Gutenberg University, Department of Medicine I); Thorsten Maass (Johannes Gutenberg University, Department of Medicine I); Frank Staib (Johannes Gutenberg University, Department of Medicine I); Tobias Bauer (Germany Cancer Research Center, Department of Tumor Genetics); Stefan Biesterfeld (Johannes Gutenberg University, Institut for Pathology); Peter R Galle (Johannes Gutenberg University, Department of Medicine I); |
| Short Abstract: We downloaded all human cancer related microarray datasets from the Stanford Microarray Database. We found several genetic signaling pathways significantly enriched in these cancer related expression data. Unsupervised clustering unraveled two major tumor clusters based on the origin of the tissue from one of the three embryonic developmental layers. |
| Long Abstract: Click Here |
| Poster A37 |
| Molecular phylogenetic congruence: a promising approach to discovering interacting proteins |
| Tom Vandekerckhove- Ghent University - Faculty of Bioscience Engineering |
| Gerben Menschaert (Ghent University - Faculty of Bioscience Engineering, Molecular Biotechnology - Lab. Bioinformatics & Computational Genomics (BIOBIX)); Wim Van Criekinge (Ghent University - Faculty of Bioscience Engineering, Molecular Biotechnology - Lab. Bioinformatics & Computational Genomics (BIOBIX)); |
| Short Abstract: Interacting proteins co-evolve. We aim to find correct bio-active peptides for orphan receptors using phylogenetic congruence measures between receptor and ligand trees. With our bioinformatics tools, well over 50% of known receptor-ligand pairs ended up among the 10% most congruent ones. This may reduce costs in downstream pharmaceutical wetlab research. |
| Long Abstract: Click Here |
| Poster A38 |
| Detection of copy number variation in single cells using Agilent 244K microarrays |
| jiqiu cheng- K. U. Leuven |
| Evelyne Vanneste (K. U. Leuven , Center for Human Genetics); Peter Konings (K. U. Leuven, ESAT-SCD); Pascal Yazbeck (K. U. Leuven, Center for Human Genetics); Thierry Voet (K. U. Leuven, Center for Human Genetics); Joris Vermeesch (K. U. Leuven, Center for Human Genetics); Yves Moreau (K. U. Leuven, ESAT-SCD); |
| Short Abstract: Chromosome instability (CIN) is a known hallmark of tumorigenesis, but was recently also found to typify early human embryogenesis. To characterize CIN, we thus need technologies that can detect chromosomal imbalances at high resolution in single cells. |
| Long Abstract: Click Here |
| Poster A39 |
| A Web Server for HIV Ultra Deep Pyro-Sequencing Data Analysis and Diagnostics |
| Alessandro Barbato- University of Rome "Tor Vergata" - CASPUR |
| Alessandro Bruselles (INMI "L.Spallanzani" , Virology); Giovanni Chillemi (CASPUR, Computational Chemistry and Bioinformatics); Daniele Paoletti (CASPUR, Bioinformatics); Tiziana Castrignanò (CASPUR, Bionformatics); Mattia Prosperi (INMI "L.Spallanzani", Virology); Alessandro Desideri (University of Rome "Tor Vergata", Biochemistry); Isabella Abbate (INMI "L.Spallanzani", Virology); Maria R. Capobianchi (INMI "L.Spallanzani", Virology); Gabriella Rozera (INMI "L.Spallanzani", Virology); Giuseppe Ippolito (INMI "L.Spallanzani", Virology); |
| Short Abstract: We propose a web server to perform UDPS data alignment, error-correction, sequence analysis forboth prediction of HIV-1 CXCR4 coreceptor usage and, as future development, phylogeneticanalysis. Our web server facilitates, speeds up and reduces computational burdens for UDPS dataprocessing. |
| Long Abstract: Click Here |
| Poster A40 |
| Machine learning approach to find the gene networks associated to specific diseases: study on leukemia |
| Celia Fontanillo- Cancer Research Center (CIC-IBMCC, CSIC/USAL) |
| Alberto Risueño (Cancer Research Center (CIC-IBMCC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); Carlos Prieto (Cancer Research Center (CIC-IBMCC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); Javier De Las Rivas (Cancer Research Center (CIC-IBMCC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); |
| Short Abstract: Machine Learning methods are common to build disease predictors using genomic data. Adequate classifiers may reflect the biology behind classes, but there is not a clear link between predictive power and explanatory potential. We prove that a robust ML method allows to discover the gene networks associated to specific diseases. |
| Long Abstract: Click Here |
| Poster A41 |
| Public index of sample and phenotype availability at multiple biobanks |
| Mikhail Gostev- EMBL/EBI |
| Natalja Kurbatova (EBI, Microarray); Alvis Brazma (EBI, Microarray); Maria Krestyaninova (EBI, Microarray); ENGAGE consortium (FIMM, ); |
| Short Abstract: We present a web based index of samples and phenotypes available inmultiple biobanks, and harmonization of the sample annotation is at thecore of the tool. |
| Long Abstract: Click Here |
| Poster A42 |
| Functional Analysis of the Hexokinase Enzyme as a Drug Target for Plasmodium Falciparum |
| chinwe ekenna- covevnant university |
| Segun Fatumo (Covenant University, computer and information sciences); |
| Short Abstract: Hexokinase has been identified as an enzyme that catalyses the phosphorylation of glucose, this phosphorylation provides the activation energy required for glycolysis.we investigated into the 3 dimensional structure of hexokinase within Plasmodium falciparum in a bid to identify more functions for which hexokinase is important within it's pathway |
| Long Abstract: Click Here |
| Poster A43 |
| An Alternative Malaria Control Strategy for Malaria Research in Africa: An Artificial Neural Network Approach |
| Oluwagbemi Olugbenga- Covenant University ,College of Science and Technology |
| Yah Suh Clarance (Covenant University, College of Science and Technology, Department of Biological Sciences); Adebiyi Ezekiel (Covenant University, College of Science and Technology, Department of Computer and Information Sciences(Bioinformatics Unit)); |
| Short Abstract: In Africa, malaria persists as the most devastating human disease. This research engaged the use of neural networks through a programming approach, to explore the strategies in analyzing and proffering solutions to malaria occurrences in endemic regions. The results obtained helped to give insight into the quest of endemicity, control and management of malaria |
| Long Abstract: Click Here |
| Poster A44 |
| Differential Analysis of Neurodegenerative Alterations in Tissue via a Novel Spatial Querying Approach |
| Raf Van de Plas- K.U.Leuven |
| Kristiaan Pelckmans (Katholieke Universiteit Leuven, Dept. of Electrical Engineering (ESAT), SCD-SISTA); Thomas Philips (Katholieke Universiteit Leuven, Dept. of Experimental Neurology); Bart De Moor (Katholieke Universiteit Leuven, Dept. of Electrical Engineering (ESAT), SCD-SISTA); Etienne Waelkens (Katholieke Universiteit Leuven, Dept. of Molecular Cell Biology); |
| Short Abstract: Mass spectral imaging (MSI) is a technology that adds a spatial dimension to mass spectrometry-based biochemical analysis. It delivers insight into the local distribution of biomolecules throughout an organic tissue section. We introduce one of the first efficient computational methods that enables interrogation of MSI data from a spatial standpoint. |
| Long Abstract: Click Here |
| Poster A45 |
| Pathogen Profiling Pipeline: A metagenomics tool for rapid identification of pathogens from clinical specimens. |
| Tom Matthews- Public Health Agency of Canada |
| Heather Kent (Public Health Agency of Canada, National Microbiology Laboratory, Bioinformatics Core Facility); Shaun Tyler (Public Health Agency of Canada, National Microbiology Laboratory, Genomics Core Facility); Christine Bonner (Public Health Agency of Canada, National Microbiology Laboratory, Genomics Core Facility); Geoff Peters (Public Health Agency of Canada, National Microbiology Laboratory, Genomics Core Facility); Franklin Bristow (Public Health Agency of Canada, National Microbiology Laboratory, Bioinformatics Core Facility); Philip Mabon (Public Health Agency of Canada, National Microbiology Laboratory, Bioinformatics Core Facility); Morag Graham (Public Health Agency of Canada, National Microbiology Laboratory, Genomics Core Facility); Gary Van Domselaar (Public Health Agency of Canada, National Microbiology Laboratory, Bioinformatics Core Facility); |
| Short Abstract: The Pathogen Profiling Pipeline project aims to develop a metagenomics procedure independent of laboratory cultivation and a flexible bioinformatics pipeline for the rapid identification and analysis of pathogens in samples containing complex mixtures of host and microbial nucleic acids. |
| Long Abstract: Click Here |
| Poster A46 |
| Cross-conditional Analysis of Host Response to Pathogen Infection |
| Yared Kidane- Virginia Polytechnic Institute and State University |
| T.M. Murali (Virginia Polytechnic Institute and State University, Computer Science); Oswald Crasta (Virginia Polytechnic Institute and State University, Virginia Bioinformatics Institute); |
| Short Abstract: Post-genomic era is characterized by deluge of gene expression data. This opens up the exciting possibility of performing integrated analysis across different experimental conditions. In this study, we integrate gene expression and human protein-protein interaction datasets in order to reveal similarities and differences among cellular response to various infections agents. |
| Long Abstract: Click Here |
| Poster A47 |
| Human Disease – a by-product of evolution |
| Jonathan Dickerson- University of Manchester |
| David Robertson (University of Manchester, Faculty of Life Sciences); |
| Short Abstract: We investigate the origin of disease and find the numbers of disease-associated genes approximately tracks the overall numbers of genes present across evolutionary time. We also investigate the proportion of disease-associated genes across various common ancestors and find a relatively constant rate of disease association in genes arising from duplicates. |
| Long Abstract: Click Here |
| Poster A48 |
| Computational identification and characterization of elements associated with structural order and disorder in Leishmania ssp. predicted proteome. |
| Patrícia Ruy- René Rachou Research Center |
| Patrícia Ruy (CPqRR - FIOCRUZ, Laboratory of Cellular and Molecular Parasitology); Raul Torrieri (CPqRR - FIOCRUZ, Laboratory of Cellular and Molecular Parasitology); Juliano Simões de Toledo (Faculdade de Medicina de Ribeirão Preto - USP, Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos); Angela Kaysel Cruz (Faculdade de Medicina de Ribeirão Preto - USP, Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos); Guilherme Corrêa de Oliveira (Laboratório de Parasitologia Celular e Molecular, Centro de Pesquisas René Rachou - FIOCRUZ); Jeronimo Conceição Ruiz (Laboratório de Parasitologia Celular e Molecular, Centro de Pesquisas René Rachou - FIOCRUZ); |
| Short Abstract: In this study we are developing a computational methodology for high throughput identification of natively unfolded proteins in Leishmania spp. We will present the developed pipeline and database together with comparative analysis of disordered predictions, functional annotation, amino acids chemical proprieties patterns and protein subcellular localization prediction of three genomes. |
| Long Abstract: Click Here |
| Poster A49 |
| Computational identification and characterization of intrinsically unstructured proteins in Schistosoma mansoni |
| Raul Torrieri- René Rachou Research Center |
| Raul Torrieri (René Rachou Research Center, Laboratory of Cellular and Molecular Parasitology); Patricia Ruy (René Rachou Research Center, Laboratory of Cellular and Molecular Parasitology); Guilherme Oliveira (René Rachou Research Center, Laboratory of Cellular and Molecular Parasitology); Jeronimo Conceição Ruiz (René Rachou Research Center, Laboratory of Cellular and Molecular Parasitology); |
| Short Abstract: In this study we are developing/implementing a computational pipeline to perform the analysis of intrinsically unstructured proteins in S.mansoni predicted proteome. The developed database integrate the consensus predictions of disorder predictors together with several physical and chemical protein proprieties aiming the identification of molecules related to host/pathogen interactions. |
| Long Abstract: Click Here |
| Poster A50 |
| Design, synthesis and biological evaluation of 5-lipoxygenase inhibitors: Structure and Ligand Based Drug Design approaches |
| Aparoy Polamarasetty- University of Hyderabad |
| Reddanna P (University of Hyderabad, School of Life Sciences); Reddy RN (Rational Labs Pvt. Ltd., Hyderabad); |
| Short Abstract: In this study, homology model of 5-lipoxygenase was built and iron was incorporated at the catalytic domain using in-house programs. This model was used to design potential inhibitors by employing drug design strategies. The molecules showed potent inhibition of 5-lipoxygenase in in vitro assays suggesting the reliability of the model |
| Long Abstract: Click Here |
| Poster A51 |
| NextGen Transcriptome Analysis of a Transmissible Cancer |
| Arthur Hsu- The Walter and Eliza Hall Institute of Medical Research |
| Elizabeth Murchison (Wellcome Trust Sanger Institute, Genomic Research); Jenny Graves (Australian National University, Research School of Biological Sciences); Tony Papenfuss (The Walter and Eliza Hall Institute of Medical Research, Bioinformatics); |
| Short Abstract: In this work, we sequenced the tumour and normal tissue transcriptomes of a Tasmanian devil. Our annotation of this non-model organism and digital differential expression analysis, in conjunction with micro RNA analysis and laboratory experiments, have identified the progenitor cell and surface marker of the transmissible cancer. |
| Long Abstract: Click Here |
| Poster A52 |
| Deriving binding site signatures in MHC Class II molecules, using a novel algorithm |
| Nagasuma Chandra- Indian Institute of Science |
| Kemp Graham J.L. (Chalmers University of Technology, Department of Computer Science and Engineering); Kalidas Yeturu (Indian Institute of Science, BIC/SERC); |
| Short Abstract: A thorough knowledge of the binding sites of MHC Class II molecules,important components of the immune system, will be of immense help indesigning or identifying peptide antigens for rational vaccine design.Here we report a new algorithm to compare structures of binding sites ofMHC class II molecules. |
| Long Abstract: Click Here |
| Poster A53 |
| An expectation-maximisation algorithm for identification of somatic substitutions in cancer genomes from next-generation sequencing data |
| David Jones- Wellcome Trust Sanger Institute |
| Peter Campbell (Wellcome Trust Sanger Institute, Cancer Genome Project); Erin Pleasance (Wellcome Trust Sanger Institute, Cancer Genome Project); Phil Stephens (Wellcome Trust Sanger Institute, Cancer Genome Project); Sarah O'Meara (Wellcome Trust Sanger Institute, Cancer Genome Project); David McBride (Wellcome Trust Sanger Institute, Cancer Genome Project); Meng-Lay Lin (Wellcome Trust Sanger Institute, Cancer Genome Project); MingMing Jia (Wellcome Trust Sanger Institute, Cancer Genome Project); David Beare (Wellcome Trust Sanger Institute, Cancer Genome Project); Adam Butler (Wellcome Trust Sanger Institute, Cancer Genome Project); Jon Teague (Wellcome Trust Sanger Institute, Cancer Genome Project); Michael Stratton (Wellcome Trust Sanger Institute, Cancer Genome Project); Andrew Futreal (Wellcome Trust Sanger Institute, Cancer Genome Project); |
| Short Abstract: Developing a variant calling application to detect single base mutations and SNPs in entire cancer genomes using an expectation-maximisation algorithm to compare normal and tumour reads generated by new sequencing technology platforms. |
| Long Abstract: Click Here |
| Poster A54 |
| Improving interpretability of survival models built from gene expression data with gene groups as additional covariates |
| Kai Kammers- TU Dortmund |
| Jörg Rahnenführer (TU Dortmund, Statistics); |
| Short Abstract: An important application of high dimensional gene expression measurements is the prediction of survival times of cancer patients.In order to improve the interpretability of the estimated models, we summarize genes as gene groups defined by the Gene Ontology and include these gene groups as covariates in the models. |
| Long Abstract: Click Here |
| Poster A55 |
| A Mathematical Framework for the Selection of an Optimal Set of Peptides for Epitope-Based Vaccines |
| Nora Toussaint- Eberhard-Karls-Universität |
| Oliver Kohlbacher (Eberhard-Karls-Universität, Simulation of Biological Systems); Pierre Dönnes (AstraZeneca R&D, Molecular Toxicology, Safety Assessment); |
| Short Abstract: Epitope-based vaccines(EVs) trigger an immune response via target-specific immunogenic peptides (epitopes). A crucial step in EV design is the selection of the epitopes to be included. This complex task is typically performed manually. We present a mathematical framework to find an optimal set of epitopes for an epitope-based vaccine. |
| Long Abstract: Click Here |
| Poster A56 |
| Cancer survival analysis from gene expression data: Non-uniform distribution of p-values under the null hypothesis |
| Esteban Czwan- German Cancer Research Center |
| David Kipling (Cardiff University, Pathology); Benedikt Brors (German Cancer Research Center, Theoretical Bioinformatics); |
| Short Abstract: In gene expression microarray studies, the distribution of p-values under the null hypothesis is often not uniform. An automated methodology which empirically approximates the distribution of p-values under the null hypothesis was developed in order to test whether predefined sets of biologically-related genes are associated with cancer prognosis. |
| Long Abstract: Click Here |
| Poster A57 |
| The use of a multi-class classifier in genome wide genetic analysis showed the existence of a distinct immature acute leukemia in T-lymphoid leukemia |
| Erdogan Taskesen- Erasmus University Medical Center |
| Bas J. Wouters (Erasmus University Medical Center, Hematology); Ruud Delwel (Erasmus University Medical Center, Hematology); |
| Short Abstract: With the creation of a multi-class classifier, trained on gene expression signature existing out of a various set of classes, we showed the true existence of a leukemia subtype having myeloid and T-lymphoid characteristics. This subtype is identified in our cohort, an independent AML cohort and a T-ALL cohort. |
| Long Abstract: Click Here |
| Poster A58 |
| Time-series and gene co-expression analyses of transcriptional changes in human monocyte RNAs after acute myocardial infarction. The Lübeck MI study |
| Seraya Maouche- INSERM UMRS 937 Cardiovascular Genomics |
| Stefanie Belz Belz (Department of Medicine, University of Lübeck, Lübeck); Jessy Brocheton (NSERM UMRS 937, Cardiovascular Genomics); Carole Proust (NSERM UMRS 937, Cardiovascular Genomics); Jeanette Erdmann (University of Lübeck, Department of Medicine); Heribert Schunkert (University of Lübeck, Department of Medicine); François Cambien (INSERM UMRS 937, Cardiovascular Genomics); Patrick Linsel- Nitschke (University of Lübeck, Department of Medicine); |
| Short Abstract: Myocardial Infarction is associated with an-inflammatory reaction and peripheral recruitment of monocytes to the injured-area. We investigated the temporal-transcriptional changes in monocytes post-MI. Co-expression modules identification combined to gene-set enrichment analysis identified genes of putative interest and revealed enrichment in major pathways pertaining to chemokine-receptor-activity, and regulation of heart contraction. |
| Long Abstract: Click Here |
| Poster A59 |
| On the influence of codon choice on viral protein synthesis: A kinetic approach |
| Diego Frias- University of the State of Bahia |
| Bernardo Galvão-Castro (CPgGM-Fiocruz Salvador, LASP); Filipe Rego (CPgGM-Fiocruz Salvador, LASP); Luiz Carlos Junior Alcantara (CPgGM-Fiocruz Salvador, LASP); |
| Short Abstract: A kinetic model is proposed for evaluating the rate of synthesis of viral proteins. The model takes into account the correspondence between the codon composition of viral mRNA and cognate tRNA availability. The model suggest that an intelligent codon choice could differ from that of the host. |
| Long Abstract: Click Here |
| Poster A60 |
| Hypothesis-driven cancer survival analysis from gene expression data: on the non-uniform distribution of p-values under the null hypothesis |
| Esteban Czwan- German Cancer Research Center |
| David Kipling (Cardiff University, Pathology); Benedikt Brors (German Cancer Research Center, Theoretical Bioinformatics); |
| Short Abstract: In hypothesis testing based on gene expression microarray data, the distribution of p-values under the null hypothesis is often not uniform. An automated methodology which empirically approximates the distribution of null p-values was developed in order to test whether predefined sets of biologically-related genes are associated with cancer prognosis. |
| Long Abstract: Click Here |
| Poster A61 |
| Whole genome analysis of mtDNA natural evolution in human and in cancer |
| Eitan Rubin- Ben Gurion University |
| Ilia Zhidkov (Ben Gurion University, Shraga Segal Dept. Microbiology and Immunology); Erez A. Livneh (Ben Gurion Univeristy, Shraga Segal Dept. Microbiology and Immunology); Dan Mishmar (Ben-Gurion University of the Negev , Life Sciences); |
| Short Abstract: Little attention has been paid to similarities in the signatures of selection in tumor cells and human populations. We show significant parallels in the mutational landscapes of mtDNA in cancer and normal human populations suggesting similar selective constraints. |
| Long Abstract: Click Here |
| Poster A62 |
| Non-redundant patent sequence databases with value added annotations |
| Weizhong Li- EMBL - European Bioinformatics Institute |
| Ana Richart de la Torre (EPO, Information Life Sciences); Adam Grodowski (EPO, Information Life Sciences); Irina Benediktovich (EPO, Information Life Sciences); Hamish McWilliam (EBI, External Services); Stephane Nauche (EPO, Information Life Sciences / Head); Rodrigo Lopez (EBI, External Services / Head); |
| Short Abstract: Non-redundant patent sequence databases have been created at two levels. At level 1 redundancy is removed at the sequence level. At level 2 patent equivalent are used to remove redundancy from multiple national submissions of the same patent. Sequence annotations from same family members are merged in level 2. |
| Long Abstract: Click Here |
| Poster A63 |
| AN APPROACH TO PREDICTION OF THE HAEMATOPOIETIC STEM CELL TRANSPLANTATION OUTCOME USING HUMAN LEUKOCYTE ANTIGEN MISMATCH INFORMATION MAPPED ON PROTEIN STRUCTURE DATA |
| Malgorzata Dudkiewicz- Warsaw University of Life Sciences |
| No additional authors |
| Short Abstract: This analysis was made to model interactions between protein products of the different HLA alleles of the transplant recipient and the T- Lymphocyte Cell Receptors from the donor immunological system.The results of interaction energy calculations allow us to suppose that the energy of contacts between TCR and HLA can influence HSCT outcome. |
| Long Abstract: Click Here |
| Poster A64 |
| Omics profile integration for characterizing Kidney Diseases |
| Irmgard Mühlberger- Medical University of Innsbruck |
| Paul Perco (emergentec biodevelopment GmbH, Research and Development); Andreas Bernthaler (Technical University of Vienna, Theory and Logic Group); Raul Fechete (emergentec biodevelopment GmbH, Research and Development); Rainer Oberbauer (Medical University of Vienna, Department of Internal Medicine); Gert Mayer (Medical University of Innsbruck, Department of Internal Medicine); Arno Lukas (emergentec biodevelopment GmbH, Research and Development); Bernd Mayer (emergentec biodevelopment GmbH, Research and Development); |
| Short Abstract: For investigating molecular mechanisms causing kidney failure we have initiated a collection of kidney tissue profiling data including transcriptomics, proteomics, and metabolomics studies. We will present analysis results from mapping the established collection of heterogeneous omics data on a molecular dependency graph representing the entire human proteome. |
| Long Abstract: Click Here |
| Poster A65 |
| Drug-target interaction maps for computational drug repositioning discovery |
| Yvonne Li- Canada’s Michael Smith Genome Sciences Centre |
| Anna Stratford (Child and Family Research Institute, University of British Columbia, Department of Pediatrics); Kaiji Hu (Child and Family Research Institute, University of British Columbia, Department of Pediatrics); Sandra Dunn (Child and Family Research Institute, University of British Columbia, Department of Pediatrics); Jianghong An (BC Cancer Agency, Canada’s Michael Smith Genome Sciences Centre); Steven Jones (BC Cancer Agency, Canada’s Michael Smith Genome Sciences Centre); |
| Short Abstract: We developed a computational drug repositioning pipeline that performs large-scale molecular docking of small molecule drugs against protein drug targets, to map the drug-target interaction space. We emphasize methods to remove potential false positive repositioning candidates. Novel interactions discovered may add insight into drug therapeutic utility, cellular mechanisms, and side-effects. |
| Long Abstract: Click Here |
| Poster A66 |
| Diagnostic and Prognostic Utility of a Universal Cancer Feature Set |
| Joseph Irgon- Centocor R&D (J&J), Rutgers University, Princeton University |
| No additional authors |
| Short Abstract: Comparing microarray data for normal tissue and solid tumors in breast, lung, colon, prostate and ovarian tissue we identified a universal 104 gene panel which we used to define a global feature set. Using SVM classification on several public data sets, we found this panel outperformed those associated with the publication. |
| Long Abstract: Click Here |
| Poster A67 |
| In vivo dynamics of the intracellular metabolite concentrations in response to the pulse addition of substrate for the mutants and the wild type of E.coli |
| Md. Hoque- University of Malaya |
| No additional authors |
| Short Abstract: An integrated study on cell growth parameters, product formation and the dynamics of intracellular metabolite concentrations were investigated in this study. Comparative investigation was also performed for the wild E.coli using acetate or pyruvate as the sole carbon source with its pgi and zwf mutants using glucose as sole carbon. |
| Long Abstract: Click Here |
| Poster A68 |
| Designing a Comparison Method of Protein using Particular Sub-Structure |
| Nam Hee Yu- Database/Bioinformatics Lab. |
| Kwang Su Jung (Database/Bioinformatics Lab., Chungbuk National University); Keun Ho Ryu (Database/Bioinformatics Lab., Chungbuk National University); Yong Je Chung (vision of Life Sciences, Chungbuk National University); |
| Short Abstract: In this paper, we proposed a novel method to compare protein surface sub-structure including active site between alpha carbon and beta carbon of residues. This method uses the sub-structure of protein surface expressed by a pair of triangles and its distance matrix. |
| Long Abstract: Click Here |
| Poster A69 |
| Identifying Protein Complexes related to Multigenic Diseases |
| Antonio Mora- University Of Oslo |
| Ian Donaldson (Group Leader, Biotechnology Centre of Oslo); Katerina Michalickova (Biotechnology Centre of Oslo / USIT, Donaldson's group); |
| Short Abstract: We compare databases of protein complexes to groups of proteins that are assumed to be involved in the same disease, in order to computationally determine all known diseases that can be related to known protein complexes in humans. We compare 474 disease groups from OMIM to two protein complex databases. |
| Long Abstract: Click Here |
| Poster A70 |
| Dissecting the dynamics of dysregulation of cellular processes in mouse mammary gland tumor |
| Wieslawa Mentzen- Parco Scientifico e Technologico POLARIS |
| Matteo Floris (Parco Scientifico e Technologico POLARIS, CRS4 Bioinformatics Lab); Alberto de la Fuente (Parco Scientifico e Technologico POLARIS, CRS4 Bioinformatics Lab); |
| Short Abstract: A novel integrative approach, combining interactome-guided designation of biological processes with differential expression and differential co-expression analyses was applied to expression data from mouse mammary gland tumor, resulting in the identification of processes with altered intensity or co-regulation during tumor progression, and discovery of regulatory microRNAs involved in tumorigenesis. |
| Long Abstract: Click Here |
| Poster A71 |
| COMPARATIVE ANALYSIS OF PRIMARY BLADDER AND BREAST TUMORS AND THEIR RECURRENCES WITH THE TUMULT ALGORITHM |
| Eric Letouzé- MTi, INSERM U973 |
| Yves Allory (Henri Mondor Hospital, Urology Department); François Radvanyi (Curie Institute, UMR144); Frédéric Guyon (MTi INSERM U973, Bioinformatics); |
| Short Abstract: Comparative analysis of copy number profiles of several tumors from a same patient enables reconstruction of the sequence of events at the origin of the cancer. Here we present the first biological results obtained with our algorithm, TuMult, on bladder and breast series of tumors analyzed with SNP microarrays. |
| Long Abstract: Click Here |
| Poster A72 |
| Building maintainable, exhaustive human mitochondrial phylogenies |
| Roberto Blanco- University of Zaragoza |
| Elvira Mayordomo (University of Zaragoza, Computer Science & Systems Engineering); |
| Short Abstract: We introduce a workflow-based architecture capable of efficiently reconstructing phylogenies from extremely large datasets, which has been used to breathe new life into the dated human mitochondrial phylogeny, where manual curation is not affordable any more. We describe advancements and current results, as well as areas of future work. |
| Long Abstract: Click Here |
| Poster A73 |
| Methods for finding and characterizing virus sequences in metagenome 454 data |
| Fredrik Lysholm- Linköping University |
| Björn Andersson (Karolinska Institutet, CMB); Bengt Persson (Linköping University, IFM Bioinformatics); |
| Short Abstract: We have analysed virus sequences from patient samples using 2nd generation sequencing techniques such as 454 sequencing, producing massive amounts of data. We have developed methods for handling large amount of sequencing data by efficient screening pipelines. Furthermore, we have developed strategies for classification and characterization of metagenome samples. |
| Long Abstract: Click Here |
| Poster A74 |
| Transcriptomic and genomic analysis of uveal melanoma tumors. |
| Cécile Laurent- Institut Curie |
| Fabien Valet (Institut Curie, U900 - Cancer et Génome bioinformatique, biostatistiques et épidémiologie d'un système complexe); Océane Anezo (Institut Curie, UMR146 - UMR146 Régulations cellulaires et oncogenèse); Philippe Hupé (Institut Curie, U900 - Cancer et Génome bioinformatique, biostatistiques et épidémiologie d'un système complexe); Jérôme Couturier (Institut Curie, Department of Tumor Biology); Ingrid Lebigot (Institut Curie, Department of Tumor Biology); Pascale Mariani (Institut Curie, Department of Oncologic Surgery); Corinne Planchet (Institut Curie, U900 - Cancer et Génome bioinformatique, biostatistiques et épidémiologie d'un système complexe); Olivier Delattre (Institut Curie, Department of Tumor Biology); Xavier Sastre (Institut Curie, Department of Tumor Biology); Sergio Roman-Roman (Institut Curie, Translational Research Department); Bernard Asselain (Institut Curie, U900 - Cancer et Génome bioinformatique, biostatistiques et épidémiologie d'un système complexe); Sophie Piperno-Neumann (Institut Curie, Department of Oncologic Surgery); Emmanuel Barillot (Institut Curie, U900 - Cancer et Génome bioinformatique, biostatistiques et épidémiologie d'un système complexe); Simon Saule (Institut Curie, UMR146 Régulations cellulaires et oncogenèse); |
| Short Abstract: We present here an analysis of gene expression profiling and array-comparative genomic hybridization of our uveal melanoma primary tumors collection and liver metastasis. The aim of this study is to identify molecular markers associated with high-risk patients (early metastasizing pattern) by compared analysis of high- and low- risk tumors. |
| Long Abstract: Click Here |
| Poster A75 |
| An exploratory Analysis of Signaling Pathways involved in Bladder Cancer using Independent Component Analysis. |
| Anne Biton- Institut Curie - INSERM U900 - CNRS UMR144 - Mines Paritech |
| Emmanuel Barillot (Institut Curie - INSERM U900 - Mines Paritech, Cancer et Génome bioinformatique, biostatistiques et épidémiologie d'un système complexe); Andrei Zynovyev (Institut Curie - INSERM U900 - Mines Paritech, Cancer et Génome bioinformatique, biostatistiques et épidémiologie d'un système complexe); François Radvanyi (Institut Curie - CNRS UMR144, Oncologie moléculaire); |
| Short Abstract: We apply ICA on a bladder cancer expression dataset including 175 tumours in order to investigate the potentially involved signaling pathways. Our results show that ICA is a promising method to identify pathways involved in tumours progression, to filter out contamination signals, and to correlate genome alterations to gene expression. |
| Long Abstract: Click Here |
| Poster A76 |
| Evaluating the correct control for prostate cancer using microarray data analysis |
| Prashant Srivastava- DKFZ |
| Brors Benedikt (DKFZ, Department of Theoretical Bioinformatics); Hermann-Josef Gröne (DKFZ, Department of Cellular and Molecular Pathology); Alexander Feuerborn (DKFZ, Department of Cellular and Molecular Pathology); William Aaron Grandy (DKFZ, Department of Cellular and Molecular Pathology); Norbert Gretz (University of Heidelberg, Medical Research Center, Mannheim); |
| Short Abstract: Choosing an optimal control can be crucial for any experiment. In this study we have demonstrated that choice of control tissues influences interpretation for certain sets of genes and pathways in gene expression analysis of prostate cancer. This may potentially mask the detection of putative early stage marker genes. |
| Long Abstract: Click Here |
| Poster A77 |
| Prediction of drug resistance in lung cancer cell lines |
| Christian Netzer- TU Dortmund University |
| Jörg Rahnenführer (TU Dortmund University, Statistics); |
| Short Abstract: We analyze multivariate measurements of genetic lesions in lung cancer cell lines. Our goal is the identification of combinations of lesions that are crucial for the prediction of therapy outcome. We present approaches for dichotomizing drug resistance values. For relevant cancer drugs like erlotinib we identify biologically plausible cutpoints. |
| Long Abstract: Click Here |
| Poster A79 |
| Impact analysis of somatic mis-sense single base mutations from cancer genome sequencing |
| Zhen Shi- University of Maryland |
| John Moult (University of Maryland Biotechnology Institute, CARB); |
| Short Abstract: Many somatic mutations have emerged from cancer genome sequencing. To distinguish ‘driver’ from ‘passenger’ mutations, we utilized SNPs3D, initially developed for assessing the impact of missense SNPs on protein activity or stability. Approximately 50% of cancer missense mutations are of high impact. Most mutations in tumor suppressors destabilize protein structures. |
| Long Abstract: Click Here |
| Poster A81 |
| Altered protein-protein interactions during the pathogenesis of orofacial clefts |
| Albertas Timinskas- Institute of Biotechnology |
| No additional authors |
| Short Abstract: Cleft lip and/or cleft palate are most frequent human craniofacial birth defects with a complex multifactorial etiology. By use of available protein-protein interaction databases and suggested iterative analysis procedures we were able to purify available data on communication of proteins during craniofacial morphogenesis and also to offer new potential actors. |
| Long Abstract: Click Here |
| Poster A82 |
| Bioinformatics for Pathogen Genomics - The Enteropathogen Resource Integration Center (ERIC), A NIAID Bioinformatics Resource Center for Biodefense and Emerging/Re-Emerging Infectious Disease |
| John Greene- SRA International, Inc. |
| David Pot (SRA International, Health Research Technology Services); Jon Whitmore (SRA International, Health Research Technology Services); Matthew Shaker (SRA International, Health Research Technology Services); Joel Fedorko (SRA International, Health Research Technology Services); Kamini Joshi (SRA International, Health Research Technology Services); Panna Shetty (SRA International, Health Research Technology Services); Jeyanthi Thangiah (SRA International, Health Research Technology Services); Sam Zaremba (SRA International, Health Research Technology Services); Guy Plunkett III (University of Wisconsin-Madison, Genetics); Jeremy Glasner (University of Wisconsin-Madison, Genetics); Brad Anderson (University of Wisconsin-Madison, Genetics); Bryan Biehl (University of Wisconsin-Madison, Genetics); Valerie Burland (University of Wisconsin-Madison, Genetics); Eric Cabot (University of Wisconsin-Madison, Genetics); Eric Neeno-Eckwall (University of Wisconsin-Madison, Genetics); Bob Mau (University of Wisconsin-Madison, Genetics); Paul Liss (University of Wisconsin-Madison, Genetics); Michael Rusch (University of Wisconsin-Madison, Genetics); Frederick Blattner (University of Wisconsin-Madison, Genetics); Nicole Perna (University of Wisconsin-Madison, Genetics); |
| Short Abstract: ERIC (www.ericbrc.org) is an NIAID Bioinformatics Resource Center focused on enteropathogens, and continues to evolve to provide analysis tools for integrated access to data on 101 genomes to date. We provide curated genome annotation of these organisms with evidence codes, and tools for comparative genomics, microarray analysis, and text mining. |
| Long Abstract: Click Here |
| Poster A83 |
| Incorporating detailed information on treatment history affords more accurate prediction of the effects of anti-HIV therapy |
| Hiroto Saigo- Max Planck Institute |
| No additional authors |
| Short Abstract: For improving the prediction of the response to anti-HIV therapy, we propose to incorporate the order of the previously prescribed regimens and their short time responses. In order to handle resulting high-dimensional feature space, our sequence boosting algorithm calls the sequence mining iteratively, and extends the feature space progressively |
| Long Abstract: Click Here |
| Poster A84 |
| A Protein Surface Comparing Method using Structure Factor |
| KWANG SU JUNG- CBITRC, PTERC, CHUNGBUK NATIONAL UNIV |
| NAM HEE YU (CBITRC, PTERC, CHUNGBUK NATIONAL UNIV, COMPUTER SCIENCE); KEUN HO RYU (CBITRC, PTERC, CHUNGBUK NATIONAL UNIV, COMPUTER SCIENCE); YONG JE CHUNG (CBITRC, PTERC, CHUNGBUK NATIONAL UNIV, LIFE SCIENCE); |
| Short Abstract: Proteins need to combine other substrates or proteins to perform their function, and proteins which have similar actives sites have similar function.We suggest a method to compare partial surfaces of proteins using structure factors and phase angles. Our work can be adopted to produce proteins which have more functionality. |
| Long Abstract: Click Here |
| Poster B01 |
| Comparative analysis of computational models of two-enzyme systems in presence of a competitive inhibitor in case of isolated and complex interactions between enzymes |
| Armen Takgyozyan- Yerevan State University |
| Aram Gevorgyan (Yerevan State University, Biophysics); Emil Gevorgyan (Yerevan State University, Biophysics); Valeri Arakelyan (Yerevan State University, Physics); |
| Short Abstract: Two models were created by STELLA package. In two-enzyme chain complex interaction of enzymes increases the products concentrations. It also causes sharp variations in change dynamics of products concentrations, which is the result of competition between enzymes. Complex interaction of enzymes does not affect change dynamics of inhibitor’s concentration. |
| Long Abstract: Click Here |
| Poster B02 |
| Primary response of myoglobin studied by time-dependent Linear Response Theory (LRT) |
| Lee Yang- University of Tokyo |
| Akio Kitao (University of Tokyo, Institute of Molecular and Cellular Biosciences); Nobuhiro Gō (Japan Atomic Energy Agency, Neutron Biology Research Center); |
| Short Abstract: Induce-fit (or sequential/KNF) model, explaining ligand-induced conformational changes, is re-comprehended in the context of a linear response theory (LRT). Here we formulated a time-dependent LRT to address experimentally observed myoglobin primary response at a time scale from femto- to 10s picoseconds. |
| Long Abstract: Click Here |
| Poster B03 |
| Electron tomography and molecular modeling study of chemoreceptor organization |
| Xiongwu Wu- National Institutes of Health |
| Peijun Zhang (University of Pittsburgh, Structural Biology); Cezar Khursigara (NIH, NCI); Sriram Subramaniam (NIH, NCI); Bernard Brooks (NIH, NHLBI); |
| Short Abstract: Through cryo-electron tomography and map-constrained molecular dynamics simulations, we obtained the assembly structures of tsr organized in a two dimensional array. It is suggested that the position of the ligand binding domain and the HAMP domain play a pivotal role in mediating signal transduction across the cell membrane. |
| Long Abstract: Click Here |
| Poster B04 |
| Assisted crystallographic RNA model building: A directed rotameric approach for building the RNA backbone |
| Kevin Keating- Yale University |
| Anna Marie Pyle (Yale University & HHMI, Molecular Biophysics and Biochemistry); |
| Short Abstract: The backbone of RNA is critical for function, but studies of the backbone have long been hampered by the difficulty of accurately determining its structure. We have combined a reduced representation of RNA with an all-atom rotamer library to increase the ease and accuracy of crystallographic backbone structure determination. |
| Long Abstract: Click Here |
| Poster B05 |
| Conformational energies and entropies of peptides. Dependence on sequence type, and relation to peptide-protein binding. |
| Evrim Besray Ünal- Koc University |
| Burak Erman (Prof., Chemical and Biological Engineering); Attila Gürsoy (Assoc. Prof., Computer Engineering); |
| Short Abstract: A novel statistical thermodynamics approach is applied to the free peptide segments to classify them according to their entropies, conformational energies and heat capacities. Our approach employs the rotational isomeric states model. Low energy, low entropy and low heat capacity determined to be essential for a good candidate inhibitor peptide. |
| Long Abstract: Click Here |
| Poster B06 |
| Structural Insights into Bacterial Signal Transduction |
| Martín Graña- Institut Pasteur Montevideo |
| Hugo Naya (Institut Pasteur Montevideo, Bioinformatics Unit); Pedro Alzari (Institut Pasteur, Structural Biochemistry Unit); Alejandro Buschiazzo (Institut Pasteur Montevideo, Protein Crystallography Unit); |
| Short Abstract: Signal transduction in prokaryotes is conducted primarily by two-component regulatory systems, basically a sensor histidine kinase and a response regulator. Several genomes revealed additional signal transduction modes, in particular Ser/Thr kinases. We provide structure/sequence insights on a His kinase family and a Ser/Thr kinase family, providing with candidate mutations. |
| Long Abstract: Click Here |
| Poster B07 |
| Paying the entropic cost: peptides and proteins in a bind |
| Ora Schueler-Furman- The Hebrew University of Jerusalem |
| No additional authors |
| Short Abstract: Strategies for peptide-protein binding are identified by a computational structural analysis of peptide-protein complex structures. The protein uses a “prepaid strategy” where no significant conformational changes occur, thereby reducing entropy reduction to the peptide. The peptide forms exceptionally many contacts and hydrogen bonds, thus maximizing enthalpy gain. |
| Long Abstract: Click Here |
| Poster B08 |
| Can we trust results from protein – ligand docking? Evaluation of the most commonly used docking programs on PDBbind database |
| Dariusz Plewczynski- University of Warsaw |
| Michal Lazniewski (University of Warsaw, ICM); Rafal Augustyniak (University of Warsaw, ICM); Krzysztof Ginalski (University of Warsaw, ICM); |
| Short Abstract: Molecular recognition plays a fundamental role in all biological processes and that is why great efforts have been made to understand and predict such kind of interactions.The purpose of our studies was to evaluate widely used docking tools on all protein-ligand complexes from PDBbind database (large set of 1300 complexes) |
| Long Abstract: Click Here |
| Poster B09 |
| A graphical model approach for predicting free energies of association for protein-protein interactions under backbone and side-chain flexibility |
| Hetunandan Kamisetty- Carnegie Mellon University |
| Christopher J (Carnegie Mellon University, Computer Science Department); Chris Bailey-Kellogg (Dartmouth College, Computer Science); |
| Short Abstract: We present GOBLIN, the first graphical-model based approach for predictingbinding free energies for all-atom models of protein complexes.GOBLIN uses a rigorous approximation to the partitionfunction of the system that is fast and accurate. Our resultsindicate the utility of accounting for entropic contributions to the bindingfree energy. |
| Long Abstract: Click Here |
| Poster B10 |
| Disordered flanks prevent peptide aggregation. |
| Sanne Abeln- FOM Institute for Atomic and Molecular Physics [AMOLF] |
| No additional authors |
| Short Abstract: We report a Monte Carlo study that aims to elucidate the role of disordered regions in proteins adjacent to binding motifs. Coarse-grained simulations show that small hydrophobic peptides without disordered flanks tend to aggregate under conditions where peptides embedded in unstructured peptide sequences remain soluble. |
| Long Abstract: Click Here |
| Poster C01 |
| An Open Source Workflow Approach to QSAR Modelling and Learning |
| Adeshola Adefioye- K.U. Leuven |
| Bart De Moor (K.U. Leuven, ESAT/SCD (SISTA)); |
| Short Abstract: PLS a multivariate method used for QSAR modelling. Descriptors correlating to causality are carefully selected for modelling. Continual reassessment of the model takes place. Further classification done using SVM. Multi-instance learning using multiple 3D conformations of molecules will be carried out. Aided by KNIME. |
| Long Abstract: Click Here |
| Poster C02 |
| Largest Common Chemical Feature Subtree as a Virtual Screening Method |
| Thomas Kristensen- Aarhus University |
| Christian Pedersen (Aarhus University, BiRC - Bioninformatic Research Center); Mikael Christensen (Molegro, BiRC); Rene Thomsen (Molegro, BiRC); |
| Short Abstract: We investigate the effectiveness of using a tree comparison based method for virtual screening. In our method, molecules are reduced to trees and we compare our method to other ligand based methods on the DUD dataset. The results of our experiments indicate that our method is comparable and sometimes better. |
| Long Abstract: Click Here |
| Poster C03 |
| Optimal Overlay of Ligands with Dlexible Bonds using Differential Evolution |
| Christian Pedersen- Aarhus University |
| Thomas Greve Kristensen (Aarhus University, BiRC- Bioinformatics Research Center); |
| Short Abstract: When designing novel drugs, the need arise to screen databases for structures resembling active ligands, e.g. by generating a query meta-structure which summarizes these. We propose a flexible bond method for making a meta-structure and present Monte Carlo, Nelder-Mead and Differential Evolution implementations. Our experiments indicate that DE is superior. |
| Long Abstract: Click Here |
| Poster C04 |
| Predicting Metabolite Fate Potential |
| Chris Sinclair- Food & Environment Research Agency |
| Robert Stones (FERA, Statistics & Informatics); Alistair Boxall (FERA, Ecological Chemistry Unit); |
| Short Abstract: There is a need to a reduction in animals used in toxicity studies. Organisms exposed to chemicals, the chemical may be bioconcentrated. Chemicals metabolised varies and may be metabolised by specific taxa or are non-metabolisable. Objective of this study was to develop new software tools to validate this concept. |
| Long Abstract: Click Here |
| Poster C05 |
| HOMOLOGY MODELING AND MOLECULAR DYNAMICS OF THE MONILIPHOTHORA PERNICIOSA CHITIN SYNTHASE ACTIVE SITE, THE AGENT OF WITCHES’ BROOM DISEASE OF COCOA |
| Bruno Andrade- State University of Feira de Santana |
| Catiane Souza (State University of Feira de Santana, Biological Sciences); Alex Taranto (State University of Feira de Santana, Health Sciences); Aristóteles Góes-Neto (State University of Feira de Santana, Biological Sciences); Sandra Assis (State University of Feira de Santana, Health Sciences); Rafaela Galante (State University of Feira de Santana, Health Sciences); Júlio Cascardo (State University of Santa Cruz, Biological Sciences); |
| Short Abstract: Chitin synthases (CHS) are the main component of the fungal cell wall and highly specific molecular targets for drugs. In this work, a model of Moniliophthora perniciosa CHS active site was constructed using Homology Modeling approach, and it was refined by a set of Molecular Mechanics and Molecular Dynamics. |
| Long Abstract: Click Here |
| Poster C06 |
| Automated tracking of proteome-wide drug target opportunities |
| Stephen Campbell- Pfizer |
| Sid Martin (Pfizer, Computational Sciences); Anna Gaulton (Pfizer, Computational Sciences); Dmitri Bichko (Pfizer, Computational Sciences); Robert Hernandez (Pfizer, Computational Sciences); Markella Skempri (Pfizer, Computational Sciences); Cory Brouwer (Pfizer, Computational Sciences); Lee Harland (Pfizer, Computational Sciences); |
| Short Abstract: Vast databanks of information present an ever-increasing challenge to drug discovery scientists. A novel data reduction and visualisation method assembles virtual maps of drug target opportunities. High impact incoming information can be detected and alerted on, according to the degree with which it alters the map. |
| Long Abstract: Click Here |
| Poster C07 |
| Real-time ray tracing of complex molecular scenes with BALLView and RTfact |
| Anna Dehof- Saarland University |
| Anne Dehof (Saarland University, Center for Bioinformatics); Iliyan Georgiev (Saarland University, Computer Graphics); Lukas Marsalek (Saarland University, Computer Graphics); Daniel Stoeckel (Saarland University, Center for Bioinformatics); Stefan Nickels (Saarland University, Center for Bioinformatics); Hans-Peter Lenhof (Saarland University, Center for Bioinformatics); Philipp Slusallek (Saarland University, Computer Graphics); Andreas Hildebrandt (Saarland University, Center for Bioinformatics); |
| Short Abstract: Molecular visualization is one of the cornerstones of structural bioinformatics,computational chemistry, and related fields. We present the first integration of a general purpose real-time ray tracingarchitecture into a molecular viewing and modelling tool by integratingthe RTfact library into BALLView, a versatile molecular viewing and editing tool. |
| Long Abstract: Click Here |
| Poster C08 |
| Leveraging Ligand-Protein Cross-interaction Information for In Silico Prediction of CYP Inhibition: Critical Assessment with In Vitro Assays |
| Teppei Ogawa- Kyoto University |
| Yohsuke Minowa (National Institute of Biomedical Innovation, Toxicogenomics-Informatics Project); Tetsuya Adachi (Kyoto University, Graduate School of Pharmaceutical Sciences); Chunlai Feng (Kyoto University, Graduate School of Pharmaceutical Sciences); Satoshi Niijima (Kyoto University, Graduate School of Pharmaceutical Sciences); Shinya Oishi (Kyoto University, Graduate School of Pharmaceutical Sciences); Nobutaka Fujii (Kyoto University, Graduate School of Pharmaceutical Sciences); Yasushi Okuno (Kyoto University, Graduate School of Pharmaceutical Sciences); |
| Short Abstract: We propose a comprehensive model for predicting CYP inhibition by leveraging ligand-CYP cross-interaction information. The proposed model was compared with existing models in terms of predictive ability and extracted features using large-scale interaction data. More importantly, we conducted in vitro bioassays to critically assess the general applicability of current techniques. |
| Long Abstract: Click Here |
| Poster C09 |
| Evaluating small molecule libraries using molecular docking and binding profile analysis |
| Annamária Ángyán- Eotvos Lorand University |
| Gábor Iván (Eotvos Lorand University, Department of Computer Science); Vince Grolmusz (Eotvos Lorand University, Department of Computer Science); |
| Short Abstract: Based on a specific small molecule that had been predicted to bind to a given protein, we designed a number of similar ligands. Using molecular docking, we predicted binding energies and conformations of the elements of this ligand library. We then evaluated our results by analyzing the protein's binding amino acids for each protein-ligand complex. |
| Long Abstract: Click Here |
| Poster C10 |
| Similarity of Chemical Mechanisms in Functionally Analogous Enzymes |
| Daniel Almonacid- University of California San Francisco |
| Emmanuel R Yera (University of California San Francisco, Department of Bioengineering and Therapeutic Sciences); John BO Mitchell (University of Cambridge, Department of Chemistry); Patricia C Babbitt (University of California San Francisco, Department of Bioengineering and Therapeutic Sciences); |
| Short Abstract: We compared 95 pairs of functionally analogous enzymes (enzymes that catalyze similar chemical transformations but do not share common ancestry) from the MACiE database. We conclude that functional analogues that catalyze similar overall transformations have commonly converged to use similar catalytic mechanisms, with several pairs sharing identical mechanistic steps. |
| Long Abstract: Click Here |
| Poster C12 |
| Tools for Validation of Predicted Pathways |
| Lynda Ellis- University of Minnesota |
| Junfeng Gao (University of Minnesota, Institute for Health Informatics); Larry Wackett (University of Minnesota, Biochemistry, Molecular Biology, and Biophysics); |
| Short Abstract: The UM-BBD Pathway Prediction System (http://umbbd.msi.umn.edu/predict/) predicts microbial catabolism of organic compounds. Predictions are validated using tools to test rules against all UM-BBD compounds, and aid manual examination of predicted pathways. In January 2009, 82% of 50 user-entered compounds received a reasonable number of plausible predictions. |
| Long Abstract: Click Here |
| Poster D01 |
| Nearest neighbor spacing distributions of basis in different species within the same genus. |
| Fernanda Higareda- Universidad Nacional Autonoma de Mexico |
| No additional authors |
| Short Abstract: We analyze the nearest neighbor spacing distribution between basis in some bacterial genomes. The distributions are similar for species of the same genus. This is not true for species belonging to different genuses. In this study we use some species of Burkholderia, Bacillus and Clostridium. Work supported by PAPIIT project-IN111308. |
| Long Abstract: Click Here |
| Poster D02 |
| cn.FARMS - a probabilistic model to detect DNA copy numbers |
| Djork Clevert- Johannes Kepler University Linz |
| Djork-Arné Clevert (Johannes Kepler University Linz, Institute of Bioinformatics); Marianne Tuefferd (Johnson & Johnson Pharmaceutical Research & Development, Pharmaceutical Research & Development); An De Bondt (Johnson & Johnson Pharmaceutical Research & Development, Pharmaceutical Research & Development); Willem Talloen (Johnson & Johnson Pharmaceutical Research & Development, Pharmaceutical Research & Development); Hinrich W.H. Göhlmann (Johnson & Johnson Pharmaceutical Research & Development, Pharmaceutical Research & Development); Sepp Hochreiter (Johannes Kepler University Linz, Institute of Bioinformatics); |
| Short Abstract: High-density oligonucleotide microarrays, and in particular Affymetrix Mapping or SNP arrays offer the opportunity to get a genome-wide view on copy number alterations and are increasingly used in oncology. We present a probabilistic latent variable model, called cn.FARMS, that takes probe level information to model the the correlation in the observed data. |
| Long Abstract: Click Here |
| Poster D03 |
| Rearrangement phylogeny of genomes in contig form |
| Adriana Munoz- University of Ottawa |
| David Sankoff (University of Ottawa, Mathematics); |
| Short Abstract: Many genomes are being published in contig form. They are thus not directly usable as input to genome rearrangement algorithms. We show how to use the contigs directly in the rearrangement algorithms as if they were chromosomes. The method is applied to Drosophila phylogeny. |
| Long Abstract: Click Here |
| Poster D04 |
| De novo detection and evolution rate of regulatory motifs based on conservation in a dual space. |
| Marleen Claeys- K.U.Leuven |
| Valerie Storms (K.U.Leuven, CMPG-bioi); Kathleen Marchal (K.U.Leuven, CMPG-bioi); |
| Short Abstract: Regulatory motifs are characterized as conserved sites in a non-functional background. In motif detection methods, conservation is typically quantified by overrepresentation, or by an evolutionary relation to a common ancestor. We develop an algorithm that searches motifs in both spaces of conservation simultaneously. The method enables to study evolution of motifs. |
| Long Abstract: Click Here |
| Poster D05 |
| HCOP: A one stop orthology shop |
| Michael Lush- European Bioinformatics Institute, |
| Susan Gordon (European Bioinformatics Institute,, HGNC); Ruth Seal (European Bioinformatics Institute,, HGNC); Matt Wright (European Bioinformatics Institute,, HGNC); Elspeth Bruford (European Bioinformatics Institute,, HGNC); |
| Short Abstract: The HUGO Gene Nomenclature Committee (HGNC) promotes the use of the samename and symbol for orthologous genes in other species. We have developedthe HCOP search tool, which allows rapid survey of orthology assertionsfor a given gene or group of genes . |
| Long Abstract: Click Here |
| Poster D06 |
| Microbial genome sequence analysis in a high-speed process |
| Jessica Schneider- Center for Biotechnology (CeBiTec) |
| Jochen Blom (Center for Biotechnology, Computational Genomics); Eva Trost (Center for Biotechnology, Systems Biology of Regulatory Networks); Andreas Tauch (Center for Biotechnology, Systems Biology of Regulatory Networks); Alexander Goesmann (Center for Biotechnology, Computational Genomics); |
| Short Abstract: New sequencing strategies provide ultrafast access to microbial genome sequences. For their interpretation an efficient bioinformatics pipeline based on comparative genome approaches is required. Starting with the assembly and annotation of a new sequenced genome using GenDB, the software tools CARMEN and EDGAR facilitate further functional and comparative genome analysis. |
| Long Abstract: Click Here |
| Poster D07 |
| Phylogenomic inference of functional divergence |
| Tom Williams- Trinity College Dublin |
| Brian E. Caffrey (Trinity College Dublin, Smurfit Institute of Genetics); Xiaowei Jiang (Trinity College Dublin, Smurfit Institute of Genetics); Christina Toft (Trinity College Dublin, Smurfit Institute of Genetics); Mario A. Fares (Trinity College Dublin, Smurfit Institute of Genetics); |
| Short Abstract: The identification of proteins under functional divergence is of broad interest. We present a fast new method for detecting these changes at the whole-genome level across a complex phylogenetic tree. We demonstrate the usefulness of the method through application to the evolution of pathogenicity in divergent bacterial lineages. |
| Long Abstract: Click Here |
| Poster D08 |
| Comparative Analysis of the Burkholderia pseudomallei Core Genome |
| Tannistha Nandi- Genome Institute of Singapore |
| Catherine Ong Ee Ling (Defense Medical and Environmental Research Institute, Infectious Diseases); Hui Hoon Chua (Genome Institute of Singapore, Infectious Diseases); Jason Kriesberg (Genome Institute of Singapore, Infectious Diseases); Patrick Tan (Genome Institute of Singapore, Infectious Diseases); Paul Keim (Northern Arizona University, Center for Microbial Genetics and Genomics); Talima Ross Pearson (Northern Arizona University, Center for Microbial Genetics and Genomics); William Nierman (J. Craig Venter Institute (JCVI), Infectious Diseases); |
| Short Abstract: Multi-genome comparison of Burkholderia pseudomallei strains. This often causes a fatal disease called meliodosis in humans, endemic in Southeast Asia and Northern Australia. |
| Long Abstract: Click Here |
| Poster D09 |
| Evolution of structure and sequence in alternatively spliced Drosophila genes |
| Ekaterina Ermakova- Institute for Information Transmission Problems (The Kharkevich Institute) |
| Dmitry Malko (State Research Institute of Genetics and Selection of Industrial Microorganisms, Laboratory of Bioinformatics); Mikhail Gelfand (Institute for Information Transmission Problems (The Kharkevich Institute), Research and Training Center on Bioinformatics); |
| Short Abstract: Gain and loss of introns, constitutive and alternatively spliced coding regions, and nucleotide substitutions in constitutively and alternatively spliced coding regions were considered in twelve Drosophila genomes. The rearrangement rates may differ dramatically even in recently diverged species. The substitution rates depend on the type of alternative regions. |
| Long Abstract: Click Here |
| Poster D10 |
| Browsing CRISPR-cassettes in the Sorcerer II metagenome |
| Irena Artamonova- Vavilov Institute Of General Genetics RAS |
| Valery A. Sorokin (Lomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics); Mikhail S. Gelfand (Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences); |
| Short Abstract: To address the problem of CRISPR-cassettes identification in metagenomes we developed a computational technique based on publicly available programs. The scheme was applied to the Sorcerer II data. The results were collected in the MeCRISPR database (http://iitp.bioinf.fbb.msu.ru/vsorokin/crispr). For each family of related CRISPR-cassettes we reconstructed the evolutionary history. |
| Long Abstract: Click Here |
| Poster D11 |
| Detecting Cis Regulatory Modules in Networks: Towards better Candidate Selection |
| Ernesto Iacucci- K. U. Leuven |
| No additional authors |
| Short Abstract: A significant challenge in the field of Cis Regulatory Module (CRM) detection remains the selection of appropriate training genes for CRM detection algorithms. We look to address this problem through the use of orthologously co-expressed genes, protein-protein interaction, and sequence information. |
| Long Abstract: Click Here |
| Poster D12 |
| The ABCG tranporter proteins in Plasmodium: Phylogenomic Analises |
| Ricardo Gonzalez Mendez- University of Puerto Rico School of Medicine |
| Adelfa Serrano (University of Puerto Rico School of Medicine, Microbiology); Hugh Nicholas, Jr. (Pittsburgh Supercomputing Center, National Resource for Biomedical Supercomputing); Alexander Ropelewski (Pittsburgh Supercomputing Center, National Resource for Biomedical Supercomputing); Roxana Cintron Moret (University of Georgia, Department of Cellular Biology); |
| Short Abstract: The ATP-binding cassette, subfamily G (ABCG family), has five members. Sequence analyses and phylogenetic studies were done in Plasmodium species. These analyses show that the ABCG protein found in Plasmodium is a member of the ABCG1 subfamily. These results have important implications for the theories of drug resistance in Plasmodium. |
| Long Abstract: Click Here |
| Poster D13 |
| In-Silico Development of PCR Primers for Detection of Endogenous Para-Retroviruses & Episomal Viral Sequences |
| Angela Eni- Covenant University |
| Ijeoma Dike (Covenant University, Biological Sciences); Conrad Omonhinmin (Covenant University, Biological Sciences); Shalom Chinedu (Covenant University, Biological Sciences); Olubanke Ogulana (Covenant University, Biological Sciences); Segun Fatumo (Covenant University, Computer and Information Sciences); Ezekiel Adebiyi (Covenant University, Computer and Information Sciences); Abiodun Adebayo (Covenant University, Biological Sciences); |
| Short Abstract: Dioscorea spp serve as food for millions of West-Africans yet yam-viruses are a constraint to yam production. In-silico PCR-primer designing employing sequences of the conserved regions for the detection of EPRVs and episomal badnavirus sequences is proposed and will be implemented using ClustalX, Expression software and primer efficiency tested In-Silico. |
| Long Abstract: Click Here |
| Poster D14 |
| Human microRNAs with similarity to box H/ACA small nucleolar RNAs |
| Michelle Scott- University of Dundee |
| Fabio Avolio (Univeristy of Dundee, GRE); Motoharu Ono (Univeristy of Dundee, GRE); Angus I Lamond (Univeristy of Dundee, GRE); Geoffrey J Barton (Univeristy of Dundee, BCDD); |
| Short Abstract: By computational analysis, we identified miRNA precursors with significant similarity to snoRNAs, both on the level of their genomic context and predicted folded structure. Some of these miRNA precursors bind dyskerin, a protein that functionally associates with snoRNAs, strengthening the possibility of an evolutionary relationship between some miRNAs and snoRNAs. |
| Long Abstract: Click Here |
| Poster D15 |
| Genome-wide annotation of human microRNAs under long-range developmental regulation |
| YING SHENG- Bergen Center for Computational Science and Sars International Centre for Marine Molecular Biology |
| No additional authors |
| Short Abstract: MicroRNAs(miRNAs) are small non-coding RNAs that modulate gene expression at post/transcriptional level, often play important roles in fine-tuning of developmental processes. A subset of self-transcribed miRNA loci exhibits typical characteristics of developmental genes controlled by multiple long-range enhancers. We present an approach for genome-wide annotation of this class of miRNAs. |
| Long Abstract: Click Here |
| Poster D16 |
| Development of a simple method for representation of genomics features as file system objects with extended attributes |
| Steven Karcz- Agriculture and Agri-Food Canada |
| Matthew Links (Agriculture and Agri-Food Canada, Biotechnology and Bioprocesses); Isobel Parkin (Agriculture and Agri-Food Canada, Biotechnology and Bioprocesses); |
| Short Abstract: The performance and scalabilty of monolithic relational database systems are beginning to limit comparative genomics feature visualization. We have developed a system of data representation for genomics features based on open source standards using extended attributes on file system objects to overcome query latency in complex comparative genomics datasets. |
| Long Abstract: Click Here |
| Poster D17 |
| Efficient Classification of Orthologues and in-Paralogues based on Super-Partitions |
| Fredj Tekaia- Institut Pasteur |
| Edouard Yeramian (Institut Pasteur, Structural Biology); |
| Short Abstract: We introduce a method involving reasonable shortcuts for the detection of orthologues and their classification based on partitioning and mcl clusterings of Reciprocal Best Hits in closely related species. The partitioning-output (SuperPartitions) of this simple and efficient procedure recovers at least 75% of the potential sets of orthologues. |
| Long Abstract: Click Here |
| Poster D18 |
| Structure-function conservation of steroidogenic systems of plants and animals: phylogeny of the main components |
| George Shpakovski- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences |
| Irina N. Berdichevets (Institute of Genetics and Cytology, National Academy of Sciences of Belarus, Laboratory of Molecular Genetics); Nikolai A. Kartel (Institute of Genetics and Cytology, National Academy of Sciences of Belarus, Laboratory of Molecular Genetics); Elena K. Shematorova (Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Laboratory of Mechanisms of Gene Expression); Dmitry G. Shpakovski (Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Laboratory of Mechanisms of Gene Expression); Svetlana G. Spivak (Institute of Bioorganic Chemistry, National Academy of Sciences of Belarus, 3Laboratory of Lipids Chemistry); |
| Short Abstract: Phylogenetic analysis of all main components of sterol biogenesis in plants and animals was used to uncover the common stages and catalysed reactions. Steroid-5[alpha]-reductase, 3[beta]-hydroxysteroiddehydrogenase/[delta]5-4isomerase, 11[beta] |
| Long Abstract: Click Here |
| Poster D19 |
| Phylogenetic and Functional Assessment of Orthologs Inference Projects and Methods |
| Christophe Dessimoz- ETH Zurich |
| Adrian Altenhoff (ETH Zurich, Computer Science); |
| Short Abstract: This work introduces methodology to verify orthology in terms of phylogeny and function, and performs a comprehensive comparison of nine leading ortholog inference projects using both phylogenetic and functional tests. The results show large variations in terms of performances, indicating that the choice of orthology database can have a strong impact on downstream analysis. |
| Long Abstract: Click Here |
| Poster D20 |
| Viral Bioinformatics Resource Center Tools |
| Chris Upton- University of Victoria |
| No additional authors |
| Short Abstract: The VBRC was established by the NIH to provide virus-centric databases and bioinformatics tools. We support 7 virus families, including pathogens considered to be potential threats as agents of bioterrorism, as well as pathogens classified as causing emerging or re-emerging infectious diseases. |
| Long Abstract: Click Here |
| Poster D21 |
| Pathway Signature Genes |
| Lucas Brouwers- NCMLS |
| Martijn Huynen (NCMLS, Centre for Molecular and Biomolecular Informatics); Bas Dutilh (NCMLS, Centre for Molecular and Biomolecular Informatics); |
| Short Abstract: We define pathway signature genes that reliably predict the presence or absence of pathways in incomplete (metagenomic) sequencing data by overlapping presence/absence profiles of genes with pathways. Cross-validation on partial genomes yields high precision (85,3%) and accuracy (80,6%), while application to metagenomic data confirms known pathways and identifies new processes. |
| Long Abstract: Click Here |
| Poster D22 |
| Benchmarking of Methods for the Identification of Orthologs |
| Sabine Thuss- Heinrich Heine Universitaet Duesseldorf |
| Nina Levar (Heinrich Heine Universitaet Duesseldorf, - ); Christian Esser (Heinrich Heine Universitaet Duesseldorf , Institut fuer Botanik III ); Dr. Tal Dagan (Heinrich Heine Universitaet Duesseldorf , Institut fuer Botanik III ); Prof. Dr. Martin J. Lercher (Heinrich Heine Universitaet Duesseldorf, Lehrstuhl fuer Bioinformatik); |
| Short Abstract: We compare four methods for the identification of orthologous genes. A non-standard application of the Markov Cluster Algorithm (MCL), as well as a method combining sequence similarity and synteny, lead to many more complete clusters and fewer singletons than the other tested methods. |
| Long Abstract: Click Here |
| Poster D23 |
| A High Performance E-Cluster BLAST System |
| Tae-Kyung Kim- Chungbuk National University |
| Chi-Whan Choi (Chungbuk National University, Bioinformatics); Hun-Gi Kim (Chungbuk National University, Bioinformatics); Wan-Sup Cho (Chungbuk National University, MIS/BK21 Team); |
| Short Abstract: We propose a novel BLAST cluster architecture on top of E-Cluster, which consists of dynamic number of PCs. We adopt a logical partitioning and intra-query parallelism on E-Cluster. A proposed BLAST is much superior to conventional grid or cluster BLAST systems in terms of manageability, performances and expenses. |
| Long Abstract: Click Here |
| Poster D24 |
| Visual and Statistical Comparison of Metagenomes with MEGAN 3 |
| Suparna Mitra- Center for Bioinformatics (ZBIT), Tuebingen University |
| Daniel Richter (Center for Bioinformatics (ZBIT), Tuebingen University, Computer Science Department); Alexander Auch (Center for Bioinformatics (ZBIT), Tuebingen University, Computer Science Department); Stephan Schuster (Center for Comparative Genomics, Center for Infectious Disease Dynamics, PennState University); Daniel Huson (Center for Bioinformatics (ZBIT), Tuebingen University, Computer Science Department); |
| Short Abstract: MEGAN (MEtaGenome Analyzer) is a powerful computer program that allows laptop analysis of large metagenomics datasets providing taxonomic and functional analysis. It has an interactive and fully customizable chart viewer and also allows visual and statistical comparative analysis of different metagenomes. |
| Long Abstract: Click Here |
| Poster D25 |
| Convergent evolution of domain architectures is rare after all |
| Martin Madera- University of Bristol |
| Julian Gough (University of Bristol, Computer Science); |
| Short Abstract: The domain architecture of a protein is the sequential order of its domains. (Gough, 2005) concluded that only 0.2-2% of domain architectures have evolved more than once. Using an automated method, (Forslund et al., 2008) found 12.4%. We examine the Forslund predictions and present several large classes of false positives. |
| Long Abstract: Click Here |
| Poster D26 |
| Fine-Structured Segmental Variation in Eukaryote Genomes |
| Jonathan Keith- Queensland University Of Technology |
| Christopher Oldmeadow (Queensland University of Technology, School of Mathematical Sciences); |
| Short Abstract: As an initial step towards delineating new functional elements in eukaryote genomes, we present a segmentation of human and fruit fly genomes, and classify the segments according to properties suggestive of function. We further investigate the motif content and GO term enrichment of these classes. |
| Long Abstract: Click Here |
| Poster E01 |
| Integrative storage and retrieval of computational biochemical models |
| Ron Henkel- Universität Rostock |
| Dagmar Köhn (Universität Rostock, Database- and Information systems); Carsten Maus (Universität Rostock, Modeling and Simulation); |
| Short Abstract: Increasing numbers and complexity of biochemical models make model reusemore imperative. This work introduces an integrative storage approach for models from different formalisms and their meta-information given as annotations.It provides retrieval techniques, enables model comparison regarding model similarity, and suggests the generation of simulation experiments. |
| Long Abstract: Click Here |
| Poster E02 |
| TparvaDB: a database to support Theileria parva vaccine development |
| Etienne de Villiers- International Livestock Research Institute |
| Paul Visendi (University of Nairobi, Center for Biotechnology and Bioinformatics ); Wallace Bulimo (US Army Medical Research Unit , Nairobi); Wanjiku Ng’ang’a (University of Nairobi, School of Computing and Informatics); Richard Bishop (International Livestock Research Institute, Biotechnology); |
| Short Abstract: We have developed TparvaDB, an integrated database for Theileria parva based on GMOD. TparvaDB houses full genome sequences, Expressed Sequence Tags (ESTs), Massivelly Parallel Signature Sequencing (MPSS) data, vaccine candidate gene and other related data. |
| Long Abstract: Click Here |
| Poster E03 |
| GabiPD: The Gabi Primary Database - a plant integrative ‘omics’ database |
| Diego Mauricio Riaño-Pachón- Max Planck Institute for Molecular Plant Physiology |
| Axel Nagel (Max Planck Institute for Molecular Plant Physiology, Bioinformatics); Robert Wagner (Max Planck Institute for Molecular Plant Physiology, Bioinformatics); Rico Basekow (Max Planck Institute for Molecular Plant Physiology, Bioinformatics); Jost Neigenfind (Max Planck Institute for Molecular Plant Physiology, Bioinformatics); Elke Weber (Max Planck Institute for Molecular Plant Physiology, Bioinformatics); Sabrina Kleessen (Max Planck Institute for Molecular Plant Physiology, Bioinformatics); Birgit Kersten (Max Planck Institute for Molecular Plant Physiology, Bioinformatics); |
| Short Abstract: The GabiPD – Gabi Primary Database, constitutes a repository for ‘omics’ data in the plant field. Integrated data is available to the scientific community via http://www.gabipd.org/. The main goal of GabiPD is to collect, integrate, visualize and link primary information from `omics` data of various plant species. |
| Long Abstract: Click Here |
| Poster E04 |
| The Universal Protein Resource (UniProt) |
| Manuela Pruess- European Bioinformatics Institute |
| The UniProt Consortium (Swiss Institute of Bioinformatics, Centre Medical Universitaire); The UniProt Consortium (Protein Information Resource, Georgetown University Medical Center); |
| Short Abstract: UniProt (http://www.uniprot.org) is a high-quality, freely accessible resource of protein sequence and functional information, highly cross-referenced to other databases. UniProt is comprised of an Archive, a Knowledgebase, Reference Clusters, and a Metagenomic and Environmental Sequence Database. Recently the first draft of the complete human proteome in UniProtKB/Swiss-Prot has been completed. |
| Long Abstract: Click Here |
| Poster E05 |
| CHDWiki : An online collaborative and interactive data repository dedicated to congenital heart defects. |
| Sylvain Brohée- Katholieke Universiteit Leuven |
| Roland Barriot (Katholieke Universiteit Leuven, ESAT - SCD); Jeroen Breckpot (Katholieke Universiteit Leuven, Center for Human Genetics); Bernard Thienpont (Katholieke Universiteit Leuven, Center for Human Genetics); Steven Van Vooren (Katholieke Universiteit Leuven, ESAT - SCD); Bert Coessens (Katholieke Universiteit Leuven, ESAT - SCD); Léon-Charles Tranchevent (Katholieke Universiteit Leuven, ESAT - SCD); Peter Van Loo (Katholieke Universiteit Leuven, ESAT - SCD); Marc Gewellig (Katholieke Universiteit Leuven, Department of Pediatric Cardiology); Koen Devriendt (Katholieke Universiteit Leuven, Center for Human Genetics); Yves Moreau (Katholieke Universiteit Leuven, ESAT - SCD); |
| Short Abstract: We present a user-friendly resource and gene prioritization portal aimed at mapping genes involved in congenital heart defects and untangling their relations with corresponding human phenotypes. It combines both the facilities of Wiki databases and the strictness of specialized databases. This model could be applied to any other specialized fields. |
| Long Abstract: Click Here |
| Poster E06 |
| PRIDE, the PRoteomics IDEntifications database |
| Florian Reisinger- EMBL-EBI |
| Lennart Martens (EMBL-EBI, Proteomics Services ); Richard Côté (EMBL-EBI, Proteomics Services ); Juan A. Vizcaino (EMBL-EBI, Proteomics Services ); Henning Hermjakob (EMBL-EBI, Proteomics Services ); |
| Short Abstract: PRIDE, the PRoteomics IDEntifications database, is a public data repository for proteomics data consisting of proteins, peptides and spectral evidence. It provides the scientific community with a common data exchange format that implements HUPO PSI standards along with a stable repository to support proteomics literature publications and the peer-review process. |
| Long Abstract: Click Here |
| Poster E07 |
| Arabidopsis Reactome: A Pathway Database for Plant Systems Biology |
| Janet Higgins- John Innes Centre |
| Matthew Couchman (John Innes Centre, Computational and Systems Biology); Sean Walsh (John Innes Centre, Computational and Systems Biology); Michael Bevan (John Innes Centre, Cell and Developmental Biology); |
| Short Abstract: Arabidopsis Reactome is an online knowledgebase of plant metabolic, genetic and signalling pathways available at www.arabidopsisreactome.org. Pathways can be exported in BioPAX and SBML and visualised using Cytoscape. The SkyPainter tool allows visualisation of high-throughput data. Arabidopsis Reactome pathways are electronically projected onto plants and available as protein-protein interaction datasets. |
| Long Abstract: Click Here |
| Poster E08 |
| BioRPC: A Server-side Bioinformatics Platform Proposal |
| Paulo Paiva- Federal University of São Paulo |
| Jackson Lima (Federal University of São Paulo, Health Informatics Department); Cleber Magnagnagno (Federal University of São Paulo, Health Informatics Department); |
| Short Abstract: A server-side bioinformatics platform is proposed in order to allow applications based on the new paradigms of Web technology to make use of well established biological databases and tools.This is accomplished by using the Remote Procedure Call protocol and is intended to work under a Service Oriented Architecture. |
| Long Abstract: Click Here |
| Poster E09 |
| The Protein Structure Initiative Structural Genomics Knowledgebase |
| Andrei Kouranov- Protein Data Bank |
| Margaret Gabanyi (Rutgers, The State University of New Jersey, Chemistry and Chemical Biology); John Westbrook (Rutgers, The State University of New Jersey, Chemistry and Chemical Biology); Wendy Tao (Rutgers, The State University of New Jersey, Chemistry and Chemical Biology); RAship Shah (Rutgers, The State University of New Jersey, Chemistry and Chemical Biology); Torsten Schwede (University of Basel, Swiss Institute of Bioinfomatics & Biozentrum); Konstantin Arnold (University of Basel, Swiss Institute of Bioinfomatics & Biozentrum); Florian Kiefer (University of Basel, Swiss Institute of Bioinfomatics & Biozentrum); Lorenza Bordoli (University of Basel, Swiss Institute of Bioinfomatics & Biozentrum); Michael Podvinec (University of Basel, Swiss Institute of Bioinfomatics & Biozentrum); Jurgen Kopp (Heidelberg University, Biochemie-Zentrum); Paul D. Adams (Lawrence Berkeley National Laboratory, Physical Biosciences Division); Lester G. Carter (Lawrence Berkeley National Laboratory, Physical Biosciences Division); Wladek Minor (University of Virginia, Department of Molecular Physiology and Biological Physics); Rajesh Nair (Columbia University, Department of Biochemistry & Molecular Biophysics); Joshua La Baer (University Medical School, Harvard Institute of Proteomics & Department of Biological Chemistry and Molecular Pharmacology); Helen M. Berman (Rutgers, The State University of New Jersey, Department Chemistry and Chemical Biology); |
| Short Abstract: The PSI Structural Genomics Knowledgebase (PSI SGKB: http://kb.psi-structuralgenomics.org/) is designed to turn the products of the Protein Structure Initiative into knowledge that is important for understanding living systems and disease. A description of how this resource can be used for enabling biological research will be presented. |
| Long Abstract: Click Here |
| Poster E10 |
| Establishment and public release of integrated Clinical Omics Database (iCOD) with clinical and molecular biological information for systems pathological research. |
| Hiroshi Mizushima- Tokyo Medical And Dental University |
| Yasen Mahmut (Tokyo Medical and Dental University, Information Center for Medical Sciences); Ken Miyaguchi (Tokyo Medical and Dental University, Information Center for Medical Sciences); Kaoru Mogushi (Tokyo Medical and Dental University, Information Center for Medical Sciences); Kazuro Shimokawa (Tokyo Medical and Dental University, Information Center for Medical Sciences); Hiroshi Tanaka (Tokyo Medical and Dental University, Information Center for Medical Sciences); |
| Short Abstract: Development of “TMDU Clinical Omics Database” has been conducted by integrating OMICS information and clinical information. We currently collected 500+ cases including hepatic, colon, and oral cancer. Database now can be accessed at http://omics.tmd.ac.jp/. This would be the first integrated clinical database with both clinical and molecular biological information. |
| Long Abstract: Click Here |
| Poster E11 |
| The Roche Mutome Database |
| Jan Küntzer- Roche Diagnostics GmbH |
| Stefan Klostermann (Roche Diagnostics GmbH, Pharma Research Penzberg / TR-IB); Helmut Burtscher (Roche Diagnostics GmbH, Pharma Research Penzberg / TR-D3); |
| Short Abstract: We developed an integrative biological information system for the human mutome combining different publicly available databases and Roche in-house applications. The database contains all kind of mutations at the DNA and protein sequence level like substitutions, deletions, insertions, amplification, and chromosomal rearrangements. |
| Long Abstract: Click Here |
| Poster E12 |
| PDB decomposition tool |
| Rafael Ordog- Eotvos Lorand University, PIT Group |
| Zoltán Szabadka (Eotvos Lorand University, PIT Group, Department Of Computer Science); Vince Grolmusz (Eotvos Lorand University, PIT Group, Department Of Computer Science); |
| Short Abstract: We present a fast tool - freely available through a web-interface - for identifying and marking missing atoms and residues in the PDB, as well as automatically decomposing the PDB entries into separate files describing ligands and polypeptide chains. |
| Long Abstract: Click Here |
| Poster E13 |
| jORCA: Making the use of bioinformatics web services easier. |
| Victoria Martin-Requena- University of Málaga |
| Javier Rios (University of Málaga, Computer Architecture); Maximiliano García (University of Málaga, Computer Architecture); Sergio Ramirez (University of Málaga, Computer Architecture); Oswaldo Trelles (University of Málaga, Computer Architecture); |
| Short Abstract: jORCA is a client able to integrate different types of web-services repositories mapping their metadata descriptors over a general virtual definition to support scalable service discovery and to achieve flexible tools intercommunication. jORCA allows executing different invocation protocols and includes interactive features to cover a broad range of users. |
| Long Abstract: Click Here |
| Poster E14 |
| New Features in the UniProt Archive (UniParc) |
| Quan Lin- European Bioinformatics Institute (EBI) |
| Rasko Leinonen (EMBL Outstation, , European Bioinformatics Institute (EBI), ); Richard Côté (EMBL Outstation, , European Bioinformatics Institute (EBI), ); Maria Martin (EMBL Outstation, , European Bioinformatics Institute (EBI), ); Claire O'Donovan (EMBL Outstation, , European Bioinformatics Institute (EBI), ); Rolf Apweiler (EMBL Outstation, , European Bioinformatics Institute (EBI), ); |
| Short Abstract: UniParc is the most comprehensive protein sequence database available. We have extended its functionality by adding TaxId and NCBI gi numbers, by giving the reasons as why some proteins are excluded from UniProtKB and by adding UniProtKB accessions to some sequences that are not identical to a UniProKB sequence. |
| Long Abstract: Click Here |
| Poster E15 |
| Migration of the Pfam database to HMMER3 |
| Robert Finn- Wellcome Trust Sanger Institute |
| Penny Coggill (Wellcome Trust Sanger Institute, Bioinformatics); Jaina Mistry (Wellcome Trust Sanger Institute, Bioinformatics); John Tate (Wellcome Trust Sanger Institute, Bioinformatics); Sean Eddy (Janelia Farm Research Campus, Eddy Group); Alex Bateman (Wellcome Trust Sanger Institute, Bioinformatics); |
| Short Abstract: Pfam, the protein families database, is underpinned by the HMMER software package. In January 2009, a faster, more sensitive version of HMMER was released: HMMER3. The migration of Pfam to HMMER3 has resulted in many important changes to the database, which increases both its scope and its potential use. |
| Long Abstract: Click Here |
| Poster E16 |
| UniProtJAPI: a remote API for accessing UniProt data |
| Samuel Patient- EBI - European Bioinformatics Institute |
| Michael Kleen (EBI, PANDA); Maria Jesus Martin (EBI, PANDA); Rolf Apweiler (EBI, PANDA); |
| Short Abstract: The UniProtJAPI facilitates the integration of UniProt Knowledgebase data into Java-based software applications. The library supports queries and similarity searches that return UniProt entries in the form of Java objects. These objects contain functional annotations or sequence information associated with the entry. UniProtJAPI is available at http://www.ebi.ac.uk/uniprot/remotingAPI/ |
| Long Abstract: Click Here |
| Poster E17 |
| The enzyme information system BRENDA |
| Maurice Scheer- Technische Universität Braunschweig |
| Andreas Grote (Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry); Michael Rother (Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry); Juliane Thiele (Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry); Antje Chang (Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry); Ida Schomburg (Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry); Dietmar Schomburg (Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry); |
| Short Abstract: BRENDA is an enzyme information system. Biochemical and molecular information on all classified enzymes extracted from primary literature is made freely accessible by sophisticated software tools (http://www.brenda-enzymes.org). Recent innovations comprise the inclusion of protein-specific data, the display of active sites in 3D-structure of enzymes and improvements of the textmining. |
| Long Abstract: Click Here |
| Poster E18 |
| SuperToxic: a comprehensive database of toxic compounds |
| Robert Preissner- Charite |
| Ulrike Schmidt (Charite , Institute for Physiology); Swantje Struck (Charite, Institute for Physiology); Bjoern Gruening (Charite, Institute for Physiology); Julia Hossbach (Charite, Institute for Physiology); Ines S. Jaeger (Charite, Institute for Physiology); Elke Michalsky (Charite, Institute for Physiology); Roza Parol (Charite, Institute for Physiology); Ulrike Linequist (Ernst-Moritz-Arndt-University Greifswald, Institute of Pharmacy); Eberhard Teuscher (Ernst-Moritz-Arndt-University Greifswald, Institute of Pharmacy); |
| Short Abstract: The database SuperToxic is a comprehensive collection of 150,000 compounds, classified according to their toxicity based on more than 2 million measurements. \"Toxicity properties\" extracted from SuperToxic, function as a guideline for the toxicological evaluation of unknown substances and their possible biological interactions. |
| Long Abstract: Click Here |
| Poster E19 |
| BioExpert: Biological Knowledge Base Creation through Concept Mapping |
| Andrew Gibson- University of Amsterdam |
| Gerbert Jansen (University of Amsterdam, Academic Medical Center); Antoine van Kampen (University of Amsterdam, Academic Medical Center); Serge Barth (University of Amsterdam, Swammerdam Institute for Life Sciences); Aviral Vatsa (University of Amsterdam, Academic Medical Center); |
| Short Abstract: The BioExpert Project is working towards an environment in which experts can create knowledge bases that focus on specific topics in biology. Our strategy is to capture and represent knowledge using graphical concept maps. We present the pilot ‘Peroxisome Knowledge Base’, which was created using this methodology. |
| Long Abstract: Click Here |
| Poster E20 |
| BioMart and Web Services in InterPro |
| John Maslen- EMBL - European Bioinformatics Institute |
| Philip Jones (EMBL - European Bioinformatics Institute, InterPro Team); Sarah Hunter (EMBL - European Bioinformatics Institute, InterPro Team); |
| Short Abstract: InterPro has introduced a BioMart interface, giving users the ability to generate complex queries over the InterPro data, with highly-customisable control over the results. It also allows the generation of distributed queries with federated databases and web service access to the data via REST and a DAS server. |
| Long Abstract: Click Here |
| Poster E21 |
| EMBRACE web services and Chipster: easy access to up-to-date tools |
| Aleksi Kallio- CSC - The Finnish IT Center for Science |
| Taavi Hupponen (CSC - The Finnish IT Center for Science , -); Petri Klemelä (CSC - The Finnish IT Center for Science , -); Jarno Tuimala (CSC - The Finnish IT Center for Science , -); Eija Korpelainen (CSC - The Finnish IT Center for Science , -); |
| Short Abstract: Substantial amount of novel methods and databases have been produced in the EU-funded EMBRACE network (see EMBRACE Registry for complete list). We integrate the services with our user-friendly analysis software Chipster to make them accessible also to biologists. We also provide new public web services based on Chipster. |
| Long Abstract: Click Here |
| Poster E23 |
| RISSC2: an online interface to study ribosomal intergenic transcribed spacers in prokaryotes |
| Ravindra Pushker- University College Dublin |
| Giuseppe D\\\'Auria (Cavanilles Institute for Biodiversity and Evolutionary Biology, University of Valencia); Francisco Rodriguez-Valera (University of Miguel Hernandez, Department of Microbiology); |
| Short Abstract: RISSC2 is a novel database which contains a) 16S-23S ribosomal ITS present in prokaryotesfrom different environments providing an update to the old RISSC database; b) much shorterribosomal spacers which can be found between 23S and 5S rRNAs. It is available online at http://egg.umh.es/rissc2/. |
| Long Abstract: Click Here |
| Poster E24 |
| Kegg Orthology enrichment with a procedure based on UniRef clusters recruits novel elements to Atlas and Pathways |
| Gabriel Fernandes- Universidade Federal de Minas Gerais |
| J Miguel Ortega (Universidade Federal de Minas Gerais, Biochemistry and Immunology); |
| Short Abstract: Here we report a procedure to enrich information of Kegg Orthology database, initially comprised of 1,248,629 proteins from 846 distinct organisms. Using the information contained in iProClass (PIR) we raised the data to 2,241,188 proteins (1,9 fold enrichment) corresponding to 24,081 distinct genomes. |
| Long Abstract: Click Here |
| Poster E25 |
| Symbiosis: a Web-based framework for managing and analysing high throughput metabolomic data |
| Fady Mohareb- Bioinformatics Group |
| Conrad Bessant (Bioinformatics Group, Cranfield Health); George Nychas (Microbiology & Biotechnology Lab of Food, Agricultural University of Athens); |
| Short Abstract: The Symbiosis-EU framework is a Web-based research platform that allows users to store, manipulate, and analyse experimental high-throughput –omic data. The framework also provides means for performing statistical analysis through a choice of data analysis pipelines mainly for metabolomic data, but the system is continuously updated to support other platforms. |
| Long Abstract: Click Here |
| Poster E26 |
| XMLPipeDB: A Reusable, Open Source Tool Chain for Building Relational Databases from XML Sources |
| Kam Dahlquist- Loyola Marymount University |
| Alexandrea Alphonso (Loyola Marymount University, Biology); Derek Smith (Loyola Marymount University, Electrical Engineering & Computer Science); Chad Villaflores (Loyola Marymount University, Biology); John Dionisio (Loyola Marymount University, Electrical Engineering &Computer Science); |
| Short Abstract: XMLPipeDB is an open source suite of Java-based tools for automatically building relational databases from an XML schema (XSD). We have used it to generate GenMAPP Gene Databases containing UniProt and Gene Ontology data for several microorganisms and plants. Other common bioinformatics XML formats were tested for compatibility with XMLPipeDB. |
| Long Abstract: Click Here |
| Poster E28 |
| An Overview of the BioExtract Server – a Distributed, Web Based Application for Bioinformatic Analysis |
| Carol Lushbough- University of South Dakota |
| Volker Brendel (Iowa State University, the Department of Genetics, Development and Cell Biology and Department of Statistics); |
| Short Abstract: The BioExtract Server (http://bioextract.org) is a Web-based data integration application designed to aid researchers in the development of computational workflows. It allows users, via a Web browser, to query multiple data sources, save query results as searchable data sets, execute local and Web-accessible analytic tools, and create computational workflows. |
| Long Abstract: Click Here |
| Poster E29 |
| iRefIndex |
| Sabry Razick- University Of Oslo |
| Ian Donaldson (Group leader, Biotechnology Centre ofOslo); George Magklaras (Senior Computer Systems Engineer, The Biotechnology Centre of Oslo); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster E30 |
| ELIXIR Bioinformatics User Survey |
| Sandrine Palcy- Université Bordeaux 2 |
| Antoine de Daruvar (Université Bordeaux 2 , Centre de Bioinformatique de Bordeaux); |
| Short Abstract: The Bioinformatics User survey has been carried out for the European Life sciences Infrastructure for Biological Information (ELIXIR) project. Participation of 804 individual research groups and subsequent analysis of the collected information provided insights for a better understanding of the user community needs and priorities in respect to bioinformatics infrastructures. |
| Long Abstract: Click Here |
| Poster E31 |
| Hyperlink Management System for creating maintenance-free hyperlinks to major biological databases. |
| Tadashi Imanishi- AIST |
| Hajime Nakaoka (JBIC, Research and Development); |
| Short Abstract: We developed the Hyperlink Management System for automatically updating and maintaining hyperlinks among major public databases for human genes and proteins, enabling maintenance-free hyperlinks. We also developed the ID Converter System for converting data IDs of major biological databases. These systems are freely available at http://biodb.jp/. |
| Long Abstract: Click Here |
| Poster E32 |
| A database supporting Quantitaive aspects of Plant Breeding |
| Richard Finkers- WUR |
| Roeland Voorrips (WUR, Plant breeding); |
| Short Abstract: Support of databases for Quantitative breeding research are getting more important. We developed an database focusing at storage of marker and trait data. A set of tools were implemented in a web-based front-end which aims at integrative analysis and visualization of the stored information. |
| Long Abstract: Click Here |
| Poster E33 |
| SoyXpress: A soybean transcriptome database |
| Martina Stromvik- McGill University |
| Kei Chin Cheng (McGill University, Plant Science); |
| Short Abstract: In order to explore the soybean transcriptome we developed SoyXpress, a MySQL database (http://soyxpress.agrenv.mcgill.ca/). Affymetrix microarray data are linked with ESTs, metabolic pathways, GO terms and SwissProt keywords. Currently SoyXpress houses microarray data comparing transgenic and conventional soybean cultivars, as well as a section on common soybean virus sequence data. |
| Long Abstract: Click Here |
| Poster E34 |
| The Ibidas data integration and accession platform |
| Jan Bot- TU Delft |
| Marc Hulsman (TU Delft, Bioinformatics); Marcel Reinders (TU Delft, Bioinformatics); |
| Short Abstract: Ibidas provides a python-based software environment for querying biologicaldata, with support for multiple input types such as databases, text files or web services. It can be used from within widely used analysis tools such as R and Matlab, and is easily extendible. |
| Long Abstract: Click Here |
| Poster E35 |
| CliquePOINT: A tool for analysis the complex information from a protein-protein interaction network |
| Sheng-An Lee- National Taiwan University |
| Yun-Yan Yang (National Taiwan University, Department of Computer Science and Information Engineering); Yu-Lun Kuo (National Taiwan University, Department of Computer Science and Information Engineering); Cheng-Yan Kao (National Taiwan University, Department of Computer Science and Information Engineering); Chi-Ying Huang (National Yang-Ming University, Institute of Clinical Medicine); |
| Short Abstract: CliquePoint was developed to evaluate the complex information, three parts of dataset in CliquePoint (i.e., protein-protein interaction, complex, and tissue expression dataset) are utilized. The concept of clique and interologs as a comparative strategy to assign reliable experimental datasets and to explicitly reveal potential PPIs and complexes in a species. |
| Long Abstract: Click Here |
| Poster E36 |
| A Virtual Library for BITS Meetings |
| Paolo Romano- National Cancer Research Institute |
| Achille Zappa (National Cancer Research Institute, Bioinformatics); Mariangela Miele (National Cancer Research Institute, Bioinformatics); Stefania Parodi (National Cancer Research Institute, Bioinformatics); |
| Short Abstract: Grey literature may include data of extreme interest. The Virtual Library for BITS Meetings includes 669 scientific contributions from 10 meetings of the Bioinformatics Italian Society. It is available at http://bioinformatics.istge.it/bits_library/. Contributions can be searched by author, title and contents, listed by meeting and topic, and downloaded in PDF. |
| Long Abstract: Click Here |
| Poster E37 |
| Community intelligence applied to gene annotation: The Gene Wiki and BioGPS |
| Andrew Su- GNF |
| Jon Huss, III (GNF, Computational Discovery); Chunlei Wu (GNF, Computational Discovery); Camilo Orozco (GNF, Computational Discovery); Jason Boyer (GNF, Computational Discovery); James Goodale (GNF, Computational Discovery); Serge Batalov (GNF, Computational Discovery); Tim Vickers (Washington University, School of Medicine); Faramarz Valafar (San Diego State University, Computer Science); |
| Short Abstract: Recently, we introduced two community intelligence initiatives aimed at accelerating gene annotation and gene portal development, called the Gene Wiki and BioGPS, respectively. We present details on the design on these two resources, as well as usage statistics showing substantial usage and contributions by the scientific community. |
| Long Abstract: Click Here |
| Poster E39 |
| InterMine – open source data warehouse and query interface |
| Richard Smith- Cambridge University |
| Adrian Carr (University of Cambridge, Cambridge Systems Biology Centre); Sergio Contrino (University of Cambridge, Cambridge Systems Biology Centre); Rachel Lyne (University of Cambridge, Cambridge Systems Biology Centre); Julie Sullivan (University of Cambridge, Cambridge Systems Biology Centre); Dan Tomlinson (University of Cambridge, Cambridge Systems Biology Centre); Xavier Watkins (University of Cambridge, Cambridge Systems Biology Centre); Matthew Wakeling (University of Cambridge, Cambridge Systems Biology Centre); Gos Micklem (University of Cambridge, Cambridge Systems Biology Centre); |
| Short Abstract: InterMine is an open-source system for building query-optimised data warehouses. It supports data integration from standard biological formats and makes it easy to add your own data. A sophisticated web application provides flexible access for users to create custom queries, use templates and operate on lists. |
| Long Abstract: Click Here |
| Poster E40 |
| Custom Databases and Queries for PFAM, GO, and GOA: Exploratory analysis of protein and function relations |
| Mark Fenner- Norwich University |
| No additional authors |
| Short Abstract: For exploratory problems that build and manipulate sets of elements from large biological databases, local access is a practical necessity. We present a small suite of tools which balance speed and convenience for exploring PFAM, GO, and GOA within Python. Exploratory results can be directly processed by further Python-based workflows. |
| Long Abstract: Click Here |
| Poster E41 |
| The ELIXIR Database Provider Survey |
| Andrew Lyall- EMBL- European Bioinformatics Institute |
| Christopher Southan (EMBL- European Bioinformatics Institute, Elixir Database Survey Coordinator); Graham Cameron (EMBL- European Bioinformatics Institute, Associate Director); |
| Short Abstract: A major survey of biomolecular resources has been carried out for the European Life sciences Infrastructure for Biological Information (ELIXIR) project. From 531 European databases contacted 208 have completed the questionnaire. Information about location, data, funding, usage and other statistics of database operation will be outlined in this poster |
| Long Abstract: Click Here |
| Poster E42 |
| Annotating drugs and metabolites with their chemical class |
| Roman Eisner- University of Alberta |
| Russ Greiner (University of Alberta, Computing Science); Craig Knox (University of Alberta, Computing Science); Joseph Cruz (University of Alberta, Computing Science); David Wishart (University of Alberta, Computing Science); |
| Short Abstract: We annotate the compounds in the HMDB and Drugbank with their chemical class. Using machine-learning, structural similarity methods, and manual curation, we assign chemical class to these compounds. The chemical class makes for more searchable databases, and can aid in further annotation of compounds. |
| Long Abstract: Click Here |
| Poster E43 |
| The ArrayExpress Atlas – a semantically enriched multispecies atlas of gene expression |
| Tony Burdett- European Bioinformatics Institute |
| Helen Parkinson (European Bioinformatics Institute, Microarray); Ele Holloway (European Bioinformatics Institute, Microarray); Tomasz Adamusiak (European Bioinformatics Institute, Microarray); Ibrahim Emam (European Bioinformatics Institute, Microarray); Pavel Kurnosov (European Bioinformatics Institute, Microarray); James Malone (European Bioinformatics Institute, Microarray); Gabriella Rustici (European Bioinformatics Institute, Microarray); Alvis Brazma (European Bioinformatics Institute, Microarray); Misha Kapushesky (European Bioinformatics Institute, Microarray); |
| Short Abstract: The ArrayExpress Atlas is a semantically enriched database of meta-analytical summary statistics over the ArrayExpress Warehouse. Users can query for condition-specific gene expression across multiple gene expression datasets. |
| Long Abstract: Click Here |
| Poster E44 |
| UniProt Automatic Annotation |
| Michael Kleen- EMBL-EBI The European Bioinformatics Institute |
| Ricardo Antunes (EBI - Panda, EMBL-EBI The European Bioinformatics Institute); Maria-Jesus Martin (EBI - Panda, EMBL-EBI The European Bioinformatics Institute); Rolf Apweiler (EBI - Panda, EMBL-EBI The European Bioinformatics Institute); |
| Short Abstract: The UniProt Automatic Annotation Project automatically annotates protein entries in the unreviewed TrEMBL section of the UniProtKnowledgebase(UniProtKB). The system is used to create rules based on the annotation in the reviewed Swiss-Prot section of UniProtKB. Theserules are then applied in each release to enrich the TrEMBL section with general annotations. |
| Long Abstract: Click Here |
| Poster F01 |
| Phylogenetic reconstruction by Automatic Likelihood Model Selector (PALM) : A Framework for Phylogenetic Analysis with the Best Substitution Model |
| Chung-Yen Lin- Academia Sinica |
| No additional authors |
| Short Abstract: To make the whole phylogenetic analysis smoothly and avoid tedious manipulations of various programs, we build an intuitive framework named as Phylogentic Reconstruction by Automatic Likelihood Model selector (PALM) with the most convinced, updated algorithms and models in a seamless way. |
| Long Abstract: Click Here |
| Poster F02 |
| Inference of huge polygenetic trees |
| Martin Simonsen- University of Aarhus |
| Thomas Mailund (Aarhus university, BIRC); Christian Pedersen (Aauhus university, BIRC); |
| Short Abstract: RapidDiskNJ is a heuristic for the canonical phylogenetic inference method, Neighbour-Joining, which utilise external memory to reduce the need for internal memory while also reducing the running time of the canonical Neighbour-Joining method. RapidDiskNJ makes it feasible to efficiently infer huge phylogenies with more than 40000 taxa. |
| Long Abstract: Click Here |
| Poster F03 |
| Gene duplication is a key driver of adaptation within a species |
| Ryan Ames- University of Manchester |
| Bharatkumar Rash (University of Manchester, Faculty of Life Sciences); David Robertson (University of Manchester, Faculty of Life Sciences); Daniela Delneri (University of Manchester, Faculty of Life Sciences); Simon Lovell (University of Manchester, Faculty of Life Sciences); |
| Short Abstract: Using genomic sequences from multiple strains of S. cerevisiae and S. paradoxus we identified and compared duplicates within populations of the same species. We show an abundance of duplication in both species and demonstrate that the duplicates have experienced selection. Differential duplicate retention also leads to predictable differences in phenotype. |
| Long Abstract: Click Here |
| Poster F04 |
| Three-Dimensional Structural Determinants of Amino Acid Conservation in Proteins |
| Sungsam Gong- Cambridge University |
| Tom Blundell (University of Cambridge, Department of Biochemistry); |
| Short Abstract: In this poster, we try to answer the question “what determines amino acid substitutions in the three-dimensional structures of proteins”. We show that solvent accessibility is the most important determinant, followed by the existence of hydrogen-bonds from the side-chain to main-chain functions and the nature of the element of secondary structure |
| Long Abstract: Click Here |
| Poster F05 |
| Adaptability contra biodiversity – comparative modeling of closed trophic webs using “Evolutionary Constructor” program |
| Sergey Lashin- THE INSTITUTE OF CYTOLOGY AND GENETICS |
| Valentin Suslov (THE INSTITUTE OF CYTOLOGY AND GENETICS, Laboratory of Theoretical Genetics); |
| Short Abstract: Coevolution of the two trophic rings of haploid organism populations which exchanged of metabolites and consumed of the common substrat was in silico modeled. The trophic ring with Rubel’s factors replaceability was more competitive according to total growth of biomass and adaptability, ring with Liebig’s trophism - in biodiversity and potentially evolvability. |
| Long Abstract: Click Here |
| Poster F06 |
| The computational analysis of GTF2I gene family evolution |
| Irina Medvedeva- Institute of Cytology and Genetics SB RAS |
| Vladimir Ivanisenko (Institute of Cytology and Genetics SB RAS, Laboratory of theoretical genetics); Konstantin Gunbin (Institute of Cytology and Genetics SB RAS, Laboratory of theoretical genetics); Anatoly Ruvinsky (University of New England, Institute for Genetics and Bioinformatics); |
| Short Abstract: The GTF2I gene family consist of the genes of transcriptional factors that contain the different number of GTF2I repeats. We analyzed the exon-intron structure of genes, their phylogenetic relationships and tertiary structure. These techniques could be used for the developing software tools for genome-level analysis of the exon-intron structures evolution. |
| Long Abstract: Click Here |
| Poster F07 |
| The Evolution of Beta Amyloid Cleaving Enzyme (BACE1): an Alzheimer’s disease Drug Target |
| Christopher Southan- ChrisDS Consulting |
| John Hancock (MRC Harwell, Bioinformatics); |
| Short Abstract: We have used new genome data to examine the evolution of this important drug target. A tree of 30 BACE-like sequences showed a single membrane-anchored Eumetazoan ancestor. After duplication in fish the paralogue BACE2 evolved more rapidly suggesting BACE1 has maintained its ancestral neuronal function. |
| Long Abstract: Click Here |
| Poster F08 |
| A Single beta-beta Hairpin is the Ancestor of Bacterial Outer Membrane beta-barrels |
| Michael Remmert- Gene Center, LMU |
| Andreas Biegert (Gene Center, LMU, Computational Biology); Dirk Linke (Max-Planck-Institute for Developmental Biology, Protein Evolution); Andrei N. Lupas (Max-Planck-Institute for Developmental Biology, Protein Evolution); Johannes Soeding (Gene Center, LMU, Computational Biology); |
| Short Abstract: We show that bacterial outer membrane beta-barrels (OMBBs) arose by duplication of an ancestral beta-beta hairpin: We link all known families of single-chain OMBBs by transitive profile searches, detect a clear repeat pattern in most OMBB families, and demonstrate that the observed sequence similarity cannot be explained by structural convergence. |
| Long Abstract: Click Here |
| Poster F09 |
| Animal proteins acquire new domains through gene duplications and joining of adjacent genes’ exons |
| Marija Buljan- Wellcome Trust Sanger Institute |
| Adam Frankish (Wellcome Trust Sanger Institute, Sanger Institute); Alex Bateman (Wellcome Trust Sanger Institute, Sanger Institute); |
| Short Abstract: The relative contributions of different molecular mechanisms that underlie domain gains in animals are as yet unclear. Here we show that the major mechanism for domain gains in metazoa is gene duplication and joining of adjacent genes' exons, possibly mediated by non-allelic homologous recombination. |
| Long Abstract: Click Here |
| Poster F10 |
| Darwin Rocks! |
| Daniel Huson- Tuebingen University |
| Johannes Faber (Tuebingen University, Biology); Nico Michiels (Tuebingen University, Biology); |
| Short Abstract: In this poster we present Darwin Rocks!, a program for demonstrating principles of evolution using "tuneomes", which are like genomes, except that they encode pieces of music rather than organisms. The Darwin Rocks! program is freely available from www.darwinrocks.de. |
| Long Abstract: Click Here |
| Poster F11 |
| Signature genes as a phylogenomic tool |
| Bas Dutilh- Radboud University Nijmegen Medical Centre |
| Berend Snel (Utrecht University, Department Biology and Academic Biomedical Centre); Thijs J.G. Ettema (Uppsala Universitet, Department of Molecular Evolution); Ying He (Ghent University, VIB Department of Plant Systems Biology); Maarten L. Hekkelman (Radboud University Nijmegen Medical Centre, CMBI); Martijn A. Huynen (Radboud University Nijmegen Medical Centre, CMBI); |
| Short Abstract: Signature genes are unique to a taxonomic clade andare present in all daughter lineages. They can be usedfor the phylogenetic characterisation of sequencesamples, including incomplete genomes and metagenomicsamples. We have tested the reliability of signaturegenes as a phylogenomic tool, and implementedthe method in a web server. |
| Long Abstract: Click Here |
| Poster F12 |
| Assessing the impact of protein structure on sequence evolution |
| Claudia Kleinman- Université de Montréal |
| Nicolas Rodrigue (University of Ottawa, Biology); Nicolas Lartillot (Universite de Montreal, Biochemistry); Hervé Philippe (Universite de Montreal, Biochemistry); |
| Short Abstract: Despite the undeniable role that protein structure plays in the evolution of protein sequences, tools for considering it explicitly in models of sequence evolution remain primitive. We present a statistical potential (a scoring system for sequence-structure compatibility) specifically designed for the recently developed structurally constrained evolutionary models. |
| Long Abstract: Click Here |
| Poster F13 |
| Insertion Sequences Distribution And Evolution In Prokaryotic Genomes Using Network Approach. |
| Nicola Vitulo- CRIBI Biotecnology Centre, University of Padova |
| Riccardo Rosselli (CRIBI Biotecnology Centre, University of Padova, Biology); Alessandro Vezzi (CRIBI Biotecnology Centre, University of Padova, Biology); Enrico Negrisolo (University of Padova, Public Health, Comparative Pathology and Veterinary Hygiene); Giorgio Valle (CRIBI Biotecnology Centre, University of Padova- Biology, Biology); |
| Short Abstract: Insertion Sequences (IS) are the simplest form of transposable elements and considered key elements for genome plasticity and variability. We studied ISs distribution among 765 fully sequenced bacteria. The results suggest the existence of a “core†of ISs phyla specific, transferred with a vertical mechanisms and with a phylogenetic signal. |
| Long Abstract: Click Here |
| Poster F14 |
| Automated comparative analysis of transcriptional factors expressed in stem cells |
| Achille Zappa- Bioinformatics, National Cancer Research Institute (IST), Genoa – Italy ; IEIIT, National Research Council (CNR), Genoa – Italy |
| Mariangela Miele (National Cancer Research Institute (IST), Genoa – Italy, Bioinformatics); Paolo Romano (National Cancer Research Institute (IST), Genoa – Italy, Bioinformatics); |
| Short Abstract: An automated workflow has been designed and implemented in order to investigate the similarity among transcriptional factors involved in the maintenance of totipotency in plant, planarian, drosophila and mammalian stem cells. Identifiers or sequences of selected proteins are used as input; alignments, with relative phylogenetic distance files constitute the output. |
| Long Abstract: Click Here |
| Poster F15 |
| Detection of horizontal gene transfer in prokaryotes using BLAST and 16S rRNA distances |
| Apuã Paquola- Universidade de São Paulo |
| Wanessa Lima (Instituto de Ciências Biomédicas/Universidade de São Paulo, Depto. de Microbiologia); Carlos Menk (Instituto de Ciências Biomédicas/Universidade de São Paulo, Depto. de Microbiologia); |
| Short Abstract: We have developed a new HGT detection method based on BLAST and 16S rRNA sequence distances. Application in 408 prokaryotic genomes shows that: (i) operational genes are more prone to HGT than informational genes; (ii) genes with few interaction partners participate more often in HGT than those with many partners. |
| Long Abstract: Click Here |
| Poster F16 |
| Virus Classification Using Phylogenetic Networks |
| Ingo Bulla- University of Goettingen |
| Anne-Kathrin Schultz (University of Goettingen, Bioinformatics); Fabian Schreiber (University of Goettingen, Bioinformatics); Ming Zhang (Los Alamos National Laboratory, Theoretical Division); Thomas Leitner (Los Alamos National Laboratory, Theoretical Division); Bette Korber (Los Alamos National Laboratory, Theoretical Division); Burkhard Morgenstern (University of Goettingen, Bioinformatics); Mario Stanke (University of Goettingen, Bioinformatics); |
| Short Abstract: We developed the program ARGUS that scores classifications of HIV sequences into subtypes and recombinant forms. It reconstructs Ancestral Recombination Graphs (ARGs) that reflect the genealogy of the input sequences given a classification hypothesis. An ARG with maximal probability is approximated using a Markov Chain Monte Carlo approach. |
| Long Abstract: Click Here |
| Poster F17 |
| Robust phylogenetic trees for annotation of evolutionary inferences |
| Paul Thomas- SRI International |
| Stan Dong (SRI International, Evolutionary Systems Biology); |
| Short Abstract: Evolutionary gene trees are a workhorse of comparative genomics, yet they remain underutilized, partly due to lack of robustness as data are added or corrected. We present a new algorithm for gene tree inference that dramatically improves robustness; the Gene Ontology Consortium is annotating functional evolution within these trees. |
| Long Abstract: Click Here |
| Poster F19 |
| Frequent Toggling between Alternative Amino Acids Is Driven by Selection in HIV-1 |
| Konrad Scheffler- University of Stellenbosch |
| Wayne Delport (University of Cape Town, Institute of Infectious Disease and Molecular Medicine); Cathal Seoighe (University of Cape Town, Institute of Infectious Disease and Molecular Medicine); |
| Short Abstract: We develop a phylogenetic model of immune escape and reversion and provide evidence that it outperforms existing models for the detection of selective pressure associated with host immune responses. The model demonstrates that amino acid toggling is a pervasive process in HIV-1 evolution. |
| Long Abstract: Click Here |
| Poster G01 |
| Tissue-specific repression of certain housekeeping genes is essential to allow specialized tissue function |
| Lieven Thorrez- K.U.Leuven |
| Ilaria Laudadio (Universite Catholique de Louvain, de Duve Institute); Katrijn Van Deun (K.U.Leuven, Department of Psychology); Roel Quintens (K.U.Leuven, Gene expression unit); Nico Hendrickx (K.U.Leuven, Gene expression unit); Mikaela Granvik (K.U.Leuven, Gene expression unit); Katleen Lemaire (K.U.Leuven, Gene expression unit); Anica Schraenen (K.U.Leuven, Gene expression unit); Leentje Van Lommel (K.U.Leuven, Gene expression unit); Stefan Lehnert (K.U.Leuven, Gene expression unit); Cristina Aquayo-Mazzucato (Harvard University, Section of islet transplantation and cell biology); Susan Bonner-Weir (Harvard University, Section of islet transplantation and cell biology); Rui Cheng-Xue (University of Louvain, Unite d\\\'endocrinologie et metabolisme); Patrick Gilon (University of Louvain, Unite d\\\'endocrinologie et metabolisme); Ivan Van Mechelen (K.U.Leuven, Psychology); Frederic Lemaigre (Universite Catholique de Louvain, de Duve Institute); Frans Schuit (K.U.Leuven, Gene expression unit); |
| Short Abstract: We propose that specific tissue functions not only rely on tissue-specific gene expression but also on tissue-specific gene repression, which is established during maturation of these tissues. |
| Long Abstract: Click Here |
| Poster G02 |
| BRISKA: Brassica Seed Knowledge Application |
| Hugo Berube- National Research Council Canada |
| Alain Tchagang (National Research Council Canada, Institute for Information Technology); Yunli Wang (National Research Council Canada, Institute for Information Technology); Ziying Liu (National Research Council Canada, Institute for Information Technology); Sieu Phan (National Research Council Canada, Institute for Information Technology); Fazel Famili (National Research Council Canada, Institute for Information Technology); Youlian Pan (National Research Council Canada, Institute for Information Technology); |
| Short Abstract: The Brassica Seed Knowledge Application (BRISKA) is an interactive web-based application providing, via interactive tools, useful biological information for functional genomics studies of oilseed crops with emphasis on seed development and fatty acid metabolism in Brassica napus and related species. |
| Long Abstract: Click Here |
| Poster G03 |
| Building your own gene sets with WhichGenes, a new webtool for creating biological hypothesis to test in gene set based methods. |
| Gonzalo Gómez-López- CNIO |
| Daniel Gonzalez-Peña (University of Vigo, Higher Technical School of Computer Engineering); Florentino Fernandez-Riverola (University of Vigo, Informatics Department); David Gonzalez-Pisano (CNIO, Bioinformatics Unit); |
| Short Abstract: Whichgenes is a new web-tool to build gene sets from multiple and scattered biological databases. The aim of this user-friendly server is to facilitate the creation of biological hypothesis to test using gene set based methods. |
| Long Abstract: Click Here |
| Poster G04 |
| Functional annotation of orthologous groups by using hierarchical multi label classification |
| Nives Skunca- Rudjer Boskovic Institute |
| Fran Supek (Rudjer Boskovic Institute, Department of Electronics); Tomislav Smuc (Rudjer Boskovic Institute, Department of Electronics); Pance Panov (Jozef Stefan Institute, Department of Knowledge Technologies); Saso Dzeroski (Jozef Stefan Institute, Department of Knowledge Technologies); |
| Short Abstract: The object of research was assessing the success of phylogenetic profiling in predicting the function of protein groups in the Orthologous Matrix project, when using decision-trees for Hierarchical Multilabel Classification. Performance analysis will be presented, broken down per Gene ontology category, discussing the effect of different features used in prediction. |
| Long Abstract: Click Here |
| Poster G05 |
| A systematic analysis of alternative 3’ UTR of human transcripts: improvement of detection of microRNA targets |
| Gabriele Sales- University of Padua |
| Marta Biasiolo (University of Padua, Department of Biology); Silvio Bicciato (University of Modena, Department of Medical Biosciences); Stefania Bortoluzzi (University of Padua, Department of Biology); Chiara Romualdi (University of Padua, Department of Biology); |
| Short Abstract: MicroRNAs are small noncoding RNAs that serve as post-transcriptional regulators of gene expression in Eukaryotes. DNA microarray technology can be used to detect the interaction between microRNAs and their targets. Given that microRNAs interact with 3\\\'UTR regions only, we propose a custom annotation scheme based on custom 3'UTR transcript annotation. |
| Long Abstract: Click Here |
| Poster G06 |
| ConceptGen: A gene set enrichment and concept mapping tool |
| Maureen Sartor- University of Michigan |
| Vasudeva Mahavisno (Univ of Michigan, CCMB); Zach Wright (Univ of Michigan, CCMB); Alla Karnovsky (Univ of Michigan, CCMB); Gilbert Omenn (Univ of Michigan, CCMB); Brian Athey (Univ of Michigan, CCMB); James Cavalcoli (Univ of Michigan, CCMB); |
| Short Abstract: We have developed ConceptGen, a web-based gene set enrichment and concept mapping tool that allows researchers to identify biological concepts, derived from 13 knowledge sources, in their experimental results or collaborative analyses. Networks of relationships among these diverse concepts, including several hundred experimentally-derived gene sets, can be explored and visualized. |
| Long Abstract: Click Here |
| Poster G07 |
| Designing, Executing, and Sharing Scientific Workflows: Taverna and myExperiment |
| Paul Fisher- University of Manchester |
| Alan Williams (University of Manchester, Computer Science); Aleksandra Nenadic (University of Manchester, Computer Science); Constantinos Astreos (University of Manchester, Computer Science); Danius Michaelides (University of Southampton, Computer Science); Don Cruickshank (University of Southampton, Computer Science); David De Roure (University of Southampton, Computer Science); David Withers (University of Manchester, Computer Science); Franck Tanoh (University of Manchester, Computer Science); Ian Dunlop (University of Manchester, Computer Science); Jiten Bhagat (University of Manchester, Computer Science); Katy Wolstencroft (University of Manchester, Computer Science); Paolo Missier (University of Manchester, Computer Science); Sergejs Aleksejevs (University of Manchester, Computer Science); Stian Soiland-Reyes (University of Manchester, Computer Science); Stuart Owen (University of Manchester, Computer Science); Tom Oinn (Contractor, Computer Science); Carole Goble (University of Manchester, Computer Science); |
| Short Abstract: The Taverna workbench allows scientists to design and execute scientific workflows, combining distributed services and data resources into a single experimental protocol. Workflows provide a means of conducting systematic and explicit data analyses. Workflows developed in Taverna can be shared through myExperiment, a social networking site for scientists. |
| Long Abstract: Click Here |
| Poster G08 |
| Global modeling of cancer gene expression signatures |
| Leo Lahti- Helsinki University of Technology |
| Samuel Myllykangas (Stanford University School of Medicine, Division of Oncology); Sakari Knuutila (University of Helsinki, Haartman Institute); Samuel Kaski (Helsinki University of Technology, Information and Computer Science); |
| Short Abstract: Heterogeneous cancer types are coupled through common functionalchanges and the corresponding gene expressionsignatures. Computational modeling of these functional relationshipsis used to build a comprehensive view of the functional landscape ofhuman cancer. |
| Long Abstract: Click Here |
| Poster G09 |
| Generalised Linear Models of yeast transcriptional regulation |
| Juri Reimand- University of Tartu |
| Juan Vaquerizas (EMBL , European Bioinformatics Institute); Annabel Todd (EMBL , European Bioinformatics Institute); Jaak Vilo (University of Tartu, Insitute of Computer Science); |
| Short Abstract: Transcriptional regulation is a complex and poorly characterised process. We present a framework for predicting transcriptional regulatorsof selected cellular processes, using protein-DNA interactions and expressionprofiles of transcription factor (TF) knockouts. Our model successfully recovers the yeast cell cycle, as 7 of the 10 key cell cycle TFs are detected in top10 list of candidates. |
| Long Abstract: Click Here |
| Poster G10 |
| Cross-platform microarray compendium and a corresponding web interface |
| Qiang FU- Katholieke Universiteit Leuven |
| kristof engelen (Katholieke Universiteit Leuven, Centre of Microbial and Plant Genetics); Pieter Meysman (Katholieke Universiteit Leuven, Centre of Microbial and Plant Genetics); Karen Lemmens (Katholieke Universiteit Leuven, Centre of Microbial and Plant Genetics); Riet De Smet (Katholieke Universiteit Leuven, Centre of Microbial and Plant Genetics); Carolina Fierro (Katholieke Universiteit Leuven, Centre of Microbial and Plant Genetics); Inge Thijs (Katholieke Universiteit Leuven, Centre of Microbial and Plant Genetics); Kathleen Marchal (Katholieke Universiteit Leuven, Centre of Microbial and Plant Genetics); |
| Short Abstract: We have designed a (semi-automatic) system to create cross-platform expression compendia, offering the advantage of maximally exploiting publicly available information. A web interface exists for public access of the data, including tools for performing query-based bi-clustering and visualization of overlapping bi-clusters. Compendia are created for Escherichia coli, Salmonella enterica and Bacillus subtilis. |
| Long Abstract: Click Here |
| Poster G11 |
| Discovery of functional human ncRNAs by expression profiling using new mapping of microarray probes to the non protein coding transcriptome |
| Alberto Risueño- Cancer Research Center (CIC, CSIC/USAL) |
| Carlos Prieto (Cancer Research Center (CIC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); Celia Fontanillo (Cancer Research Center (CIC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); Javier De Las Rivas (Cancer Research Center (CIC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); |
| Short Abstract: Transcriptomic profiling provided by high density microarrays includes a significant signal coming from non-protein coding RNAs (like miRNAs, snRNA, etc). However, specific expression signal produced by such bio-entities is usually neglected. We use significant differential expression of probes remapped to non-protein coding transcriptome to discover functional ncRNAs. |
| Long Abstract: Click Here |
| Poster G12 |
| Identification of functional related gene in Malaria parasites using Computational Pipeline Technique |
| Jelili Oyelade- Covenant University |
| Ezekiel Adebiyi (Covenant University, Computer and Information Sciences); |
| Short Abstract: P. falciparum, is the most deadly form of malaria. Several computational methods have been used to identify genes clustering. Grouping of genes that are co-regulated in a metabolic pathway is very important in drug prediction. We applied k-means clustering tool to classify genes into their various metabolic pathways. |
| Long Abstract: Click Here |
| Poster G13 |
| Genome-wide DNA Methylation Analysis by sequencing of reduced complexity bisulfite-treated genomic fragments |
| Irina Khrebtukova- Illumina, Inc. |
| Lu Zhang (Illumina, Inc., Expression Applications R&D); Raymond McCauley (Illumina, Inc., Expression Applications R&D); Juying Yan (Illumina, Inc., Expression Applications R&D); Gary P Schroth (Illumina, Inc., Expression Applications R&D); |
| Short Abstract: Next-generation sequencing with the Illumina GAII system allows study of DNA methylation at single base resolution on the whole genome scale. We have developed a bioinformatics pipeline for alignment of bisulfite-converted methylated fragments to the genome followed by scoring of methylation levels of CpG dinucleotides on a genome-wide scale. |
| Long Abstract: Click Here |
| Poster G14 |
| Meta-analysis of Chronic obstructive pulmonary disease public gene expression datasets |
| Ketan Patel- Pfizer Ltd |
| Sari Ward (Pfizer Ltd, eBiology); Iain Kilty (Pfizer Ltd, Allergy and Respiratory); |
| Short Abstract: A meta-analysis of several publically available Chronic obstructive pulmonary disease (COPD) gene expression datasets was performed. To understand the consistent gene expression changes in lung tissue we used gene set enrichment techniques and the 'Connectivity map' of small molecule gene expression signatures to identify pathways for drug targeting. |
| Long Abstract: Click Here |
| Poster G15 |
| Understanding the consistency of molecular changes in Endometriosis through meta-analysis of public gene expression datasets |
| Roddy Walsh- Pfizer Ltd |
| Ketan Patel (Pfizer Ltd., Computational Sciences); Anneli Sullivan (Pfizer Ltd, eBiology); |
| Short Abstract: A meta-analysis of public Endometriosis gene expression datasets was performed. Due to the large amount of gene changes, we have used a comprehensive approach to tease apart underlying consistent changes in biological processes. Our results provide an understanding of data consistency between the various published datasets and provide guidance for designing future studies. |
| Long Abstract: Click Here |
| Poster G16 |
| An Ensemble Model of Competitive Multi-factor Binding of the Genome |
| Todd Wasson- Duke University |
| Alexander Hartemink (Duke University, Department of Computer Science); |
| Short Abstract: DNA occupancy by various proteins and protein complexes is the result of thermodynamic competition amongst them. This competition is driven by the sequence preferences and concentration of each of these DNA binding factors. We present a model that explicitly considers competition to produce a probabilistic representation of DNA occupancy. |
| Long Abstract: Click Here |
| Poster G17 |
| MouseCyc: a pathways approach to integration of mouse functional, phenotype and expression data |
| Judith Blake- The Jackson Laboratory |
| Alexei Evsikov (The Jackson Laboratory, Mouse Genome Informatics); Mary E. Dolan (The Jackson Laboratory, Mouse Genome Informatics); Carol J. Bult (The Jackson Laboratory, Mouse Genome Informatics); |
| Short Abstract: MouseCyc is a database of curated biochemical pathways for the laboratory mouse. We have developed a resource based on pathway genes sets that integrates functional, phenotype and expression data for MouseCyc pathways based on mouse genetic and genomic data available at Mouse Genome Informatics. |
| Long Abstract: Click Here |
| Poster G18 |
| Subtractive Genomic Context and the Gene Modules of Patho-genic strains of Escherichia coli |
| Gabriel Moreno-Hagelsieb- Wilfrid Laurier University |
| Anis Karimpour-Fard (University of Colorado School of Medicine, Center for Computational Pharmacology); Lawrence Hunter (University of Colorado School of Medicine, Center for Computational Pharmacology); |
| Short Abstract: This work demonstrates the use of subtractive interactomics for examining the functional interactions that differentiate evolutionarily closely related Prokaryotes, such as non-pathogenic and pathogenic strains of Escherichia coli. We focused on distinct interactions responsible for pathogenicity by comparing two pathogenic strains against each other, and against a non-pathogenic strain. |
| Long Abstract: Click Here |
| Poster G19 |
| Using related functions to improve the construction of composite functional linkage networks |
| Sara Mostafavi- University of Toronto |
| Quaid Morris (University of Toronto, Computer Science); |
| Short Abstract: We use related Gene Ontology categories to improve the construction of composite functional linkage networks. In doing so, we show that we can considerably improve the accuracy of gene function prediction on several benchmark datasets. |
| Long Abstract: Click Here |
| Poster G20 |
| Meta - Analysis |
| Mahesh Visvanathan- KU |
| Mahesh Visvanathan (KU, BCF); Gerald Lushington (KU, BCF); |
| Short Abstract: Meta-analysis of microarray data coming from a number of microarray experiments can be attempted with two systematically different approaches. |
| Long Abstract: Click Here |
| Poster G21 |
| Design and implementation of image and data analysis strategies for assessing the relationship between cell state and endocytic system in a high-content genome-wide screening |
| Giovanni Marsico- Max Planck Institut of Molecular Cell Biology and Genetics |
| Yannis Kalaidzidis (Max Planck Institut of Molecular Cell Biology and Genetics , MPG); Marino Zerial (Max Planck Institut of Molecular Cell Biology and Genetics , MPG); |
| Short Abstract: We propose a new methodology for the analysis of cell-based, high-content assays. We design and implement image and data analysis strategies for assessing the relationship between cell state and endocytic system. We show as a proof of principle how this approach can lead to the formulation of new biological hypothesis. |
| Long Abstract: Click Here |
| Poster G22 |
| Supervised learning for detection of transcription factor binding sites |
| Justin Bedo- NICTA |
| Geoff Macintyre (NICTA, Life Sciences); Izhak Haviv (Baker IDI, ); Adam Kowalczyk (NICTA, Life Sciences); |
| Short Abstract: We have developed a supervised prediction method for genome-wide discovery oftranscription factor (TF) binding sites that uses sequence information only.Using a single chromosome TF binding profile, we trained a support vectormachine (SVM) which predicts TF binding with an accuracy superior to standardposition-weight matrix (PWM) approaches. |
| Long Abstract: Click Here |
| Poster G23 |
| Nucleosome-free Regions are Associated with Coding and Non-coding Transcripts |
| Karin Schwarzbauer- Johannes Kepler University |
| Ulrich Bodenhofer (Johannes Kepler University, Institute of Bioinformatics); Mihaela Ionescu (Johannes Kepler University, Institute of Bioinformatics); Sepp Hochreiter (Johannes Kepler University, Institute of Bioinformatics); |
| Short Abstract: We analyze sequence characteristics of long nucleosome-free regions (lNFRs) in the human genome obtained from next-generation sequencing. lNFR sequences in promoter regions and the remaining lNFR sequences share the same sequence patterns, hence long NFR sequences not lying in known promoter regions potentially reveal previously unknown transcripts. |
| Long Abstract: Click Here |
| Poster G24 |
| Novel RNA Paired-End Sequencing Technique Generates High-Resolution Map of Drosophila Melanogaster Transcription Start Sites During Embryogenesis |
| David Corcoran- Duke University |
| Ting Ni (Duke University, Institute for Genome Sciences and Policy); Yuan Gao (Virginia Commonwealth University, School of Engineering); Elizabeth Rach (Duke University, Institute for Genome Sciences and Policy); Eric Spana (Duke University, Department of Biology); Jun Zhu (Duke University, Institute for Genome Sciences and Policy); Uwe Ohler (Duke University, Institute for Genome Sciences and Policy); |
| Short Abstract: Our study utilizes a novel high-throughput sequencing technique for the identification of transcription start sites, and we present a high-resolution map of start sites utilized by Drosophila melanogaster during embryogenesis. This map makes it possible to identify sequence specific features that are associated with different types of transcriptional initiation. |
| Long Abstract: Click Here |
| Poster G25 |
| Mechanisms for Action of the Ultraconserved Elements in Embryonic Stem Cell Differentiation |
| Courtney Onodera- University of California, Santa Cruz |
| Jason Underwood (University of California, Santa Cruz, Howard Hughes Medical Institute); Sol Katzman (University of California, Santa Cruz, Biomolecular Engineering); Bryan King (University of California, Santa Cruz, Howard Hughes Medical Institute); Sara Sowko (University of California, Santa Cruz, Biomolecular Engineering); Andre Love (University of California, Santa Cruz, Howard Hughes Medical Institute); Sofie Salama (University of California, Santa Cruz, Howard Hughes Medical Institute); David Haussler (University of California, Santa Cruz, Howard Hughes Medical Institute); |
| Short Abstract: We examine the ultraconserved elements as transcriptional regulators in neural differentiation of mouse embryonic stem cells. We demonstrate with a luciferase reporter that several UCEs possess activity as cis-regulatory DNA elements and present current RNA-sequencing efforts to uncover novel UCE-derived ncRNAs that may be involved in transcriptional regulation. |
| Long Abstract: Click Here |
| Poster H1 |
| Searching for Genes in Novel Genomes |
| Brona Brejova- Comenius University Bratislava |
| Tomas Vinar (Comenius University Bratislava, Applied Informatics); Daniel G. Brown (University of Waterloo, Computer Science); Ming Li (University of Waterloo, Computer Science); Yan Zhou (Chinese National Human Genome Center at Shanghai, Shanghai-MOST Key Laboratory of Health and Disease Genomics); |
| Short Abstract: We have developed a novel iterative method for estimating parametersof hidden Markov models for gene finding in newly sequencedspecies. We have used our approach to produce initial annotation ofnewly sequenced Schistosoma japonicum draft genome. Our new gene setprovides a first glimpse at a gene complement of a flatworm (phylumplatyhelmintes). |
| Long Abstract: Click Here |
| Poster H2 |
| Improving Gene Finding Accuracy with RNA_Seq and Tiling Array Data |
| Jonas Behr- Max Planck Society |
| Gabriele Schweikert (Max Planck Society, Friedrich Miescher Laboratory); |
| Short Abstract: We have developed a new accurate gene finding system called mGene based on Hidden Semi Markov SVMs, that is very flexible in terms of incorporating different features. Exploiting tiling array and RNA-Seq transcriptome measurements as features in addition to the genome sequence leads to considerably improvements in prediction accuracy. |
| Long Abstract: Click Here |
| Poster H3 |
| The effect of sequencing errors on metagenomic gene prediction |
| Katharina Hoff- Georg-August-Universität Göttingen |
| Maike Tech (Georg-August-Universität Göttingen, Institut für Mikrobiologie und Genetik, Abteilung für Bioinformatik); Fabian Schreiber (Georg-August-Universität Göttingen, Institut für Mikrobiologie und Genetik, Abteilung für Bioinformatik); Peter Meinicke (Georg-August-Universität Göttingen, Institut für Mikrobiologie und Genetik, Abteilung für Bioinformatik); |
| Short Abstract: Gene prediction is essential during the annotation of metagenomic sequencing reads. In a benchmark test, we compared the performance of gene prediction tools on simulated reads with sequencing errors. Our results suggest that the incorporation of similar error-compensating methods into metagenomic gene prediction tools may improve their quality significantly. |
| Long Abstract: Click Here |
| Poster H4 |
| A Fully Automatic AUGUSTUS Pipeline for Eukaryotic Genome Annotation Based on ESTs |
| Mario Stanke- Universit of Goettingen |
| No additional authors |
| Short Abstract: We are presenting an open source gene prediction pipeline that only requires a genome assembly and a set of ESTs as input. It trains AUGUSTUS fully automatically using the ESTs. The gene structure annotation is then basedon EST evidence where locally available or is performed ab initio. |
| Long Abstract: Click Here |
| Poster H5 |
| mGene.web: A Web Service for Accurate Computational Gene Finding |
| Ratsch Gunnar- Friedrich Miescher Laboratory of the Max Planck Society |
| Gabriele Schweikert (Friedrich Miescher Laboratory, Machine Learning in Biology); Jonas Behr (Friedrich Miescher Laboratory, Machine Learning in Biology); Alexander Zien (Friedrich Miescher Laboratory, Machine Learning in Biology); Johannes Eichner (Friedrich Miescher Laboratory, Machine Learning in Biology); Soeren Sonnenburg (Friedrich Miescher Laboratory, Machine Learning in Biology); Gunnar Raetsch (Friedrich Miescher Laboratory, Machine Learning in Biology); |
| Short Abstract: We provide mGene.web, a web service for genomewideprediction of protein coding genes from DNAsequences. mGene.web additionally offers the functionalityto retrain the system on a new organism.It is integrated into the Galaxy framework forgenomic data analysis, is availableat http://www.mgene.org/webservice, freeof charge, and can be used for eukaryotic genomes ofmoderate size. |
| Long Abstract: Click Here |
| Poster I01 |
| Automatic Functional Annotation in a Distributed Web Service Environment |
| Anika Joecker- Max-Planck Institute for Plant Breeding Research |
| Andreas Joecker (Max-Planck Institute for Plant Breeding Research, Plant Computational Biology); Ulrike Göbel (Max-Planck Institute for Plant Breeding Research, Bioinformatics Support); Heiko Schoof (Max-Planck Instiute for Plant Breeding Research, Plant Computational Biology); |
| Short Abstract: We present a phylogenomics approach integrated in a web service workflow that is able to predict the function of a gene very precisely. The workflow is integrated in AFAWE, a tool for the automatic and manual annotation of genes, and used in the Medicago and tomato genome projects. |
| Long Abstract: Click Here |
| Poster I02 |
| PREDICTION OF NOVEL SHORT PROTEINS USING COMPARATIVE GENOMICS AND LOCAL PROTEIN STRUCTURE PROPERTIES |
| Josue Samayoa- UC Santa Cruz |
| Kevin Karplus (UC Santa Cruz, Biomolecular Engineering); |
| Short Abstract: Short proteins (50 amino acids or less) are increasingly being characterized as functional biological components. However, accurate prediction of short proteins remains an open problem in bioinformatics. We developed a method that incorporates local protein structure properties into a comparative genomic analysis to generate whole-genome short protein predictions. |
| Long Abstract: Click Here |
| Poster I03 |
| Predicting RNA-binding proteins on a genomic scale |
| Susan Jones- University of Sussex |
| Ruth Spriggs (University of Sussex, Biochemistry); Yoichi Murakami (National Institute of Biomedical Innovation, Bioinformatics); |
| Short Abstract: A two-stage support vector machine has been developed that predicts RNA-binding function at the protein level based on the prediction of RNA binding at the residue level; using only sequence information. The method achieves an MCC of 0.5 and has the potential to identify novel RNA-binding proteins on a genomic scale. |
| Long Abstract: Click Here |
| Poster I04 |
| Comprehensive Solexa Based Annotation of Alternatively Spliced Transcripts in Drosophila melanogaster Male, Female, and tra Mutant Transcriptomes |
| Joyce Kao- University of Southern California |
| Joseph Dunham (University of Southern California, Molecular Computational Biology); Frances Sung (University of Southern California, Molecular Computational Biology); Mazin Elhadary (University of Southern California, Molecular Computational Biology); Michelle Arbeitman (University of Southern California, Molecular Computational Biology); Sergey Nuzdhin (University of Southern California, Molecular Computational Biology); |
| Short Abstract: We have Solexa sequenced male, female, and tra mutant D. melanogaster transcriptomes and are seeking to annotate alternatively spliced transcripts between those specimens. The methods we develop to do so will also be applied across species to D. simulans and D. yakuba. |
| Long Abstract: Click Here |
| Poster I05 |
| PromoterSweep: Identification of Transcription Factor Binding Sites |
| Agnes Hotz-Wagenblatt- German Cancer Research Center (DKFZ) |
| Karl-Heinz Glatting (German Cancer Research Center (DKFZ), Mol. Biophysics ); Oliver Pelz (German Cancer Research Center (DKFZ), Mol. Biophysics ); Coral del Val (University Granada, ETS Ingenieria Informatica); Sándor Suhai (German Cancer Research Center (DKFZ), Mol. Biophysics); |
| Short Abstract: A new pipeline is available for the prediction of transcription factor binding sites (TFBS), and potential promoter regions using a combination of different methods to enhance prediction accuracy. Methods employed include searches to promoter databases, the search against TFBS databases, and motif discovery tools using orthologous sequences. |
| Long Abstract: Click Here |
| Poster I06 |
| Maximum likelihood estimation for targeted homology search |
| Peter Menzel- University of Copenhagen / Faculty of Life Sciences |
| Jan Gorodkin (University of Copenhagen / Faculty of Life Sciences, Department of Animal and Veterinary Basic Sciences); Peter Stadler (University of Leipzig, Institute for Computer Sciences); |
| Short Abstract: Modeling the characteristic motifs of genes is still a manual task that requires expertise and constrains large scale genome annotations. We suggest an approach for creating models based on multiple sequence alignments that are suitable for searching in a particular phylogenetic branch by calculating residue probabilities at each alignment position. |
| Long Abstract: Click Here |
| Poster I07 |
| Blannotator - making sense of Blast annotations |
| Matti Kankainen- Institute of Biotechnology, University of Helsinki |
| Liisa Holm (University of Helsinki, Institute of Biotechnology); |
| Short Abstract: One line descriptions are the most popular way to represent the function of a gene. Blannotator creates a concise summary from the match list generated by Blast. Blannotator is a highly accurate tool for the annotation of thousands of gene or protein sequences in a matter of minutes. |
| Long Abstract: Click Here |
| Poster I08 |
| Xanthomonas vasicola pathovar musacearum draft genome and the putative virulence factors |
| Mtakai Ngara- International Institute of Tropical Agriculture(IITA) |
| No additional authors |
| Short Abstract: Xanthomonas vasicola pathovar musacearum (XVM) is an etiological agent of Xanthomonas wilt, a disease affecting all genome groups and varieties of the Musa species. Using in silico approaches, XVM draft genome has been annotated and the genes responsible for it's virulence and pathogenesis characterized. |
| Long Abstract: Click Here |
| Poster I09 |
| MaDAS a collaborative tool for genome annotation. |
| Victor Russis- Spanish National Bioinformatics Institute (INB), Spanish National Cancer Research Centre (CNIO) |
| Alfonso Valencia (Spanish National Cancer Research Centre (CNIO), Structural Biology and Biocomputing); |
| Short Abstract: MaDAS is a collaborative annotation environment for the annotation of genomes (or set of sequences) by the end users of the information. The system is oriented to the use by groups of geographyically disperse groups of users, typically experimental biologist, organized in research teams. |
| Long Abstract: Click Here |
| Poster I10 |
| Annotating Principal Isoforms with APPRIS |
| Jose Manuel Rodriguez- Spanish National Cancer Research Center (CNIO) |
| Iakes Ezkurdia (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Gonzalo Lopez (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Alessandro Pietrelli (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Jan-Jaap Wesselink (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Alfonso Valencia (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Michael Tress (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); |
| Short Abstract: We have developed a server to annotate principal functional variants for well-annotated genes. The server deploys a range of computational methods including the conservation of exonic structure and the conservation of protein structure and function. The server is currently being used in ENCODE project to annotate the human genome. |
| Long Abstract: Click Here |
| Poster I11 |
| BASys 2: Distributed laboratory software for automated bacterial genome annotation, analysis and visualization |
| Matthew Stuart-Edwards- Public Health Agency of Canada - National Microbiology Laboratories |
| Aaron Petkau (Public Health Agency of Canada - National Microbiology Laboratory, Bioinformatics Core); Gary Van Domselaar (Public Health Agency of Canada - National Microbiology Laboratory, Bioinformatics Core); Paul Stothard (University of Alberta, Department of Agricultural, Food and Nutritional Science); |
| Short Abstract: BASys 2 is a prokaryotic genome annotation, analysis and visualization software platform designed to provide a powerful and flexible analysis tools for biologists. Annotation functionality is extendable through the use of plugins, and computation annotation workload can be distributed across multiple computers. |
| Long Abstract: Click Here |
| Poster I12 |
| Comparative Multi Genome Annotation with Gnomon |
| Alexandre Souvorov- National Center for Biotechnology Information |
| Yuri Kapustin (National Center for Biotechnology Information, IEB); Boris Kiryutin (National Center for Biotechnology Information, IEB); Vyacheslav Chetvernin (National Center for Biotechnology Information, IEB); Tatiana Tatusova (National Center for Biotechnology Information, IEB); David Lipman (National Center for Biotechnology Information, IEB); |
| Short Abstract: Genome sequencing from Fungi and Protozoa are focusing on closely related species for comparative studies. These genomes often lack transcript data. Our multi-genome approach is an iterative process that uses protein similarity between predicted genes to gradually improve the annotation. The results for Theileria and Aspergillus are presented. |
| Long Abstract: Click Here |
| Poster I13 |
| Transcript Identification from Tiling Array Data |
| Georg Zeller- Friedrich Miescher Laboratory of the Max Planck Society |
| Sascha Laubinger (Max Planck Isntitute for Developmental Biology, Molecular Biology); Jonas Behr (Friedrich Miescher Laboratory of the Max Planck Society, Machine Learning in Biology); Timo Sachsenberg (Max Planck Institute for Developmental Biology, Molecular Biology); Detlef Weigel (Max Planck Institute for Developmental Biology, Molecular Biology); Gunnar Rätsch (Friedrich Miescher Laboratory of the Max Planck Society, Machine Learning in Biology); |
| Short Abstract: Whole-genome tiling arrays allow characterizing the transcriptome under various conditions. For the central analysis task of identifying expressed transcripts, we present machine learning methods that exploit a combination of hybridization and sequence features. Evaluation on Arabidopsis tiling array data and annotated transcripts indicates greatly improved accuracy compared to other methods. |
| Long Abstract: Click Here |
| Poster I14 |
| BLASTScanner: Fast BLAST data processing with database output |
| Detlef Groth- University Potsdam |
| Joachim Selbig (University Potsdam, AG Bioinformatics); Albert J. Poustka (MPIMG Berlin, Evolution and Development); Georgia Panopoulou (MPIMG Berlin, Evolution and Development); |
| Short Abstract: Scanning BLAST files is still not on solved problem. We use crossplatform single file C-applications generated with the scanner generator re2c developing scanners of biological data. They are easy to install, download and run. The output is database code suitable for piping into standard relational database systems. |
| Long Abstract: Click Here |
| Poster I15 |
| Anchors based annotation of subsystem: Application to oxidative stress response in prokaryotic genomes |
| David Thybert- CNRS UMR 6026 |
| Stephane Avner (CNRS UMR 6026 , Equipe B@sic); Céline Lucchetti-Miganeh (CNRS UMR 6026 , Equipe B@sic); Angélique Chéron (CNRS UMR 6026 , Equipe B@sic); Frédérique Barloy-Hublercorresponding author (CNRS UMR 6026 , Equipe B@sic); |
| Short Abstract: To improve annotation accuracy and homogeneity we developed OxyGene a platform implementing a new annotation approach based on subsystems and ab-initio genome annotation using anchors. OxyGene improves the functional annotation of ROS-RNS detoxification subsystems in prokaryotic genomes by detecting forgotten loci and by simplifying, homogenizing and correcting functions description. |
| Long Abstract: Click Here |
| Poster I16 |
| Coiled coil genome annotation: prediction, structure, and evolutionary Past |
| Owen Rackham- University of Bristol |
| Julian Gough (University of Bristol, Computer Science); Martin Madera (University of Bristol, Computer Science); Dek Woolfson (University of Bristol, Biochemistry); |
| Short Abstract: We will present a novel approach to coiled coil prediction, the analysis of all genomes and the resulting Spiricoil database, and most importantly, the results of our evolutionary investigations based on this new resource. |
| Long Abstract: Click Here |
| Poster I17 |
| ENSEMBL ANNOTATION OF HUMAN GRCh37. Better algorithms for a better human. |
| Julio Fernandez Banet- Wellcome Trust Sanger Institute |
| Bronwen Aken (Wellcome Trust Sanger Institute, Vertebrate Genome Analysis); Susan Fairley (Wellcome Trust Sanger Institute, Vertebrate Genome Analysis); Magali Ruffier (Wellcome Trust Sanger Institute, Vertebrate Genome Analysis); Stephen Searle (Wellcome Trust Sanger Institute, Vertebrate Genome Analysis); Amy Tang (Wellcome Trust Sanger Institute, Vertebrate Genome Analysis); Jan-Hinnerk Vogel (Wellcome Trust Sanger Institute, Vertebrate Genome Analysis); Simon White (Wellcome Trust Sanger Institute, Vertebrate Genome Analysis); Amonida Zadissa (Wellcome Trust Sanger Institute, Vertebrate Genome Analysis); Michael Schuster (European Bioinformatics Institute, Panda Coordination and Outreach); |
| Short Abstract: After the release of the new human genome assembly in February 2009, EnsEMBL has created an annotation set introducing new methods developed recently.We present how these methods improved the consistency of our annotation set compared to the protein sets provided by RefSeq and SwissProt. |
| Long Abstract: Click Here |
| Poster I18 |
| HMMerThread Database: a resource for remotely conserved domains |
| Charles Bradshaw- MPI-CBG |
| Robert Henschel (TU-Dresden, ZIH); Matthias Mueller (TU-Dresden, ZIH); Bianca Habermann (Scionics c/o MPI-CBG, Bioinformatics); |
| Short Abstract: The HMMerThread Database combines structure and sequence based similarity searches to provide weakly conserved domains for 8 species along with the associated functional predictions within the twilight zone of sequence similarity. The domains are validated and are presented along with extensive annotation. 1,180 validated domains are found in human alone. |
| Long Abstract: Click Here |
| Poster I19 |
| Annotating the Zebra Finch Genome |
| Susan Fairley- Wellcome Trust Sanger Institute |
| Bronwen Aken (Wellcome Trust Sanger Institute, Informatics); Julio Fernandez-Banet (Wellcome Trust Sanger Institute, Informatics); Magali Ruffier (Wellcome Trust Sanger Institute, Informatics); Amy Tang (Wellcome Trust Sanger Institute, Informatics); Jan-Hinnerk Vogel (Wellcome Trust Sanger Institute, Informatics); Simon White (Wellcome Trust Sanger Institute, Informatics); Amonida Zadissa (Wellcome Trust Sanger Institute, Informatics); Steve Searle (Wellcome Trust Sanger Institute, Informatics); Tim Hubbard (Wellcome Trust Sanger Institute, Informatics); |
| Short Abstract: Assembly taeGut3.2.4 is the first public release of the 6x coverage Taeniopygia guttata (zebra finch) genome. It was annotated using a variant of the Ensembl genebuild pipeline. The resulting annotation includes 17,148 protein coding genes and 398 pseudogenes, along with other genomic features. This annotation is available at www.ensembl.org. |
| Long Abstract: Click Here |
| Poster I20 |
| Analysis of automatic gene annotation of low coverage genome assemblies in Ensembl |
| Amonida Zadissa- Wellcome Trust Sanger Institute |
| Bronwen Aken (Wellcome Trust Sanger Institute, Informatics); Susan Fairley (Wellcome Trust Sanger Institute, Informatics); Juilo Fernandez-Banet (Wellcome Trust Sanger Institute, Informatics); Magali Ruffier (Wellcome Trust Sanger Institute, Informatics); Amy Tang (Wellcome Trust Sanger Institute, Informatics); Jan Vogel (Wellcome Trust Sanger Institute, Informatics); Simon White (Wellcome Trust Sanger Institute, Informatics); Val Curwen (Wellcome Trust Sanger Institute, Informatics); Tim Hubbard (Wellcome Trust Sanger Institute, Informatics); Steve Searle (Wellcome Trust Sanger Institute, Informatics); |
| Short Abstract: The standard evidence-based Ensembl annotation pipeline is not suitable for annotating low coverage (2x) genomes because of the highly fragmented nature of the assemblies. We present this highly automated method for producing gene annotation and analyse its application on 21 low coverage genome assemblies, using the cat genome as example. |
| Long Abstract: Click Here |
| Poster I21 |
| Large duplications in the human genome reveal details of pseudogene formation |
| Ekta Khurana- Yale University |
| Hugo Lam (Yale University, Program in Computational Biology and Bioinformatics); Chao Cheng (Yale University, Molecular Biophysics and Biochemistry); Mark Gerstein (Yale University, Molecular Biophysics and Biochemistry); |
| Short Abstract: We have performed a detailed analysis of pseudogenes (?genes) present in large duplicated regions of the human genome. Comparisons of the substitution rates of a ?gene and its parent gene with the larger duplicated segments that contain them reveal details about the origin and time of ?gene formation. |
| Long Abstract: Click Here |
| Poster I22 |
| An integrative approach to support phenotype-genotype research on bioenergy crops |
| Keywan Hassani-Pak- Rothamsted Research |
| Shao Chih Kuo (Rothamsted Research, Mathematical and Computational Biology ); Jan Taubert (Rothamsted Research, Mathematical and Computational Biology ); Steve Hanley (Rothamsted Research, Bioenergy and Climate Change ); Chris Rawlings (Rothamsted Research, Mathematical and Computational Biology ); |
| Short Abstract: The functional annotation of genomes is still a major challenge in bioinformatics. We are developing methods for automated genome annotation and systematic QTL analysis using the Ondex system. Our methods will be used to annotate the poplar genome and identify candidate genes to improve bioenergy production for willow. |
| Long Abstract: Click Here |
| Poster J01 |
| Towards investigation of the evolution of nitrogen fixation using condensed matrix method and probing for the unit of selection |
| Arnab Sen- University of North Bengal |
| Saubashya Sur (University of North Bengal, NBU Bioinformatics Facility); Asim Bothra (Raiganj College, Chemistry); Uttam Mondal (Raiganj College, Chemistry); |
| Short Abstract: Evolution of nitrogen fixation has been investigated using condensed matrix method. Findings support polyphyly and lateral gene transfer. Mutation and selection occur at different intensities. nif genes did not evolve as a unit. Positive Darwinian selection controls nif D genes while purifying selection influences nif H and nif K. |
| Long Abstract: Click Here |
| Poster J02 |
| Computational Prediction of Genes Regulated by LEC1, LEC2, and WRI1 in Oil Seed Plants |
| Alain Tchagang- National Research Council Canada |
| Hugo Bérubé (National Research Council Canada, Knowledge Discovery Group, Institute for Information Technology); Fazel Famili (National Research Council Canada, Knowledge Discovery Group, Institute for Information Technology); Youlian Pan (National Research Council Canada, Knowledge Discovery Group, Institute for Information Technology); |
| Short Abstract: We present a data mining approach for predicting genes that may be regulated by one of the transcription factors, LEC1, LEC2, and WRI1 in Arabidopsis thaliana. This leads to discovery of potential new components in the gene networks controlling fatty acid metabolism and to the potential improvement of oil production. |
| Long Abstract: Click Here |
| Poster J03 |
| Improved base calling for the Illumina Genome Analyzer using machine learning strategies |
| Martin Kircher- Max-Planck-Institute for evolutionary Anthropology |
| Udo Stenzel (Max-Planck-Institute for evolutionary Anthropology, Evolutionary Genetics/Bioinformatics); Janet Kelso (Max-Planck-Institute for evolutionary Anthropology, Evolutionary Genetics/Bioinformatics); |
| Short Abstract: Various approaches to base calling have been proposed for the Illumina high-throughput DNA sequencer, which are either limited in accuracy or too time consuming. We show that fast and accurate base calling can be performed without prior modeling of the sequencing chemistry. |
| Long Abstract: Click Here |
| Poster J04 |
| First steps towards Barley Genome Sequencing by second generation sequencing technologies |
| Marius Felder- Leibniz Institute for Age Research – Fritz Lipmann Institute (FLI) |
| Burkhard Steuernagel (Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genome Diversity Group); Daniela Schulte (Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Genome Diversity Group); Andreas Petzold (Institute for Age Research – Fritz Lipmann Institute (FLI), Jena, Genome Analysis Group); Heidrun Gundlach (Helmholtz Center Munich, Information Center for Protein Sequences); Uwe Scholz (Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Genome Diversity Group); Mihaela Martis (Helmholtz Center Munich, Information Center for Protein Sequences); Stefan Taudien (Institute for Age Research – Fritz Lipmann Institute (FLI), Jena, Genome Analysis Group); Hana Simková (Institute of Experimental Botany, Olomouc , Laboratory of Molecular Cytogenetics and Cytometry); Eva Hřibová (Institute of Experimental Botany, Olomouc , Laboratory of Molecular Cytogenetics and Cytometry); Andreas Graner (Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Genome Diversity Group); Jaroslav Dolezel (Institute of Experimental Botany, Olomouc, Laboratory of Molecular Cytogenetics and Cytometry); Klaus Mayer (Helmholtz Center Munich, Information Center for Protein Sequences); Matthias Platzer (Institute for Age Research – Fritz Lipmann Institute (FLI), Jena, Genome Analysis Group); Nils Stein (Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Genome Diversity Group); |
| Short Abstract: Within the GABI-BARLEX project we evaluate the efficiency to achieve part of genetic anchoring by high-throughput second generation sequencing of BAC clones. Towards this end, we combine the physical map construction by fingerprinted BAC libraries with massively parallel sequencing of barcoded BAC pools and sorted chromosomes. |
| Long Abstract: Click Here |
| Poster J05 |
| Populus DNA digestion with restriction endonucleases in silico |
| Viktor Tomilov- SibEnzyme Ltd |
| Elena Savchkova (SibEnzyme Ltd, ); Danila Gonchar (SibEnzyme Ltd, ); Murat Abdurashitov (SibEnzyme Ltd, ); Sergey Degtyarev (SibEnzyme Ltd, ); |
| Short Abstract: In this work we have performed in silico analysis of populus DNA digestion at recognition sequences of restriction enzymes. Theoretical data have been compared to experimental patterns of total populus DNA hydrolysis with respective restriction enzymes and the correspondence has been observed in the most cases. |
| Long Abstract: Click Here |
| Poster J06 |
| INCORPORATING EPIGENOMIC INFORMATION TO STUDY THE TRANSCRIPTIONAL REGULATION OF HUMAN MICRORNAS |
| Xiaowo Wang- Tsinghua University |
| Yu Liu (Tsinghua Univ., Automation); Michael Zhang (Cold Spring Harbor Laboratory, CSHL); Yanda Li (Tsinghua Univ., Automation); |
| Short Abstract: By incorporating the information of promoter predictions, histone modifications, DNAse I hypersensitive sites and comparative genomics, we conducted a systematic analysis of the cis-regulatory region of human miRNAs, and constructed a regulatory network between miRNAs and transcription factors. |
| Long Abstract: Click Here |
| Poster J07 |
| De novo assembly of short read sequence data using SASSY |
| Michael Imelfort- The University of Queensland |
| Daniel Marshall (Australian center for plant functional genomics, Bioinformatics); Chris Duran (Australian center for plant functional genomics, Bioinformatics); David Edwards (Australian center for plant functional genomics, Bioinformatics); Ping Zhang (Australian center for plant functional genomics, Bioinformatics); |
| Short Abstract: Second generation sequencing (SGS) technology will provide fast cheap genome sequencing. Most SGS projects have focussed on re-sequencing however the majority of organisms have no available reference sequence. We have developed novel algorithms for the de-novo assembly of short read sequence data and we have produced software which implements these algorithms. |
| Long Abstract: Click Here |
| Poster J08 |
| Evaluation of DNA intramolecular interactions for nucleosome positioning in yeast |
| Michael Fernandez- Kyushu Institute of Technology |
| Satoshi Fujii (Kyushu Institute of Technology (KIT), Department of Bioscience and Bioinformatics); Hidetoshi Kono (Japan Atomic Energy Agency, Computational Biology Group); Akinori Sarai (Kyushu Institute of Technology, Department of Bioscience and Bioinformatics); |
| Short Abstract: We calculated intramolecular interaction energies of DNA by threading DNA sequences around crystal structures of nucleosomes. The strength of the intramolecular energy oscillations at frequency ~10 bps for dinucleotides was in agreement with previous nucleosome models. The intramolecular energy calculated along yeast genome positively correlated with nucleosome positioning experimentally measured. |
| Long Abstract: Click Here |
| Poster J09 |
| Evolutionary histories of gene clusters in primate genomes |
| Tomas Vinar- Comenius University Bratislava |
| Brona Brejova (Comenius University Bratislava, Computer Science); Webb Miller (Penn State University, Center for Comparative Genomics and Bioinformatics ); Adam Siepel (Cornell University, Biological Statistics and Computational Biology); |
| Short Abstract: Complex gene clusters are hotspots of evolutionary innovation andcontain many biomedically important gene families. We propose thatthese clusters should be analyzed in the context of theirduplication histories. We show novel methods forreconstructing the duplication histories from genomic sequences ofmultiple species and use them to analyze several biomedicallyinteresting human gene clusters. |
| Long Abstract: Click Here |
| Poster J10 |
| The Mouse Genomes Project Pilot: Short-read sequencing and de novo assembly of chromosome 17 from two inbred mouse strains: A/J and CAST/EiJ |
| James Stalker- Wellcome Trust Sanger Institute |
| Ian Sudbery (WTSI, Mouse cancer group); Jared Simpson (WTSI, Informatics); Thomas Keane (WTSI, Informatics); Ian Jackson (MRC Human Genetics Unit, Molecular Genetics); Laura Reinholdt (Jackson Laboratory, Reproductive Genomics); Leah Rae Donahue (Jackson Laboratory, Genetic Resources); Steve Brown (MRC Harwell, Mammalian Genetics Unit); Jonathan Flint (Wellcome Trust Centre for Human Genetics , Neurogenetics & Psychiatric Genetics); Ewan Birney (EMBL-EBI, Informatics); Allan Bradley (WTSI, Mouse Genetics); Zemin Ning (WTSI, Informatics); Richard Durbin (WTSI, Genome Informatics); David Adams (WTSI, Mouse cancer group); |
| Short Abstract: The Mouse Genomes Project aims to sequence 17 inbred strains to generate complete maps of the nucleotide and structural variation, and ultimately de novo genome assemblies, of each strain. Here we present the pilot sequencing, analysis, and assembly of chromosome 17 from two strains: A/J (domesticus) and CAST/EiJ (castaneus). |
| Long Abstract: Click Here |
| Poster J11 |
| Bayesian multiple QTL approach for detecting completely imprinted QTL loci in outbred F2 families |
| Virpi Ahola- Univerisity of Helsinki |
| Johanna Vilkki (MTT Agrifood Research Finland, Biotechnoloy and food research); Mikko Sillanpää (University of Helsinki, Department of Mathematics and Statistics); |
| Short Abstract: The phenomenon called genomic imprinting leads to different expression of a particular allele depending on the parent from which it is inherited. We developed a Bayesian method for detecting imprinted QTL loci in outbred F2 families. The results suggest that the method can flexibly test complete paternal and maternal imprinting. |
| Long Abstract: Click Here |
| Poster J12 |
| Analysis of alternative splicing of 3'UTRs defines modules of functional motifs |
| Fabrizio Ferrè- Università Sapienza |
| Paolo Marcatili (Università Sapienza, Biochemical Sciences); Domenico Raimondo (Università Sapienza, Biochemical Sciences); |
| Short Abstract: The generation of alternative 3'UTRs regulates the fate of mRNAs, modulating the presence of motifs (e.g. miRNA binding sites). The distribution of motifs suggests the presence of regulatory modules in which different regulatory regions act in a concerted fashion to govern transcript processes such as translation efficiency, localization, and stability. |
| Long Abstract: Click Here |
| Poster J13 |
| In-Silico Analysis of Prospective African Strains of Algae for Bio-Diesel Production |
| Ijeoma Dike- Covenant University |
| Conrad Omonhinmin (covenant university, biological science); Ezekiel Adebiyi (covenant university, Computer and Information Sciences); Angela Eni (covenant university, biological science); Shalom Chinedu (covenant university, biological science); Frank Ibikunle (covenant university, Electrical and Information Engineering); Itunu Ekwejobi (covenant university, Computer and Information Sciences); Olubanke Ogulana (covenant university, biological science); |
| Short Abstract: The rise in fuel rates, projected depletion of oil reserves and mounting environmental pollution, indicates the need for alternate energy sources, of which algae is of priority. Through in-silico genetic analysis, establishment of optimum nutrient supply and environmental conditions, efficient and higher oil-storing capacity of algae will be triggered. |
| Long Abstract: Click Here |
| Poster J14 |
| Structure and functions study of human PMS2-related genes and products of their expression |
| Elena Shematorova- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences |
| Dmitry Shpakovski (Shemyakin-Ovchinnikov Institute Of Bioorganic Chemistry, Russian Academy of Science); George V. Shpakovski (Shemyakin-Ovchinnikov Institute Of Bioorganic Chemistry, Russian Academy of Science); |
| Short Abstract: Using bioinformatics and experimental approaches all main stages of the molecular evolution of PMS2-related sequences in the Primates lineage were deciphered and direct correlation between amplification and diversification of the PMS2-related genes and the main steps of the higher Primates evolution have been established. |
| Long Abstract: Click Here |
| Poster J15 |
| Integration of summary-level gene expression and genetic association data |
| Johan Rung- EMBL-EBI |
| Misha Kapushesky (EMBL - EBI, Microarray Informatics group); Maria Krestyaninova (EMBL - EBI, Microarray Informatics group); Alvis Brazma (EMBL - EBI, Microarray Informatics group); |
| Short Abstract: In genetical genomics, the aim is to discover regulatory mechanisms behind various sample conditions when both genotype and gene expression data have been measured. We present a method to integrate publicly available results from gene expression and genetic association studies to discover such effects even when measured on different samples. |
| Long Abstract: Click Here |
| Poster J16 |
| Explore human housekeeping genes with a manually-curated microarray database |
| Cheng-Wei Chang- National Tsing Hua University |
| Wei-Chung Cheng (National Tsing Hua University, Biomedical Engineering and Environmental Science); Chaang-Ray Chen (National Tsing Hua University, Biomedical Engineering and Environmental Science); Ming-Lung Tsai (National Tsing Hua University, Biomedical Engineering and Environmental Science); Ian C. Hsu (National Tsing Hua University, Biomedical Engineering and Environmental Science); |
| Short Abstract: We obtained HK gene lists using 1,714 Affymetrix microarray data of 28 normal human tissues, by analyzing the gene expression with both intensity and present call after raw data were uniformly normalized. Several selection criteria were adjusted to obtain various HK gene lists which were then analyzed by Gene Ontology. |
| Long Abstract: Click Here |
| Poster J17 |
| Transcript Quantification with RNA-Seq Data |
| Regina Bohnert- Friedrich Miescher Laboratory Of The Max Planck Society |
| Gunnar Rätsch (Friedrich Miescher Laboratory Of The Max Planck Society, Machine Learning in Biology); |
| Short Abstract: High-throughput sequencing technologies opens exciting new approaches to transcriptome profiling. For the important task of inferring transcript abundances from RNA-Seq data, we developed a new technique based on linear programming. Combined with ab initio gene finding, our method is also a powerful tool to reveal and quantify novel (alternative) transcripts. |
| Long Abstract: Click Here |
| Poster J18 |
| Data Structures and Compression Algorithms for High-Throughput Sequencing Technologies |
| Kenny Daily- University of California, Irvine |
| Pierre Baldi (University of California, Irvine, Department of Computer Science, Institute for Genomics and Bioinformatics, Department of Biological Chemistry); Xiaohui Xie (University of California, Irvine, Department of Computer Science, Institute for Genomics and Bioinformatics); Paul Rigor (University of California, Irvine, Department of Computer Science, Institute for Genomics and Bioinformatics); Scott Christley (University of California, Irvine, Department of Computer Science, Department of Mathematics); |
| Short Abstract: The amount of data produced by high throughput sequencing technologies creates significant challenges to store and share these data. We have developed new data structures and entropy coding algorithms for the efficient storage, retrieval, and transmission of the data with factors in the 10-400 range. |
| Long Abstract: Click Here |
| Poster J19 |
| DNA methylation status at CpG islands are characterized by histone codes |
| Inkyung Jung- Korea Advanced Institute Of Science And Technology |
| No additional authors |
| Short Abstract: We propose several plausible mechanisms for precise controlling of DNA methylation status at CpG islands. We utilized Bayesian network to construct regulatory network and found several meaningful relationships supported by previous studies. Based on those findings we predicted the status of methylation level at CpG islands with high accuracy. |
| Long Abstract: Click Here |
| Poster J20 |
| 2d Gaussian convolution identifies a network of co-operating DNA copy number losses. |
| Christiaan Klijn- Netherlands Cancer Institute |
| Jan Bot (Delft University of Technology, Information and Communication Theory); David Adams (Wellcome Trust Sanger Institute, Experimental Cancer Genetics); Marcel Reinders (Delft University of Technology, Information and Communication Theory); Lodewyk Wessels (Netherlands Cancer Institute, Molecular Biology); Jos Jonkers (Netherlands Cancer Institute, Molecular Biology); |
| Short Abstract: In order to develop cancer, multiple simultaneous mutations are necessary. We have analyzed copy number mutation data to find simultaneously occurring changes in the DNA of tumors. Using a genome-wide scoring framework we are able to identify known and novel interacting copy number changes that are related to cancer. |
| Long Abstract: Click Here |
| Poster J21 |
| Dynamics in genome organisation during cell differentiation |
| Wouter Meuleman- Netherlands Cancer Institute / Delft University of Technology |
| Daan Peric Hupkes (Netherlands Cancer Institute, Gene Regulation); Marcel Reinders (Delft University of Technology, Bioinformatics); Lodewyk Wessels (Netherlands Cancer Institute, Molecular Biology); Bas van Steensel (Netherlands Cancer Institute, Gene Regulation); |
| Short Abstract: Our data provide a genome-wide view on the spatial reorganisation of the mouse genome during differentiation. We quantify changes in organisation using a statistical test and find they often encompass exactly one gene, reflect cellular state and are strongly linked to changes in gene expression. |
| Long Abstract: Click Here |
| Poster J22 |
| Probing M. tuberculosis through transcriptomic data |
| Luke Yancy Jr- Morehouse College |
| Robert Riley (Broad Institute of MIT/Harvard, Computational Biology); Brian Weiner (Broad Institute of MIT/Harvard, Computational Biology); Bruce Birren (Broad Institute of MIT/Harvard, Computational Biology); |
| Short Abstract: Newly accessible gene expression data from Mycobacterium tuberculosis presents an opportunity to learn more about the biological basis of TB. Here, we applied both a biclustering, and a traditional clustering algorithm to Mtb expression data in hopes to eventually produce a global regulatory network for Mtb. |
| Long Abstract: Click Here |
| Poster J23 |
| Looking for chromosome spatial organization rules in microarray gene expression data |
| Teresa Szczepińska- Nencki Institute of Experimental Biology |
| No additional authors |
| Short Abstract: Evidence supports that the basic nuclear functions are structurally integrated. We have used the human data and rat hippocampi gene expression data to explore relations between gene expression and genomic context. We identified and functionally annotated statistically higher than random number of distant genomic clusters within co-expression clusters. |
| Long Abstract: Click Here |
| Poster J24 |
| ACT: Aggregation and Correlation Tool |
| Justin Jee- Yale |
| Joel Rozowsky (Yale, MBB); Robert Bjornson (Yale, CS); Guoneng Zhong (Yale, MBB); Zhengdong Zhang (Yale, MBB); Mark Gerstein (Yale, MBB); |
| Short Abstract: We have created a tool which facilitates the analysis of genomic signal data, such as ChIP-Seq, providing an aggregate signal profile across annotated positions (such as TSS’s) or calculates the correlation between a set of signal tracks as a means of determining their phylogenetic relationship. |
| Long Abstract: Click Here |
| Poster J25 |
| Cross Platform Data Integration applied to Ageing Studies |
| Erik van den Akker- Leiden University Medical Centre / Delft University of Technology |
| Bas Heijmans (Leiden University Medical Centre, Molecular Epidemiology); Marian Beekman (Leiden University Medical Centre, Molecular Epidemiology); Joost Kok (Leiden University Medical Centre, Molecular Epidemiology); Marcel Reinders (Delft University of Technology, Information and Communication Theory Group); Pieternella Slagboom (Leiden University Medical Centre, Molecular Epidemiology); |
| Short Abstract: Classical gene set enrichment tests can be improved by weighting gene contributions according to the amount of supporting evidence. We aim to develop a statistical framework which allows for both the incorporation of weights derived from gene network topology as well as additional experimental evidence. |
| Long Abstract: Click Here |
| Poster J26 |
| Prediction of Prokaryotic Transcription Units from Microarray Data Revisited |
| Ulrich Bodenhofer- Johannes Kepler University |
| Wilhelm Lichtberger (Johannes Kepler University, Institute of Bioinformatics); Frank Klawonn (University of Applied Sciences Braunschweig-Wolfenbuettel, Data Analysis and Pattern Recognition Lab); |
| Short Abstract: We propose a framework for inferring hypotheses about prokaryotic transcription units from expression microarray data. Upon summarization with the FARMS algorithm, support vector machines are employed to determine possible interrelations between genes using intergenic distances and a specifically designed correlation measure. The approach is validated on E.coli data. |
| Long Abstract: Click Here |
| Poster J27 |
| Identification of Mammalian Polyadenylation Sites Using Logistic Regression |
| Eric Ho- Rutgers University |
| Samuel Gunderson (Rutgers University, Molecular Biology & Biochemistry); |
| Short Abstract: Our goal is to identify less-understood polyadenylation cis-acting elements, and to predict polyA sites. Singular value decomposition is used to locate and identify putative cis-acting elements flanking polyA sites. These features are incorporated into our logistic regression classifier. Sensitivity-specificity assessment has shown that our classifier achieves greater than 90% in performance. |
| Long Abstract: Click Here |
| Poster J28 |
| Detecting Copy Number Variation With Ultra Short Reads |
| Paul Medvedev- University of Toronto |
| Michael Brudno (University of Toronto, Computer Science); Marc Fiume (University of Toronto, Computer Science); Seunghak Lee (University of Toronto, Computer Science); Tim Smith (University of Toronto, Computer Science); Adrian Dalca (University of Toronto, Computer Science); |
| Short Abstract: We develop a paired-end mapping method that combines depth-of-coverage information with a novel interpretation of matepair information to detect CNVs with ultra-short NGS reads. We use our method to detect CNVs within an individual, making a total of 9909 calls. |
| Long Abstract: Click Here |
| Poster J29 |
| Function-based analysis of microarray data via l1-l2 regularization |
| Tiziana Sanavia- University of Padua |
| Annalisa Barla (University of Genova, Department of Computer and Information Science); Barbara Di Camillo (University of Padua, Department of Information Engineering); Sofia Mosci (University of Genova, Department of Computer and Information Science); Gianna Toffolo (University of Padua, Department of Information Engineering); |
| Short Abstract: A method is presented to integrate functional annotation with feature selection based on l1-l2 double optimization in microarray high-throughput studies. Our approach is able to increase the biological interpretability of gene signatures by defining subsets of genes annotated with groups of GO terms with similar functional meaning. |
| Long Abstract: Click Here |
| Poster J30 |
| PeakSeq: Systematic Scoring of ChIP-Seq Experiments Relative to Controls |
| Joel Rozowsky- Yale University |
| ghia Euskirchen (Yale, MCDB); Raymond Auerbach (Yale, CBB); zhengdong zhang (Yale, MBB); Theodore Gibson (Yale, MBB); Robert Bjornson (Yale, CS); Nicholas Carriero (Yale, CS); Michael Snyder (Yale, MCDB); Mark Gerstein (Yale, CBB); |
| Short Abstract: We develop a methodology for analyzing ChIP-seq data. Our method use a two-pass approach to identify potential target binding sites compensating for variability in genomic mappability, and then to filter these regions in order to identify sites that are significantly enriched compared to an appropriately normalized control sample. |
| Long Abstract: Click Here |
| Poster J31 |
| Development of a new Fungal Model, Holleya Sinecauda, by Paired End Solexa Sequencing |
| Pankaj Agarwal- Duke University |
| Fred Dietrich (Duke University, Department of Molecular Genetics and Microbiology); |
| Short Abstract: Development of a new fungal model, Holleya Sinecauda, using data from paired end Solexa sequencing, is presented. The sequencing data was assembled and the resulting contigs were analyzed computationally to characterize this organism. Results from this work and future experimental and computational work to further characterize the organism are presented. |
| Long Abstract: Click Here |
| Poster J32 |
| Data Structures and Compression Algorithms for High-Throughput Sequencing Technologies |
| Kenny Daily- University of California, Irvine |
| Xiaohui Xie (University of California, Irvine, Department of Computer Science, Institute for Genomics and Bioinformatics); Paul Rigor (University of California, Irvine, Department of Computer Science, Institute for Genomics and Bioinformatics); Pierre Baldi (University of California, Irvine, Department of Computer Science, Institute for Genomics and Bioinformatics, Department of Biological Chemistry); Scott Christley (University of California, Irvine, Department of Computer Science, Department of Mathematics); |
| Short Abstract: HTS technologies are driving profound, revolutionary, changes in biology and medicine, while generating massive amounts of data. We have developed new data structures and entropy coding algorithms for the efficient storage, retrieval, and transmission of the data with compression factors in the 10-400 range. |
| Long Abstract: Click Here |
| Poster J33 |
| Whole Genome Sequencing of a Glioblastoma Multiforme Cell Line |
| Brian O'Connor- UCLA |
| Michael Clark (UCLA, Human Genetics); Nils Homer (UCLA, Human Genetics); Hane Lee (UCLA, Human Genetics); Barry Merriman (UCLA, Human Genetics); Zugen Chen (UCLA, Human Genetics); Stanley Nelson (UCLA, Human Genetics); |
| Short Abstract: Due to its morbidity, understanding glioblastoma multiforme (GBM) genetic etiology is of great interest. Here we report the full genome sequencing of U87MG, a well-studied GBM cell line. Greater than 25x average genomic coverage was generated using the ABI SOLiD Sequencer platform and a novel 50 base paired end strategy. |
| Long Abstract: Click Here |
| Poster K1 |
| THE SPANISH NATIONAL BIONFORMATICS INSTITUTE |
| THE SPANISH NATIONAL BIONFORMATICS INSTITUTE INB- CNIO |
| No additional authors |
| Short Abstract: THE SPANISH NATIONAL BIONFORMATICS INSTITUTEThe INB (Spanish National Bioinformatics Institute, www.inab.org) is a technical platform of Genoma España, a Public Fundation for the development of Genomic an Proteomic research in Spain (www.gen-es.org/) The INB is organized in 9 specialized nodes including a partnership with the Barcelona Supercomputing Centre (www.bsc.org). During the five years it has |
| Long Abstract: Click Here |
| Poster L01 |
| Finding Protein Sequence Signatures from Protein-Protein Interaction Data Using Gene Ontology Annotations |
| Osamu Maruyama- Kyushu University |
| Hideki Hirakawa (Kyushu University, Faculty of Agriculture); Takao Iwayanagi (National Institute of Genetics, Center for Information Biology and DNA Data Bank of Japan); Yoshiko Ishida (Hitachi, Ltd., Central Research Laboratory); Shizu Takeda (Hitachi, Ltd., Central Research Laboratory); Jun Otomo (Hitachi, Ltd., Central Research Laboratory); Satoru Kuhara (Kyushu University, Graduate School of Genetic Resources Technology); |
| Short Abstract: We propose a method for predicting protein sequence signatures ofinteracting partners with a particular protein called a host proteinusing gene ontology annotations. The method can also simultaneouslyfind potential interacting partners with host proteins.Our method was applied to our original human PPI data set. |
| Long Abstract: Click Here |
| Poster L02 |
| Discovering the carbohydrate binding properties of PA-1L lectin from Pseudomonas aeruginosa by molecular modeling |
| Alessandra Nurisso- CNRS |
| Anne Imberty (CNRS, CERMAV); |
| Short Abstract: Pseudomonas aeruginosa is a human pathogen whose virulence is based on the capability of adhesion to the surface of host cells through the production of two carbohydrate binding proteins, PA-1L and PA-IIL. In this work, the molecular bases of the carbohydrate–PA-IL interactions are elucidated through molecular mechanics techniques. |
| Long Abstract: Click Here |
| Poster L03 |
| NASCENT: An Automatic Protein Interaction Network Generation Tool for Non-Model Organisms |
| Dániel Bánky- Eötvös University |
| Vince Grolmusz (Eötvös University, Protein Information Technology Group); |
| Short Abstract: NASCENT is a tool capable of constructing protein-protein interaction networks for any chosen non-model organisms. Calculations are based on a model organism protein-protein interaction data, retrieved from several major biological databases. The mapping of the interactions is performed by corresponding the genes of the expressed proteins of the two species. |
| Long Abstract: Click Here |
| Poster L04 |
| PINA: an integrated network analysis platform for protein-protein interactions |
| Jianmin Wu- University of Helsinki |
| Tea Vallenius (University of Helsinki, Genome-Scale Biology Program and Institute of Biomedicine); Kristian Ovaska (University of Helsinki, Genome-Scale Biology Program and Institute of Biomedicine); Jukka Westermarck (University of Tampere and Tampere University Hospital, Institute of Medical Technology); Tomi Mäkelä (University of Helsinki, Genome-Scale Biology Program and Institute of Biomedicine); Sampsa Hautaniemi (University of Helsinki, Genome-Scale Biology Program and Institute of Biomedicine); |
| Short Abstract: We introduce a web-based Protein Interaction Network Analysis platform (PINA), which integrates protein-protein interaction data from six databases and provides network construction, filtering, analysis, and visualization tools. Its advantages have been demonstrated in analysis of two human PPI networks. PINA is freely available at http://csbi.ltdk.helsinki.fi/pina/. |
| Long Abstract: Click Here |
| Poster L05 |
| XIPPI: a merged database of protein-protein interactions |
| Yuri Vyatkin- Institute of Cytology and Genetics SB RAS |
| Dmitry Afonnikov (Institute of Cytology and Genetics, Laboratory of Theoretical Genetics); |
| Short Abstract: The information about protein-protein interactions spreads over a number of databases with different data formats, interaction descriptions and protein sequence referencing. We suggest a tool XIPPI to overcome a problem of protein sequence redundancy in PPI databases. The XIPPI allows searching for interactions available and building datasets of protein interactions. |
| Long Abstract: Click Here |
| Poster L06 |
| Analysis of Biomolecular Network in Structurome |
| Akinori Sarai- Kyushu Institute of Technology |
| Mitsuaki Ohtsuaka (KIT, Biosci. Bioinfo.); Satoshi Fujii (KIT, Biosci. Bioinfo.); |
| Short Abstract: We have developed a database/tool of biomolecular network, PDBnet, based on the structural information of structurome. PDBnet enables us to extract and visualize various kinds of information from the structurome. We have analyzed the relationship among various molecular, evolutionary and network properties, in a systematic way by using PDBnet. |
| Long Abstract: Click Here |
| Poster L07 |
| Identification of Computational Hot Spots in Protein Interfaces Using Solvent Accessibility and Inter-Residue Potentials |
| Nurcan Tuncbag- Koc University |
| Attila Gursoy (Koc University, Center for Computationa Biology and Bioinformatics and College of Engineering); Ozlem Keskin (Koc University, Center for Computationa Biology and Bioinformatics and College of Engineering); |
| Short Abstract: Hot spots are residues comprising only a small fraction of interfaces yet accounting for the majority of the binding energy. Here, we present a new efficient method to determine computational hot spots based on solvent accessibility and statistical pairwise potentials of the interface residues. Our method reaches 70% accuracy. |
| Long Abstract: Click Here |
| Poster L08 |
| Effective atomic interactions for the characterization of protein-ligand binding interfaces |
| Alex Slater- Pontificia Universidad Católica de Chile |
| Francisco Melo (Pontificia Universidad Católica de Chile, Genética Molecular y Microbiología); Evandro Ferrada (University of Zurich, Department of Biochemistry); |
| Short Abstract: We describe a method to classify intermolecular interfaces using effective atomic interactions, and tested on 372 ATP-protein complexes. We found a high diversity in binding modes and illustrate specific cases where ligands in same conformation bind proteins with different interfaces, and also give examples where ligands in different conformations bind proteins with the same conformation. |
| Long Abstract: Click Here |
| Poster L09 |
| Identifying genetic interactions with sparse hidden factors |
| Leopold Parts- Wellcome Trust Sanger Institute |
| Oliver Stegle (University of Cambridge, Cavendish Laboratory); John Winn (Microsoft Research, Cambridge); Richard Durbin (Wellcome Trust Sanger Institute, ); |
| Short Abstract: We present a method for learning sparse, biologically informed hidden factors, and include them in a genetic interaction model.For the first time, we find biologically meaningful interactions between genotype and hidden determinants of gene expression, complementing and extending established results. |
| Long Abstract: Click Here |
| Poster L11 |
| Re-examining the connection between the network topology and essentiality |
| Elena Zotenko- Max-Planck Institute fuer Informatiks |
| Julian Mestre (Max Planck Institute for Informatics, Algorithms and Computational Complexity); Dianne O'Leary (University of Maryland, College Park, Computer Science Department); Teresa Przytycka (National Institutes of Health, National Center for Biotechnology Information); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster L12 |
| Determinants of interaction specificity in the plant MADS transcription factor network |
| Aalt-Jan Van Dijk- PRI, Wageningen University And Research Centre |
| Roeland van Ham (PRI, Wageningen UR, Applied Bioinformatics); Richard Immink (PRI, Wageningen UR, Plant Developmental Systems); Gerco Angenent (PRI, Wageningen UR, Plant Developmental Systems); |
| Short Abstract: We obtain sequence-level determinants of protein interaction specificity for the Arabidopsis MADS proteins, which are involved in a wide range of important developmental processes (e.g. floral organ formation). Our predictions were experimentally validated using site-specific mutagenesis and yeast-two-hybrid screening. Not only loss-of-function was observed, but also more revealing gain-of-function. |
| Long Abstract: Click Here |
| Poster L13 |
| Discovery of correlated motifs in large protein-protein interaction networks |
| Peter Boyen- Hasselt University |
| Aalt-Jan Van Dijk (Wageningen UR, Applied Bioinformatics); Dries Van Dyck (Hasselt University, WNI); Roeland van Ham (Wageningen UR, Applied Bioinformatics); Frank Neven (Hasselt University, WNI); |
| Short Abstract: We present a local search algorithm to identify correlated motif pairs. We validate the algorithm both on artificial and biological datasets. Our predicted interaction motifs are overrepresented at protein interaction surfaces. For the first time we present the application of correlated motif search on large-scale interaction networks. |
| Long Abstract: Click Here |
| Poster L14 |
| Computational prediction of small non-coding RNA targets in bacteria |
| Andreas Richter- University of Freiburg |
| Anke Busch (University of Leipzig, Department of Computer Science); Rolf Backofen (University of Freiburg, Department of Computer Science); |
| Short Abstract: We present a general energy-based approach, IntaRNA, to the prediction of RNA-RNA interactions incorporating both interaction site accessibility and existence of an interaction seed. Its performance has been demonstrated on prediction of bacterial sRNA targets. We also successfully predicted the regulatory outcome of the sRNA-mRNA interaction on translation initiation. |
| Long Abstract: Click Here |
| Poster L15 |
| Increasing the reliability and coverage of protein-protein interaction data from tandem affinity purification experiments. |
| James Vlasblom- University of Toronto |
| Shuye Pu (Hospital for Sick Children, Molecular structure and function program); Shoshana Wodak (Hospital for Sick Children, Molecular Structure and Function program); |
| Short Abstract: High throughput purification methods are increasingly successful in identifying protein-protein interactions. However, to achieve acceptable accuracy, many of the observed interactions are discarded during data processing. Here, interactome coverage is extended by integrating additional biological evidence using supervised classification, and potentially novel protein complex components are identified with graph clustering. |
| Long Abstract: Click Here |
| Poster L16 |
| Classification and retrieval of protein interfaces based on interface similarity: Detecting homology and analogy in protein interactions |
| Dmitry Korkin- University of Missouri, Columbia |
| Nan Zhao (University of Missouri, Columbia, Informatics Institute and Dept. of Computer Science); Bin Pang (University of Missouri, Columbia, Informatics Institute and Dept. of Computer Science); Chi-Ren Shyu (University of Missouri, Columbia, Informatics Institute and Dept. of Computer Science); |
| Short Abstract: In this work, we (1) present a novel protein interface similarity measure, determined using a machine learning approach; (2) construct and compare two protein interface retrieval systems using the defined similarity; and (3) introduce a biologically sound hierarchical classification of protein interfaces applied to a set of ~2,800 protein-protein interactions. |
| Long Abstract: Click Here |
| Poster M01 |
| Discovering the Rules of Reversible Membrane Binding: A Machine Learning Protocol for identifying C1, C2, and PH Domain Properties. |
| Morten Källberg- University of Illinois |
| No additional authors |
| Short Abstract: We present a machine learning protocol for determining membrane-targeting properties achieving 85-90% accuracy in separating binding and non-binding domains within families. The developed model is represented as an interpretable tree of rules showing good agreement between statistically discovered binding properties and those reported in experimental work. |
| Long Abstract: Click Here |
| Poster M02 |
| A new kernel function for clinical data |
| Anneleen Daemen- KULeuven |
| Bart De Moor (KULeuven, ESAT-SCD); |
| Short Abstract: To fully exploit clinical information, appropriate modeling is required. We propose a new kernel function that distinguishes between continuous, ordinal and nominal variables. Evidently, a Least Squares Support Vector Machine based on this kernel function significantly outperformed the widely used linear kernel function when tested on three data sets. |
| Long Abstract: Click Here |
| Poster M03 |
| Identifying essential genes in metabolic networks of bacteria in silico |
| Rainer Koenig- IPMB |
| Kitiporn Plaimas (IPMB, University of Heidelberg, Bioinformatics); Roland Eils (DKFZ Heidelberg, TBI Bioinformatics); |
| Short Abstract: We have developed a machine learning algorithm that infers essential reactions in a metabolic network from the topology of the network and experimental data from genomic sequences and gene expression of the corresponding coding genes. With this we support and extend experiments of high throughput genome wide knock screens. |
| Long Abstract: Click Here |
| Poster M04 |
| Predicting Protein Subcellular Localization Using Abstract Sequential Features |
| Cornelia Caragea- Iowa State University |
| Adrian Silvescu (Yahoo! Labs, CA); Vasant Honavar (Iowa State University, Computer Science); |
| Short Abstract: We present an approach to predicting protein subcellular localization from amino acid sequences that exploits the complementary strengths of feature construction (constructing complex features from existing features) and feature abstraction (grouping similar features to generate more abstract features) or feature selection to adapt the data representation used by the learner. |
| Long Abstract: Click Here |
| Poster M05 |
| Kernel Alignment K-NN for the Identification of Human Cancer Samples using the Gene Expression Profiles |
| Manuel Martin-Merino- Universidad Pontificia de Salamanca |
| No additional authors |
| Short Abstract: kNN classifier has been applied to the identification of cancer samples with encouraging results. We present a new method to learn a linear combination of dissimilarities for the kNN classifier that is robust to overfitting and solves a semi-definite programming approach. Our algorithm outperforms otheralternatives in several cancer datasets. |
| Long Abstract: Click Here |
| Poster M06 |
| A Kernel PCA Biplot method applied to gene expression data |
| Ferran Reverter- Universitat de Barcelona |
| Esteban Vegas Lozano (Universitat de Barcelona, Dept. Estadística); |
| Short Abstract: We describe a computational graphical tool to visualize genes and samples. We develop a biplot technique based on kernel PCA. We analyze two genomic datasets. Results suggest that our technique is a useful tool to find genes that have a similar pattern of up/down regulation for the samples |
| Long Abstract: Click Here |
| Poster M07 |
| Automatic classification of P-type ATPases using Structured Logistic Regression |
| Poul Liboriussen- Aarhus University |
| Bjørn Panyella Pedersen (Aarhus University, Centre for Membrane Pumps in Cells and Disease (PUMPKIN)); Poul Nissen (Aarhus University, Centre for Membrane Pumps in Cells and Disease (PUMPKIN)); Christian Nørgaard Storm Pedersen (Aarhus University, Bioinformatics Research Center (BiRC)); |
| Short Abstract: P-type ATPases are a very large family of ATP-driven membrane pumps involved in transmembrane transport of charged substrates. We have constructed a classifier that can distinguish between the 11 subfamilies with high accuracy. The classified it applied to Swiss-Prot/TrEMBL, and finds 6.624 P-Type ATPases. |
| Long Abstract: Click Here |
| Poster M08 |
| Discovering biomarker panels in experiments with pooling or heterogeneous tissues |
| Dirk Repsilber- Research Institute for the Biology of Farm Animals |
| Anna Telaar (FBN Dummerstorf, Genetics and Biometry); Gerd Nürnberg (FBN Dummerstorf, Genetics and Biometry); |
| Short Abstract: A plethora of statistical learning approaches is being applied to find biomarkers and also true multivariate biomarker signatures. We show how pooling and tissue heterogeneity influence the possibility of detection of biomarker signatures and compare statistical learning algorithms with respect to robustness to these stumbling blocks of biomarker discovery. |
| Long Abstract: Click Here |
| Poster M09 |
| Combining evidence from ranked gene lists |
| Raivo Kolde- University of Tartu |
| Sven Laur (University of Tartu, Institute of Computer Science); Priit Adler (University of Tartu, Institute of Molecular and Cell Biology); Jaak Vilo (University of Tartu, Institute of Computer Science); |
| Short Abstract: We propose a strategy for combining evidence from ranked lists of genes. In addition to the ranking of genes, the algorithm assigns significance probability for each gene. The method can be applied in network reconstruction, meta-analysis of microarray studies, etc. |
| Long Abstract: Click Here |
| Poster M10 |
| Missing Value Imputation for Epistasis Maps |
| Colm Ryan- University College Dublin |
| Derek Greene (University College Dublin, School of Computer Science and Informatics); Nevan Krogan (University of California, San Francisco, Quantitiative Biology Institute); Gerard Cagney (University College Dublin, Conway Institute of Biomolecular and Biomedical Research); Pádraig Cunningham (University College Dublin, School of Computer Science and Informatics); |
| Short Abstract: We introduce the problem of missing value imputation for Epistasis miniarray profiles(E-MAPS) and show the results of adapting two existing techniques to address the problem. In doing so we highlight some unique aspects of the problem – the pairwise nature of the data and the high percentage of missing values. |
| Long Abstract: Click Here |
| Poster M11 |
| KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences |
| Sebastian Schultheiss- Friedrich Miescher Laboratory of the Max Planck Society |
| Wolfgang Busch (Duke University, Biology Department); Jan Lohmann (University of Heidelberg, Center for Organismal Studies); Oliver Kohlbacher (University of Tuebingen, Wilhelm Schickard Institute for Computer Science); Gunnar Raetsch (Friedrich Miescher Laboratory of the Max Planck Society, Machine Learning in Biology); |
| Short Abstract: We identify genes regulated by the same transcription factor by analyzing sets of co-expressed genes from microarrays. KIRMES infers all genes regulated by the same mechanism as the ones in the input set. KIRMES makes use of motif sampling and newly developed kernel methods for this task. |
| Long Abstract: Click Here |
| Poster M12 |
| Combining Support Vector Machines to predict novel angiogenesis genes |
| Kaur Alasoo- University of Tartu |
| Phaedra Agius (Memorial Sloan-Kettering Cancer Center, .); Jaak Vilo (Quretec Ltd, .); Hedi Peterson (Quretec Ltd, .); |
| Short Abstract: Angiogenesis is the natural process of growing new blood vessels in human body, that also plays an important role in cancer development. We have identified candidate genes based on 274 known angiogenesis genes using a new machine learning method employing Support Vector Machine (SVM) classification. |
| Long Abstract: Click Here |
| Poster M13 |
| Natural Kernel-Induced Bayesian Learning for Microarray Data Analysis |
| Leo Cheung- Loyola University Medical Center |
| Xin Zhao (Sanjole Inc., Computer Engineering); |
| Short Abstract: Incorporating a novel natural kernel building procedure under a general unifying Bayesian framework, we propose a Natural Kernel-Imbedded Gaussian Process (NKIGP) for microarray data analysis. Based on simulated and real data studies, NKIGP performed very well consistently in both linear and non-linear cases without the need of parameter tuning. |
| Long Abstract: Click Here |
| Poster M14 |
| Using support vector machines for the evaluation of computationally developed lipoxygenase structures |
| Aditya Jitta- University of Hyderabad |
| Aparoy P (University of Hyderabad, School of Life Sciences); Reddanna P (University of Hyderabad, School of Life Sciences); |
| Short Abstract: Lipoxygenases are a group of structurally related family of non-heme, iron-containing dioxygenases,the geometry and composition at metal binding site in 3D models of lipoxygenases is very important.Based on these features,a tool was developed using support vector machines to evaluatecomputationally developed lipoxygenase structures. |
| Long Abstract: Click Here |
| Poster M15 |
| I/NI-calls: a novel unsupervised feature selection criterion |
| Sepp Hochreiter - Johannes Kepler University Linz |
| Djork-Arné Clevert (Johannes Kepler University Linz, Institute of Bioinformatics); Willem Talloen (Johnson & Johnson Pharmaceutical Research & Development, Pharmaceutical Research & Development); Hinrich Göhlmann (Johnson & Johnson Pharmaceutical Research & Development, Pharmaceutical Research & Development); Sepp Hochreiter (Johannes Kepler University Linz, Institute of Bioinformatics); |
| Short Abstract: We propose a novel unsupervised gene selection criterion that is based on a probabilistic latent variable model that takes probe level information -- probe correlations that cannot be explained by noise -- into account to filter out inconsistent probe sets. |
| Long Abstract: Click Here |
| Poster M16 |
| An integrative pipeline for automated data analysis and gene function annotation for genome wide high content RNAi screening |
| Stephen Wong- Center for Biotechnology and Informatics, The Methodist Hospital |
| Xiaobo Zhou (Center for Biotechnology and Informatics, The Methodist Hospital, The Methodist Hospital Research Institute and Department of Radiology); |
| Short Abstract: We propose an integrated pipeline of automated data analysis for high-content screening of genome-wide RNA interference on Drosophila cell assays. Millions of cells are efficiently segmented, and previously un-scored phenotypes are identified. This image bioinformatics pipeline is especially helpful in predicting the roles of genes in complex biological processes. |
| Long Abstract: Click Here |
| Poster M17 |
| Computational Linguistic Analyses of Unknown Metagenome Sequences |
| Victor Seguritan- San Diego State University |
| Anca Segall (San Diego State University, Biology); Rob Edwards (San Diego State University, Computer Science); Forest Rohwer (San Diego State University, Biology); |
| Short Abstract: A method is needed to assign functions to unknown sequences which does not rely on sequence homology alone. The linguistic elements, syntax and semantics, of several model proteins will be used to assign functions to unknown metagenomes in a manner similar to the concept of understanding human language. |
| Long Abstract: Click Here |
| Poster M18 |
| Neural Network Pairwise Interaction Fields for protein model quality assessment |
| Alberto Jesus Martin- University College |
| Gianluca Pollastri (Complex and Adaptive Systems Laboratory, University College Dublin, School of Computer Science and Informatics); Alessandro Vullo (Complex and Adaptive Systems Laboratory, University College Dublin, School of Computer Science and Informatics); |
| Short Abstract: We present a new knowledge-based Model Quality Assessment Program (MQAP) at the residue level which evaluates single protein structure models. We use a tree representation of the C-alpha trace to train a novel Neural Network Pairwise Interaction Field (NN-PIF) to predict the global quality of a model. |
| Long Abstract: Click Here |
| Poster M19 |
| BayesCall: A model-based basecalling algorithm}{BayesCall: A model-based basecalling algorithm |
| Wei-Chun Kao- UC Berkeley |
| Kristian Stevens (UC Davis, Computer Science); Yun Song (UC Berkeley, EECS); |
| Short Abstract: A novel model-based basecalling algorithm BayesCall is introduced for the Illumina sequencing platform. This new approach significantly improves the accuracy over Illumina's basecaller Bustard. For the 76-cycle PhiX174 data from Genome Analyzer II, BayesCall improves Bustard's per-base error rate by about 47%. |
| Long Abstract: Click Here |
| Poster M20 |
| A Bayesian Monte Carlo Hidden Markov Model Approach to Transmembrane Protein Structure Prediction |
| Takashi Kaburagi- Waseda University |
| Takashi Matsumoto (Waseda University, Electrical Engineering and Bioscience); |
| Short Abstract: We present the preliminary results of a novel scheme for transmembrane protein structure prediction using a Bayesian hidden Markov model. We applied a Bayesian learning method via the Markov chain Monte Carlo (MCMC) sampling scheme to evaluate posterior distribution of Hidden Markov Model (HMM) parameters given the training data set. |
| Long Abstract: Click Here |
| Poster M21 |
| A method for analyzing gene expression profiles based on the underlying structures |
| Shigeto Seno- Dept. Bioinfo. Eng., Grad. Sch. Info. Sci. Tech., Osaka Univ. |
| Yoichi Takenaka (Graduate School of Information Science and Technology, Osaka University, Bioinfomatic Engineering); Hideo Matsuda (Graduate School of Information Science and Technology, Osaka University, Bioinfomatic Engineering); |
| Short Abstract: Clustering is a powerful tool for elucidating relationships among genes, and one of the first steps in analysis. Meanwhile choice of suitable method for a given dataset is still difficult. Our approach discovers the underlying structure of a gene expression profile and provides a more intuitive understanding. |
| Long Abstract: Click Here |
| Poster M22 |
| Monte Carlo-Based Bayesian Prediction of Gene Regulatory Networks with Zipf Distribution: Mouse Nuclear Receptor Superfamily |
| Haruka Miyachika- Waseda University |
| Yusuke Kitamura (Waseda University, Electrical Engineering and Bioscience); Tomomi Kimiwada (National Center of Neurology and Psychiatry, Neurosurgery); Jun Maruyama (Waseda University, Electrical Engineering and Bioscience); Takashi Kaburagi (Waseda University, Electrical Engineering and Bioscience); Takashi Matsumoto (Waseda University, Electrical Engineering and Bioscience); Keiji Wada (National Center of Neurology and Psychiatry, Neurosurgery); |
| Short Abstract: We present a Monte Carlo-based algorithm to predict gene regulatory network structure within a Bayesian framework. The algorithm assumes that prior distribution follows the Zipf law, and is implemented using the Exchange Monte Carlo method. We applied the algorithm to a mouse nuclear receptor superfamily. |
| Long Abstract: Click Here |
| Poster M23 |
| Improving the prediction of protein-protein interactions by combining different biological sources |
| Herman van Haagen- LUMC |
| Peter-Bram 't Hoen (LUMC, Human Genetics); Barend Mons (LUMC, Human Genetics); Martijn Schuemie (Erasmus MC, Biosemantics group); |
| Short Abstract: Protein-protein interactions (PPIs) can be predicted based on different databases. In this study we investigate if combining those databases increases prediction power. In addition we investigate if the combined system covers more PPIs that can be evaluated. First results are promising both on coverage and prediction improvement. |
| Long Abstract: Click Here |
| Poster M24 |
| Two-way Analysis of High-Dimensional Metabolomic Datasets |
| Ilkka Huopaniemi- Helsinki University of Technology |
| Tommi Suvitaival (Helsinki University of Technology, Department of Information and Computer Science); Janne Nikkilä (Helsinki University of Technology, Department of Information and Computer Science); Matej Oresic (VTT Technical Research Centre of Finland, Quantitative Biology and Bioinformatics); Samuel Kaski (Helsinki University of Technology, Department of Information and Computer Science); |
| Short Abstract: We present a Bayesian machine learning method for multivariate two-way ANOVA-type analysis ofhigh-dimensional, small sample-size metabolomic datasets. The method assumes clustered metabolites and presents confidence intervals of main and interaction up/down-regulation effects of the clusters. |
| Long Abstract: Click Here |
| Poster M25 |
| Prediction of antifreeze protein from protein sequence |
| Chin-Sheng Yu- Feng Chia University |
| No additional authors |
| Short Abstract: By overall screening in current databases, there are very few homologs of anti-freeze protein in any other species with similar protein sequence and structure identified. We present an approach to recognize AFP from protein sequence. For a nonredundant data set, the overall prediction accuracy reaches 88%. |
| Long Abstract: Click Here |
| Poster M26 |
| Bioinformatic analyses of mammalian 5'-UTR sequence properties of mRNAs predicts alternative translation initiation sites |
| Jill Wegrzyn- University of California at San Diego |
| Thomas Drudge (University of California at San Diego, Skaggs School of Pharmacy and Pharmaceutical Sciences); Farmarz Valafar (San Diego State University, Bioinformatics and Medical Informatics Research Center (BMIRC)); Vivian Hook (University of California at San Diego, Skaggs School of Pharmacy and Pharmaceutical Sciences); |
| Short Abstract: This study conducted a bioinformatic evaluation of the 5'-UTR of mammalian mRNA sequences. Machine learning techniques were applied for the classification and identification of non-AUG initiation sites in a group of mRNAs that have been experimentally demonstrated to utilize alternative sites for protein translation. |
| Long Abstract: Click Here |
| Poster M27 |
| Cognitive State Classification with Magnetoencephalography Data |
| andrej savol- University of Pittsburgh |
| No additional authors |
| Short Abstract: We train a Support Vector Machine (SVM) soft-margin classifier on magnetoencephalography (MEG) brain-activation trajectories generated by human subjects viewing 60 common nouns divided into 12 noun groups. Semantic groupings and sensor information content are addressed. |
| Long Abstract: Click Here |
| Poster M28 |
| The evaluation of common 1H-NMR metabolomics data preprocessing procedures reveals unanticipated side-effects |
| Tim De Meyer- Ghent University |
| Bjorn Van Gasse (Ghent University, Dept. Organic Chemistry); Davy Sinnaeve (Ghent University, Dept. Organic Chemistry); Sofie Bekaert (Ghent University, Dept. Molecular Biotechnology); José Martins (Ghent University, Dept. Organic Chemistry); Wim Van Criekinge (Ghent University, Dept. Molecular Biotechnology); |
| Short Abstract: 1H-NMR metabolomics provides a high-throughput methodology capable of acquiring high-resolution profiles of low-molecular weight metabolites. However, the complicated data-analysis forms a major drawback, requiring numerous data preprocessing procedures (particularly normalization, reduction and scaling steps). Here, we evaluate the most common procedures and demonstrate several unanticipated side-effects. |
| Long Abstract: Click Here |
| Poster N01 |
| iNNfovis: Neural Network Enhanced Information Visualization of High-Dimensional Microarray Data |
| Marjan Trutschl- Louisiana State University and Louisiana State University Health Sciences Center in Shreveport |
| Urska Cvek (Louisiana State University and Louisiana State University Health Sciences Center in Shreveport, Computer Science and Center for Molecular and Tumor Virology); John Clifford (Louisiana State University Health Sciences Center in Shreveport, Department of Biochemistry and Molecular Biology); Rona Scott (Louisiana State University Health Sciences Center in Shreveport, Department of Microbiology and Immunology); Evan Boswell (Louisiana State University in Shreveport, Department of Computer Science); Phillip Kilgore (Louisiana State University in Shreveport, Department of Computer Science); John Wessler (Louisiana State University in Shreveport, Department of Computer Science); Zanobia Syed (Louisiana State University Health Sciences Center in Shreveport, Department of Biochemistry and Molecular Biology); |
| Short Abstract: High-dimensional microarray data does not only create the need for the analysis of the data and interpretation of results, but also the need for the development of tools and methods that can handle such data. We present techniques that combine well-understood classic visualizations and neural-network algorithms, creating meaningful visual representations. |
| Long Abstract: Click Here |
| Poster N02 |
| Bayesian Gene Set Enrichment Analysis |
| David Rossell- IRB Barcelona |
| No additional authors |
| Short Abstract: We formulate a GSEA generalization within the Bayesian paradigm which provides extra flexibility in testing the right hypothesis and considering more than 2 biological states and 2 hypotheses,and delivers easy to interpret results.The framework is general and can be used with any Bayesian hypothesis-testing probability model. |
| Long Abstract: Click Here |
| Poster N03 |
| An evaluation framework for statistical tests on microarray data |
| Dominik Mertens- Center for Biotechnology |
| Michael Dondrup (Center for Biotechnology, Computational Genomics); Andrea Hueser (Center for Biotechnology, Genetics); Alexander Goesmann (Center for Biotechnology, Computational Genomics); |
| Short Abstract: Microarray experiments characteristically involve a small number of replicates causing unreliable estimates of the sample variance. We evaluate the performance of widely used statistical tests for generating ranked gene lists from two-channel direct comparisons for a variable number of replicates based on a highly replicative oligonucleotide microarray experiment. |
| Long Abstract: Click Here |
| Poster N04 |
| Gene expression analysis of oral tongue squamous cell carcinoma between different macroscopic appearances |
| Afsaneh Eslami- Tokyo Medical and Dental University |
| Mayuko Ishikawa (Tokyo Medical and Dental University, Department of Oral Restitution); Akiko Hatano (Tokyo Medical and Dental University, Information Center for Medical Sciences); Ken Miyaguchi (Tokyo Medical and Dental University, Information Center for Medical Sciences); Kaoru Mogushi (Tokyo Medical and Dental University, Information Center for Medical Sciences); Hiroshi Mizushima (Tokyo Medical and Dental University, Information Center for Medical Sciences); Hiroshi Watanabe (Tokyo Medical and Dental University, Department of Oral Restitution); Norihiko Okada (Tokyo Medical and Dental University, Department of Oral Restitution); Masahiko Miura (Tokyo Medical and Dental University, Department of Oral Restitution); Hitoshi Shibuya (Tokyo Medical and Dental University, Department of Head and Neck Reconstruction); Hiroshi Tanaka (Tokyo Medical and Dental University, Information Center for Medical Sciences); |
| Short Abstract: Oral tongue squamous cell carcinoma has different macroscopic appearances; superficial, exophytic and invasive types. We investigated gene expression related to distinction of three types by microarray. Different gene expression was found between invasive and superficial types. Results suggest that different macroscopic appearances may be related to unusual gene expression. |
| Long Abstract: Click Here |
| Poster N05 |
| A modified LOESS normalization applied to miRNA arrays: a comparative evaluation |
| Davide Risso- University of Padua |
| Maria Sofia Massa (University of Padua, Department of Statistical Sciences); Chiara Romualdi (University of Padua, Department of Biology); |
| Short Abstract: We propose a novel normalization (loessM) applied to microRNA arrays, based on loess algorithm, that scales data on the median expression values. LoessM is able to outperform other techniques in most experimental scenarios, giving the best results in term of specificity and sensitivity either on simulated and on real data. |
| Long Abstract: Click Here |
| Poster N06 |
| Time-resolved monitoring of the transcriptome of MCF-7 breast cancer cells during the emergence of cisplatin resistance |
| Martin Koch- University Bonn |
| Niels Eckstein (University Düsseldorf, Institute of Human Genetics and Anthropology); Norbert Brenner (Caesar, Neurosensorik); Hans-Dieter Royer (University Düsseldorf, Institute of Human Genetics and Anthropology); Michael Wiese (University Bonn, Pharmaceutical Chemistry); |
| Short Abstract: Cisplatin is an emerging new treatment modality of breast cancer, after failure of chemotherapy. Development of a resistant phenotype resembles a major obstacle in clinical cisplatin therapy. We monitored the gene expression of cisplatin treated MCF-7 cells. Microarray time series can resolve the development of a cisplatin resistant phenotype. |
| Long Abstract: Click Here |
| Poster N07 |
| Comparative analysis of mRNA isoforms features using statistical and learning methods |
| Murlidharan Nair- Indiana University South Bend |
| No additional authors |
| Short Abstract: mRNA isoforms reflect the integrated outcome of molecular regulation and is thus a more effective measure towards understanding the state of the cell. We have identified mRNA isoform features using statistical and recursive-SVM based feature selection methods. We address the question of understanding which features best represent class separation biologically. |
| Long Abstract: Click Here |
| Poster N08 |
| Integrating miRNAs and mRNAs data from microarray experiments. Testing the influence of miRNAs signatures into gene expression profiles. |
| David Gonzalez-Pisano- Spanish National Cancer Research Centre (CNIO) |
| Marcos Malumbres (Spanish National Cancer Research Centre (CNIO), Molecular Oncology); Miguel Angel Piris (Spanish National Cancer Research Centre (CNIO), Molecular Pathology); |
| Short Abstract: We introduce a new approach to determine statistically relevant relationships between microRNAs profiles and gene expression signatures integrating both types of microarray experiments. The results obtained by this approach were experimentally validated. |
| Long Abstract: Click Here |
| Poster N09 |
| Probabilistic Search for Relevant Microarray Experiments |
| Jose Caldas- Helsinki University of Technology |
| Nils Gehlenborg (European Bioinformatics Institute, Microarray Team); Ali Faisal (Helsinki University of Technology, Department of Information and Computer Science); Alvis Brazma (European Bioinformatics Institute, Microarray Team); Samuel Kaski (Helsinki University of Technology, Department of Information and Computer Science); |
| Short Abstract: Search for data sets in gene expression data repositories is commonly based on textual descriptions of the experimental setup. We introduce novel retrieval methods that incorporate the gene expression measurements into the search process in order to retrieve data sets in which similar biological processes are activated. |
| Long Abstract: Click Here |
| Poster N10 |
| METASIS: The mata-analysis tool for expression microarray |
| Mi-Kyung Lee- KyungHee University |
| YangSeok Kim (KyungHee University, Department of Physiology); JinHo Yoo (Yonsei University College of Medicine, Cancer Metastasis Research Center); |
| Short Abstract: We have developed meta-analysis software for expression array, METASIS. Many different types of expression array data can be used in METASIS such as Affymetrix, Illumina, Agilent, ABI and two-dye style. For the meta-analysis, t-based modeling, parametric approach, and rank product, non-parametric approach, were implemented in METASIS. |
| Long Abstract: Click Here |
| Poster N11 |
| A comparison of Affymetrix exon expression values when preprocessed with different library files |
| Lingjia Kong- Tampere University of Technology |
| Olli Yli-Harja (Tampere University of Technology, Department of Signal Processing); Reija Autio (Tampere University of Technology, Department of Signal Processing); |
| Short Abstract: The selection of the library files has an effect on the values of several exons and genes. In addition, this study may offer a reliable solution for the selection of suitable library files, and for the development of more advanced methods to be used in the exon expression data analysis. |
| Long Abstract: Click Here |
| Poster N12 |
| Filtering and Identifying non-reliable probes in Affymetrix GeneChip® platforms |
| Noura Chelbat- Johannes Kepler University |
| Ulrich Bodenhofer (Johannes Kepler University, Institute of Bioinformatics); Sepp Hochreiter (Johannes Kepler University, Institute of Bioinformatics); |
| Short Abstract: Non-reliable/bad probes of oligonucleotide microarrays fail to spot signals which are detected and by the majority of probes in a probe set. We predict “bad” probes from the nucleotide sequence using SVMs and spectrum kernels with accuracies between 60 and 75% where, surprisingly, the models generalize to other platforms. |
| Long Abstract: Click Here |
| Poster N13 |
| Characterization of gene-specific intrinsic expression patterns by global analysis of microarray data |
| Changsik Kim- Sookmyung Women's University |
| Jiwon Choi (Sookmyung Women's University, Department of Biological Sciences); Yanghee Jang (Sookmyung Women's University, Department of Biological Sciences); Sukjoon Yoon (Sookmyung Women's University, Department of Biological Sciences); |
| Short Abstract: We have developed a method to integrate heterogeneous microarray global data for physiome-wide analysis of gene-expression. We found that individual genes have unique levels of average expression and expressional variation in thousands of different tissues and experimental conditions. This feature was used to identify novel tissue (or disease)-selective gene expression. |
| Long Abstract: Click Here |
| Poster N14 |
| A database for meta-analysis of clinical microarray studies |
| Ian Hsu- National Tsing Hua University |
| Wei-Chung Cheng (National Tsing Hua University, Biomedical Engineering and Environmental Sciences); Min-Lung Tsai (National Tsing Hua University, Biomedical Engineering and Environmental Sciences); Chung-Wei Chang (National Tsing Hua University, Biomedical Engineering and Environmental Sciences); Ching_Lung Huang (National Tsing Hua University, Biomedical Engineering and Environmental Sciences); Chaang-Ray Chen (National Tsing Hua University, Biomedical Engineering and Environmental Sciences); Wun-Yi Shu (National Tsing Hua University, Statistics); Yi-Chun Lin (National Tsing Hua University, Statistics); Tzu-Hao Wang (Chang Gung Memorial Hospital and Chang Gung University, Obstetrics and Gynecology); Ji-Hong Hong (Chang Gung Memorial Hospital, Radiation Oncology); |
| Short Abstract: Features offered by this database can efficiently facilitate the searching and retrieval process to assure the reliability of human clinical microarray metadata. The database provides uniformly preprocessed data along with sets of QC metrics that can significantly improve the data quality and comparability of microarray data generated among different laboratories. |
| Long Abstract: Click Here |
| Poster N15 |
| Comparative analysis of gene expression across species |
| Ana Carolina Fierro Gutierrez- K.U. Leuven |
| Peyman Zarrineh (Katholieke Universiteit Leuven, Department of Microbial and Molecular system); Kristof Engelen (Katholieke Universiteit Leuven, Department of Microbial and Molecular system); Lieve Verlinden (Katholieke Universiteit Leuven, Laboratorium voor Experimentele Geneeskunde en Endocrinologie); Guy Eelen (Katholieke Universiteit Leuven, Laboratorium voor Experimentele Geneeskunde en Endocrinologie); Els Vanoirbeek (Katholieke Universiteit Leuven, Laboratorium voor Experimentele Geneeskunde en Endocrinologie); Annemieke Verstuyf (Katholieke Universiteit Leuven, Laboratorium voor Experimentele Geneeskunde en Endocrinologie); Kathleen Marchal (Katholieke Universiteit Leuven, Department of Microbial and Molecular system); |
| Short Abstract: In this study we compared the response to vitaminD in human and mouse based on gene coexpression derived from microarray experiments. By applying a differential clustering approach we get a better view on which gene expression changes are species-specific and which are conserved between human and mouse. |
| Long Abstract: Click Here |
| Poster N16 |
| TAFFEL: A Tool for Parts Based Analysis of Differentially Expressed Genes |
| Petri Pehkonen- University of Kuopio |
| Mitja Kurki (University of Kuopio, Department of Biosciences); Garry Wong (University of Kuopio, Department of Biosciences); Jussi Paananen (University of Kuopio, Department of Biosciences); Markus Storvik (University of Kuopio, Department of Biosciences); Mikael von und zu Fraunberg (Kuopio University Hospital, Department of Neurosurgery); Juha Jääskeläinen (Kuopio University Hospital, Department of Neurosurgery); |
| Short Abstract: We present a software tool TAFFEL that performs analysis of differentially expressed genes by finding co-regulated and co-functional gene sub groups and their internecine correlations. Analysis of data from forskolin treated human hepatocytes and ruptured saccular cerebral artery aneurysm reveal the key processes driven by different sets of regulatory proteins. |
| Long Abstract: Click Here |
| Poster N17 |
| A NEW MANIFOLD LEARNING APPROACH FOR ANALYSIS AND VISUALISATION OF DIFFERENTIAL GENE EXPRESSION |
| Jitender Cheema- John Innes Centre |
| Jo Dicks (John Innes Centre, Computational and System Biology); |
| Short Abstract: We present a new method to create, visualise and validate clusters of gene expression profiles. Our approach combines ideas from machine learning and graph partitioning (manifold Laplacian embedding) and, through a 3D visualisation process, allows the user to interact with their results, using their expert knowledge to refine them. |
| Long Abstract: Click Here |
| Poster N18 |
| Filtering low-signal probesets improves enrichment analysis in microarray studies |
| Krzysztof Goryca- Medical Center for Postgraduate Education and the Maria Skłodowska-Curie Memorial Cancer Center |
| Tymon Rubel (Maria Skłodowska-Curie Memorial Cancer Center, Department of Gastroenterology and Hepatology); Lucjan Wyrwicz (Maria Skłodowska-Curie Memorial Cancer Center, Department of Gastroenterology and Hepatology); |
| Short Abstract: Statistical techniques for analysis of microarrays data sets possess limitations related to low signal-to-noise ratio, especially for least abundant mRNAs. Here we report, that a simple procedure - filtering of genes with unfavorable signal-to-noise ratio in a given microarray experiment- can result in better functional description of microarray data. |
| Long Abstract: Click Here |
| Poster N19 |
| Bicluster-based meta-analysis of microarray data |
| Edward Curry- University of Edinburgh |
| Simon Tomlinson (University of Edinburgh, MRC Centre for Regenerative Medicine); |
| Short Abstract: We have developed a meta-analysis technique to identify, in large gene expression datasets, subsets of the data that facilitate prediction of different roles a gene or group of genes may have in different biological contexts. We demonstrate use of our approach on publicly available microarray data to explore observed effects in novel datasets. |
| Long Abstract: Click Here |
| Poster N20 |
| Clustering of Temporal Gene Expression Data Across Multiple Treatments with a Bayesian Nonparametric Mixture Model |
| Ana Paula Sales- Duke University |
| Thomas Kepler (Duke University, Biostatistics and Bioinformatics); Feng Feng (Duke University, Biostatistics and Bioinformatics); |
| Short Abstract: Time-course gene expression data from dendritic cells based on four distinct treatments is modeled with Gaussian processes and clustered with a Dirichlet process. This mixture model does not impose any parametric form for the time-trajectories nor requires specification of the number of clusters, inferring it from the data. |
| Long Abstract: Click Here |
| Poster N21 |
| Ecological Genomics: Construction of Molecular Pathways Responsible for Gene Regulation and Adaptation to Heavy Metal Stress in Arabidopsis thaliana and Raphanus sativus. |
| Lynda Villagomez- Loyola Marymount University |
| Tatiana Tatarinova (Loyola Marymount University, Mathematics); Gary Kuleck (Loyola Marymount University, Biology); |
| Short Abstract: Using Pathway Studio, we explored molecular pathways for heavy metal stress responsiveness in Arabidopsis thaliana and Raphanus sativus. We built a prototype response network in Arabidopsis. 8,059 ortholog pairs were identified between Raphanus and Arabidopsis (>95% match). The 50 best candidate genes in Raphanus were nominated for RT-PCR validation. |
| Long Abstract: Click Here |
| Poster N22 |
| Multi Experiment Matrix - Webtool for finding co-expressed genes over hundreds of datasets |
| Priit Adler- University of Tartu |
| Raivo Kolde (University of Tartu, Institute of Computer Science); Meelis Kull (University of Tartu, Institute of Computer Science); Aleksandr Tkatchenko (University of Tartu, Institute of Computer Science); Hedi Peterson (University of Tartu, Institute of Molecular and Cell Biology); Jüri Reimand (University of Tartu, Institute of Computer Science); Jaak Vilo (University of Tartu, Institute of Computer Science); |
| Short Abstract: We have developed a query engine atop of the microarray experiments from ArrayExpress that performs search for co-expressed genes over hundreds of datasets at a time. Given the query gene MEM finds a list of genes that have similar expression in many datasets. (MEM, http://biit.cs.ut.ee/mem) |
| Long Abstract: Click Here |
| Poster N23 |
| Chipster microarray data analysis software - new release with extended functionality |
| Eija Korpelainen- CSC - the Finnish IT Center for Science |
| Jarno Tuimala (CSC - IT Centre for Science, Software solutions); Aleksi Kallio (CSC - IT Centre for Science, Software engineering); Taavi Hupponen (CSC - IT Centre for Science, Software engineering); Petri Klemelä (CSC - IT Centre for Science, Software engineering); |
| Short Abstract: Chipster (http://chipster.csc.fi/) offers an intuitive GUI to a comprehensive collec¬tion of up-to-date microarray data analysis methods, such as those developed in the R/Bioconductor project. Chipster supports Affymetrix, Illumina, Agilent and cDNA arrays, and it is open source. The new release has many new analysis tools, visualizations and supported chip types. |
| Long Abstract: Click Here |
| Poster N24 |
| Gene Expression data Classification using Filter method and Discrete Wavelet Feature Selection |
| Ho Sun Shon- CBITRC, PTERC, Chungbuk National University |
| Dong Gyu Lee (CBITRC, PTERC, Chungbuk National University, Computer Sciencce); Keun Ho Ryu (CBITRC, PTERC, Chungbuk National University, Computer Sciencce); |
| Short Abstract: In this research, the gene selection method that well-reflects the characteristics of microarray data was applied. That is, the performance was compared and evaluated by using the Wavelet method applicable to the high-dimensional data through similar gene selection methods by making classifiers with the extracted genes and applying the test data set. |
| Long Abstract: Click Here |
| Poster N25 |
| Splicing prediction is dominated by gene expression changes |
| Axel Rasche- MPI for Molecular Genetics |
| Ralf Herwig (MPI for Molecular Genetics, Vertebrate Genomics); |
| Short Abstract: We present a systematic evaluation of available splicing prediction methods advancing the theoretical part of alternative splicing analysis. The compared methods focus on high-throughput screening methods. The evaluation shows a lack of performance for not differentially expressed genes. This is particularly interesting for the proposed coupling of transcription and splicing. |
| Long Abstract: Click Here |
| Poster N26 |
| High accuracy for Naïve Bayesian Tree classifying disease-associated copy number variation in mental retardation |
| Jayne Hehir-Kwa- Microarray Facility |
| Nienke Wieskamp (UMCN, Human Genetics); Caleb Webber (Oxford University, Functional Genomics); Christian Gilissen (UMCN, Human Genetics); Rolph Pfundt (UMCN, Human Genetics); Chris Ponting (Oxford University, Functional Genetics); Joris Veltman (UMCN, Human Genetics); |
| Short Abstract: We have discovered several structural and functional features that significantly differ between rare de novo CNVs associated with mental retardation (MR) and benign CNVs found in healthy individuals. We train a classifier with these features and achieve a high accuracy in a replication study with individuals suffering from unexplained MR. |
| Long Abstract: Click Here |
| Poster N27 |
| Microarray Analysis to investigate Mechanisms of Metabolic Syndrome |
| Tiffany Morris- University of Cambridge |
| Mark Vickers (University of Auckland, Liggins Institute); Peter Gluckman (University of Auckland, Liggins Institute); Stewart Gilmour (University of Cambridge, Pathology Department); Nabeel Affara (University of Cambridge, Pathology Department); |
| Short Abstract: Microarray was used to investigate the effects of neonatal leptin treatment on the metabolic phenotype of adult female offspring of undernourished mothers. Liver samples from eight treatment groups were hybridised to the Illumina array and R/bioconductor was used to analyse the results. |
| Long Abstract: Click Here |
| Poster N28 |
| Fusion of sequence data and microarray data, a systematic approach toward cross-species comparison |
| Peyman Zarrineh- Katholieke Universiteit Leuven |
| Carolina Fierro (Postdoc researcher, Department of Microbial and Molecular systems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 20, 3001 Leuven); Bart De Moor (Professor, Department of Electrical engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Leuven); Kathleen Marchal (Professor, Department of Microbial and Molecular systems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 20, 3001 Leuven); |
| Short Abstract: In this study functional conservation between bacterial species has been studied by utilizing a new methodology developed for cross-species comparison. This methodology combines microarray data and orthology data in an elaborated manner. |
| Long Abstract: Click Here |
| Poster N29 |
| Combining Semantic Relations from the Literature and DNA Microarray Data for Novel Hypotheses Generation |
| Dimitar Hristovski- University of Ljubljana, Medical Faculty |
| Andrej Kastrin (University Medical Centre, Institute of Medical Genetics); Borut Peterlin (University Medical Centre, Institute of Medical Genetics); Thomas Rindflesch (National Institutes of Health, National Library of Medicine); |
| Short Abstract: Although microarray experiments have great potential to support progress in biomedicine, results are not easy to interpret. We describe a method and an application that integrates semantic relations extracted from the literature with microarray results and show the benefits for interpretation of results and novel hypotheses generation. |
| Long Abstract: Click Here |
| Poster N30 |
| GeSETbench: Gene SET analysis workbench for microarray data |
| Jaeyoung Kim- Kyungpook National University |
| Miyoung Shin (Kyungpook National University, School of Electrical Engineering & Computer Science); |
| Short Abstract: GeSETbench is a gene-set analysis and visualization for identifying significant gene-sets in a parametric way and in a nonparametric way, based on two sample groups of gene expression data and biological resources. In particular, we consider distribution model of gene ranking scores produced by several different importance ranking methods. |
| Long Abstract: Click Here |
| Poster N31 |
| Robust Extraction of Functional Signals from Gene Set Analysis using a Generalized Threshold Free Scoring Function |
| Petri Törönen- Helsinki University |
| Pauli Ojala (Finnish Red Cross, research unit); pekka marttinen (University of Helsinki, Statistics department); liisa holm (Helsinki University, Institute of Biotechnology); |
| Short Abstract: We propose a new scoring function, Gene Set Z-score (GSZ), for threshold free gene set enrichment analysis. GSZ performs over-representation analysis that takes the actual differential expression scores into account. The method surpasses other scoring functions in artificial and real data comparisons. |
| Long Abstract: Click Here |
| Poster N32 |
| Improving differential expression detection using difference normalization |
| Marc Hulsman- Delft University of Technology |
| Anouk Leusink (University of Twente, Department of Tissue Regeneration); Eugene van Someren (Department of Applied Biology, Radboud Universiteit Nijmegen); Koen J. Dechering (Schering-Plough Research Institute, Department of Molecular Pharmacology); Jan de Boer (University of Twente, Department of Tissue Regeneration); Marcel J.T. Reinders (Delft University of Technology, Information and Communication Theory Group); |
| Short Abstract: Microarrays are particularly sensitive to experimental conditions, causing unwanted signal differences between arrays. These differences can be attributed to amplification, hybridization and array location effects. These technical effects are not adequately removed by existing methods. We propose a new normalization method, showing that it significantly improves differential expression detection. |
| Long Abstract: Click Here |
| Poster N33 |
| Sparse Factor Analysis for Detecting Copy Number Variations (CNVs) |
| Andreas Mitterecker- Johannes Kepler University Linz |
| Djork-Arné Clevert (Johannes Kepler University Linz, Institute of Bioinformatics); Andreas Mayr (Johannes Kepler University Linz, Institute of Bioinformatics); An De Bondt (Janssen Pharmaceutica, Johnson & Johnson Pharmaceutical Research & Development); Willem Talloen (Janssen Pharmaceutica, Johnson & Johnson Pharmaceutical Research & Development); Marianne Tuefferd (Janssen Pharmaceutica, Johnson & Johnson Pharmaceutical Research & Development); Hinrich Göhlmann (Janssen Pharmaceutica, Johnson & Johnson Pharmaceutical Research & Development); Sepp Hochreiter (Johannes Kepler University, Institute of Bioinformatics); |
| Short Abstract: Most reported CNVs affect less than three HapMap samples. We model these sparse CNVs by Laplace or multimodal distributions, where learning is based on variational and EM approaches. With Affymetrix SNP6 chips on the HapMap data we found novel CNVs. Moreover many known CNVs seem to be false positives. |
| Long Abstract: Click Here |
| Poster N34 |
| Construction of Metagenes by Conditional Factor Analysis |
| Andreas Mayr- Johannes Kepler University Linz |
| Djork-Arne Clevert (Johannes Kepler University Linz, Institute of Bioinformatics); Andreas Mitterecker (Johannes Kepler University Linz, Institute of Bioinformatics); An De Bondt (Janssen Pharmaceutica, Johnson & Johnson Pharmaceutical Research & Development); Willem Talloen (Janssen Pharmaceutica, Johnson & Johnson Pharmaceutical Research & Development); Hinrich Göhlmann (Janssen Pharmaceutica, Johnson & Johnson Pharmaceutical Research & Development); Sepp Hochreiter (Johannes Kepler University Linz, Institute of Bioinformatics); |
| Short Abstract: To combine microarray gene selections and to transfer gene signatures across platforms, we construct "metagenes" by conditional factor analysis. A hidden factor in expression values that is correlated to a chosen genes' expression value is its "metagene", where its variance is the hyperparameter determining robustness and number of included genes. |
| Long Abstract: Click Here |
| Poster N35 |
| Multivariate Methods for Genomic Data Integration and Visualization |
| Alex Sanchez- University of Barcelona |
| Francesc Carmona (University of Barcelona, Statistics); Ferran Reverter (University of Barcelona, Statistics); Esteban Vegas (University of Barcelona, Statistics); José Fernández-Real (Hospital Universitari de Girona, Diabetes, Endocrinología y Nutrición ); |
| Short Abstract: We discuss the application of two multivariate statistics approaches to integrate bio-molecular information: Multiple Factorial Analysis and Ecological Data Analysis, each combining several traditional or new multivariate statistical methods. The techniques are applied to an unpublished dataset consisting of three different data types: DGGE, microarrays and clinical variables. |
| Long Abstract: Click Here |
| Poster N36 |
| Visualization of Large Microarray Experiments with Space Maps |
| Nils Gehlenborg- European Bioinformatics Institute |
| Nils Gehlenborg (European Bioinformatics Institute, Microarray Team); Alvis Brazma (European Bioinformatics Institute, Microarray Team); |
| Short Abstract: Microarray studies that include a large number of samples have become increasingly common over the last few years. We present the Space Maps visualization technique, which can visualize data sets with hundreds or thousands of samples, a task at which state-of-the-art techniques such as heatmaps fail. |
| Long Abstract: Click Here |
| Poster O1 |
| Function-driven creation of protein families for phylogenomic analysis |
| Barbara Fenner- Norwich University |
| Mark Fenner (Norwich University, Computer Science); |
| Short Abstract: We manually craft protein families based on potential molecular functions. Functions are translated into GO terms and their relationships are formalized as a DAG. The DAG indexes into GOA and retrieves proteins to include in new families. These families are evaluated for use in automated function prediction. |
| Long Abstract: Click Here |
| Poster O2 |
| T-pattern analysis: detecting spike sequences which encode sensory information. |
| Anne Segonds-Pichon- The Babraham Institute |
| Alister Nicol (Babraham Institute, Laboratory of Cognitive & Behavioural Neuroscience); Keith Kendrick (Babraham Institute, Laboratory of Cognitive & Behavioural Neuroscience); Magnus Magnusson (University of Iceland, Human Behavior Laboratory); |
| Short Abstract: T-pattern analysis was applied to action potential data sampled from a microelectrode array to establish whether recurring spike sequences can be detected across multiple neurons in the rat olfactory bulb. Many sequences were detected, more during stimulus presentation than before, suggesting a functional role for such sequences in encoding information. |
| Long Abstract: Click Here |
| Poster O3 |
| A genomic search for molecular evolutionary correlates of regional neuronal connectivity in the mouse brain |
| Fred Davis- Howard Hughes Medical Institute |
| Sean Eddy (Howard Hughes Medical Institute, Janelia Farm Research Campus); |
| Short Abstract: The mammalian brain is organized into anatomical regions that are neuronally connected to form circuits. Here we assess the utility of spatial gene expression data and comparative genomics for identifying molecular evolutionary correlates of regional neuronal connectivity in the mouse brain. |
| Long Abstract: Click Here |
| Poster P1 |
| QBIOS: driving toward a trusted distributed bioinformatics service infrastructure |
| FRANCOIS MOREEWS- INRA /INRIA |
| No additional authors |
| Short Abstract: QBIOS is workflow web server dedicated to bioinformatics services that allows service test case creation and execution. QBIOS provides and shares indicators of quality of service that can be used to build community based service repositories, to create an efficient and reliable distributed bioinformatics service infrastructure. http://qbios.gforge.inria.fr/ |
| Long Abstract: Click Here |
| Poster P2 |
| The Neuro-Immune Gene Ontology: a subset of GO directed for neurological and immunological systems |
| Nophar Geifman- The Shraga Segal Dept. of Microbiology and Immunology AND The National Institute of Biotechnology in the Negev, Ben Gurion University |
| Alon Monsonego (Ben Gurion University , The Shraga Segal Dept. of Microbiology and Immunology AND The National Institute of Biotechnology in the Negev); Eitan Rubin (Ben Gurion University, The Shraga Segal Dept. of Microbiology and Immunology AND The National Institute of Biotechnology in the Negev); |
| Short Abstract: We propose a new approach for editing the gene ontology, which we call clipping, in which GO is edited according to biological relevance to specific domains. We demonstrate this approach by creating a Neuro-Immune Gene Ontology (NIGO) directed for neurological and immunological systems. |
| Long Abstract: Click Here |
| Poster P3 |
| Informatics obstacles for integrating evolutionary phenotype diversity with model organism data |
| Hilmar Lapp- National Evolutionary Synthesis Center (NESCent) |
| James Balhoff (US National Evolutionary Synthesis Center, ); Cartik Kothari (US National Evolutionary Synthesis Center, ); Todd Vision (University of North Carolina, Biology); Wasila Dahdul (University of South Dakota, Biology); Paula Mabee (University of South Dakota, Biology); John Lundberg (Academy of Natural Sciences, ); Peter Midford (University of Kansas, Biology); Monte Westerfield (University of Oregon, Biology); |
| Short Abstract: We illustrate the tools, databases, user-interfaces, and semantic data processing we developed to transform the traditionally free-text comparative morphological character descriptions to the same ontology-based formal phenotype assertions employed by the model organism community. The resulting knowledge base integrates across mutant phenotype data for model organisms and evolutionary phenotype diversity. |
| Long Abstract: Click Here |
| Poster P4 |
| BioPortal: Ontologies and Integrated Data Resources at the Click of a Mouse |
| Patricia Whetzel- Stanford University |
| Natalya F. Noy (Stanford University, Stanford Center for Biomedical Informatics Research); Nigam H. Shah (Stanford University, Stanford Center for Biomedical Informatics Research); Benjamin Dai (Stanford University, Stanford Center for Biomedical Informatics Research); Michael Dorf (Stanford University, Stanford Center for Biomedical Informatics Research); Nicholas Griffith (Stanford University, Stanford Center for Biomedical Informatics Research); Clement Jonquet (Stanford University, Stanford Center for Biomedical Informatics Research); Daniel L. Rubin (Stanford University, Stanford Center for Biomedical Informatics Research); Cherie Youn (Stanford University, Stanford Center for Biomedical Informatics Research); Mark A. Musen (Stanford University, Stanford Center for Biomedical Informatics Research); |
| Short Abstract: BioPortal (http://bioportal.bioontology.org) is an open repository of biomedical ontologies that provides programmatic and web-based access to ontologies developed in OBO, OWL, Protégé frames, and RDF. Features include browsing, searching, and visualization of ontologies. Searching of integrated data resources is also possible through ontology-based indexing of biomedical resources with BioPortal ontologies. |
| Long Abstract: Click Here |
| Poster P5 |
| Semi-Supervised Clustering Based on the Distance between Gene Pairs in Gene Ontology |
| Dae-Won Kim- Chung-Ang University |
| Song Ko (Chung-Ang University, Computer Science and Engineering); Bo-Yeong Kang (Seoul National University, Dentistry); |
| Short Abstract: Comparative studies using the distance between gene pairs in Gene Ontology for semi-supervised clustering were explored. Here we applied three types of distance measure, Gene Ontology, and data set, respectively, which can provide more practical and general information about utilizing the gene distances for clustering as a prior knowledge. |
| Long Abstract: Click Here |
| Poster P6 |
| Redundancy Elimination and Visualization of Gene Ontology Term Lists |
| Tomislav Smuc- Rudjer Boskovic Institute |
| Nives Skunca (Rudjer Boskovic Institute, Department of Electronics); Tomislav Smuc (Rudjer Boskovic Institute, Department of Electronics); Fran Supek (Rudjer Boskovic Institute, Department of Electronics); |
| Short Abstract: We propose a clustering-like approach for flexible reduction in size of large user-supplied lists of overlapping Gene Ontology (GO) terms, typically resulting from high-throughput experiments. The remaining GO terms are visualized so as to faithfully reflect the terms' interrelations, relying on measures of semantic similarity in the GO space. |
| Long Abstract: Click Here |
| Poster P7 |
| A GO TOOLS ONTOLOGY |
| Jose Luis Mosquera- University of Barcelona |
| Alex Sánchez (University of Barcelona, Department of Statistics); |
| Short Abstract: We present an ontology that covers GO tools for gene expression analysis available at theGO consortium. It is intended to (1) classify them, (2) guide developers and (3) select tools.The concepts described are types of tools, input/output annotations and statistical analysisamong others. |
| Long Abstract: Click Here |
| Poster P8 |
| Beat: Bio-ontologies enrichment and alignment toolkit |
| Andrea Splendiani- U936 |
| Elena Beisswanger (Jena University, JULIE lab); Olivier Dameron (University of Rennes 1, INSERM U936); John McNaught (University of Manchester, NACTEM); Scott Piao (University of Manchester, NACTEM); Sophia Ananiadou (University of Manchester, NACTEM); Udo Hahn (Jena University, JULIE lab); Anita Burgun (University of Rennes 1, INSERM U936); |
| Short Abstract: BEAT is a toolkit for ontology enrichment and alignment, based on Semantic Web technologies. It allows for modular composition of operations on ontologies. In particular, it supports the alignment of biomedical ontologies offering modules exploiting information from the UMLS Knowledge Sources. |
| Long Abstract: Click Here |
| Poster Q01 |
| 3Dsim - 3D Structural Implication of Mutations |
| Jose Izarzugaza- CNIO - Spanish National Cancer Research Centre |
| Anja Baresic (University College London, Institute of Structural and Molecular Biology); Lisa McMillan (University College London, Institute of Structural and Molecular Biology); Corin Yeats (University College London, Institute of Structural and Molecular Biology); Andrew Clegg (University College London, Institute of Structural and Molecular Biology); Christine Orengo (University College London, Institute of Structural and Molecular Biology); Andrew Martin (University College London, Institute of Structural and Molecular Biology); Alfonso Valencia (CNIO - Spanish National Cancer Research Centre, Structural Biology and Biocomputing Programme); |
| Short Abstract: 3DSim is a web-application that facilitates the localization and visualization of single amino acid polymorphisms from SAAPdb by mapping them onto representative structures from the CATH database. The application provides a comprehensive overview of the distribution of neutral and pathogenic mutations in structural space. |
| Long Abstract: Click Here |
| Poster Q02 |
| waviCGH v2.0: a web server for the analysis, integration and visualization of aCGH experiments |
| Angel Esteban- CNIO |
| Daniel Rico (CNIO, Structural biology and biocomputing ); Eduardo Andres (CNIO, Structural biology and biocomputing ); Oscar Rueda (CNIO, Structural biology and biocomputing ); Ramon Diaz (CNIO, Structural biology and biocomputing ); David Gonzalez (CNIO, Structural biology and biocomputing ); |
| Short Abstract: waviCGH v2.0 is a versatile web server application for the analysis, visualization and integration of array-CGH (aCGH) data. The server is designed to bridge the gap between wet lab researchers doing aCGH and the methods for their numerical analysis. |
| Long Abstract: Click Here |
| Poster Q03 |
| Sanity Check and Quality Control for Data Submitted to the European Genotype Archive (EGA) |
| Vasudev Kumanduri- EBI |
| Jonathan Hinton (EBI, Vertebrate Genomics); Ilkka Lappalainen (EBI, Vertebrate Genomics); Mario Caccamo (EBI, Vertebrate Genomics); Paul Flicek (EBI, Vertebrate Genomics); |
| Short Abstract: We have created a permanent archive for all types of personally identifiable genetic and phenotypic data. The service includes now a generic QC and sanity check pipelines for all submitted data that can also be customized for needs of data generating consortium or individual user. Our tools also allow direct comparison between different analysis methods. |
| Long Abstract: Click Here |
| Poster Q04 |
| A Model of HIV-1 Coreceptor Tropism: Population Perspective |
| Gōkhan Ertaylan- University of Amsterdam |
| No additional authors |
| Short Abstract: The coreceptor tropism switch in Human Immunodeficiency Virus infection is associated with developing AIDS. We have developed a computational model for studying this phenomenon. Given the transmission with a CCR5 tropic virus, we evaluate the mutation rate carrying the virus quasispecies to an optimum fitness by changing coreceptor tropism. |
| Long Abstract: Click Here |
| Poster Q05 |
| Complex hierarchical population subdivision in guppies from Trinidad and Venezuela revealed by high-density marker analyses |
| Eva-Maria Willing- Max Planck Institute for Devolpmental Biology |
| Margarete Hoffmann (Max Planck Institute for Devolpmental Biology, Molecular Biology); Detlef Weigel (Max Planck Institute for Devolpmental Biology, Molecular Biology); Christine Dreyer (Max Planck Institute for Devolpmental Biology, Molecular Biology); |
| Short Abstract: Guppies (Poecilia reticulata) are a long-standing model of ecological genetics, yet little is known about population subdivision at the whole-genome level. We analyzed divergence among populations applying different clustering approaches to genome wide SNP data. We found that population substructure agrees with geographic vicariance and hypothesized patterns of historical colonization. |
| Long Abstract: Click Here |
| Poster Q06 |
| Genome-wide Association Analysis with Stochastic Block Lasso |
| Seyoung Kim- Carnegie Mellon University |
| Eric Xing (Carnegie Mellon University, Department of Machine Learning); |
| Short Abstract: We propose a new approach calleda stochastic block lasso for association mapping thatexploits prior knowledge on linkage disequilibrium structure in the genomesuch as recombination rate and distance between adjacent SNPs in orderto identify blocks of SNPs for association. |
| Long Abstract: Click Here |
| Poster Q07 |
| Pathway analysis of genome-wide association studies |
| Karen Kapur- University of Lausanne |
| Sven Bergmann (University of Lausanne, Department of Medical Genetics); |
| Short Abstract: There has been much interest in extending analysis of genome-wide associationstudies to include epistatic effects between two genetic variants. Using a guidedsearch strategy to search within a restricted subset of SNP pairs, we apply anintegrative approach to combine information about protein interactions with epistasisgene-gene interactions. |
| Long Abstract: Click Here |
| Poster Q08 |
| A closed-form asymptotic sampling formula for a two-locus model |
| Paul Jenkins- University of California, Berkeley |
| Yun Song (University of California, Berkeley, Electrical Engineering and Computer Science); |
| Short Abstract: We present the asymptotic behaviour of the sampling probability of genetic data in a two-locus, infinite alleles model, when recombination is large. The first two terms of an asymptotic expansion are given analytically. Extensive assessment of our formula finds close agreement with exact solutions for many configurations and parameter values. |
| Long Abstract: Click Here |
| Poster Q09 |
| Method for inferring the frequencies of disease alleles in case-control studies |
| Leeyoung Park- Yonsei University |
| No additional authors |
| Short Abstract: A Bayesian approach is proposed for the inference of disease allele frequencies. This multi-parameter model focuses on the changed frequencies of marker alleles in cases compared to controls for Bayesian update. This approach implements Markov Chain Monte Carlo techniques for estimating the posterior probabilities of disease allele frequencies. |
| Long Abstract: Click Here |
| Poster Q10 |
| MoDIL: Detecting INDEL Variation with Clone-end Sequencing |
| Seunghak Lee- University of Toronto |
| Fereydoun Hormozdiari (Simon Fraser University, School of Computing Science); Can Alkan (University of Washington and the Howard Hughes Medical Institute, Department of Genome Sciences); Michael Brudno (University of Toronto, Department of Computer Science, Banting and Best Dept. of Medical Research); |
| Short Abstract: We present a novel method for finding insertion/deletion polymorphisms from paired short reads. We model each genomic locus as a mixture of two haplotypes, and our method takes advantage of the high clone coverage to identify homozygous and heterozygous variation. Our experimental results demonstrates that MoDIL accurately identifies indels (>20bp). |
| Long Abstract: Click Here |
| Poster Q11 |
| A new conditional sampling distribution for the coalescent with recombination |
| Joshua Paul- University of California, Berkeley |
| Yun Song (University of California, Berkeley, EECS Department); |
| Short Abstract: We describe a principled technique for approximating the conditional sampling distribution (CSD) for a general finite-sites, finite-alleles coalescent model with recombination, and provide evidence that it is more accurate than previously proposed methods. Additionally, we explore the effect of our new approximate CSD on importance sampling and PAC methods. |
| Long Abstract: Click Here |
| Poster Q13 |
| Match probabilities in a finite, subdivided population |
| Anna-Sapfo Malaspinas- UC Berkeley |
| Yun Song (UC Berkeley, EECS and Statistics); Montgomery Slatkin (UC Berkeley, Integrative Biology); |
| Short Abstract: Recently a graphical framework was introduced to compute the probability that two individuals randomly chosen from a finite population have matching DNA profiles at several unlinked loci. Here, we extend that framework to include subdivided population structure and show that match probabilities depend strongly on migration rates. |
| Long Abstract: Click Here |
| Poster Q14 |
| De novo transcriptome assembly from paired-end RNA-Seq data |
| Marcel Schulz- Max Planck Institute for Molecular Genetics |
| Daniel Zerbino (European Bioinformatics Institute, Protein and Nucleotide Database Group ); Ewan Birney (European Bioinformatics Institute, Protein and Nucleotide Database Group); Martin Vingron (Max Planck Institute for Molecular Genetics, Computational Molecular Biology); |
| Short Abstract: We consider the de novo transcriptome assembly problem from next-generation paired-end short read data. Extending the Velvet genome assembler we demonstrate how to assemble transcriptomes of different complexity. |
| Long Abstract: Click Here |
| Poster R01 |
| MRMaid: automating the design of multiple reaction monitoring (MRM) experiments using expert knowledge and MS/MS data-mining |
| Jennifer Mead- Cranfield University |
| Luca Bianco (Cranfield University, Bioinformatics Group); Conrad Bessant (Cranfield University, Bioinformatics Group); |
| Short Abstract: Multiple reaction monitoring (MRM) is a popular technique that employs tandem MS to quantify multiple proteins in a single experiment. MRMaid (pronounced ‘mermaid’) is a new service (www.mrmaid.info) that answers the challenging question faced when designing MRM experiments: which peptide/product ions should I monitor for my protein of interest? |
| Long Abstract: Click Here |
| Poster R02 |
| spectral clustering in peptidomics studies helps to unravel modification profile of biologically active peptides, and enhances peptide identification rate. |
| Gerben Menschaert- University of Ghent |
| Tom Vandekerckhove (Ghent University, Department of Molecular Biotechnology); Wim Vancriekinge (Ghent University, Department of Molecular Biotechnology); Eisuke Hayakawa (K.U. Leuven, Research group of Functional Genomics and Proteomics); Bart Landuyt (K.U. Leuven, Research group of Functional Genomics and Proteomics); Liliane Schoofs (K.U. Leuven, Research group of Functional Genomics and Proteomics); Walter Luyten (K.U. Leuven, Department of Woman & Child, Biomedical Science Group); |
| Short Abstract: Identification of bio-active peptides (the peptidome) is mostly attempted by mass spectrometry. However, the identification rates are often unsatisfactory, mainly caused by the wealth of peptide modifications. Including a spectral clustering step into a peptidomics identification pipeline results in doubled identification rates and a complete modification profile (including new ones). |
| Long Abstract: Click Here |
| Poster R03 |
| FOLD SPACE GRAPHS – A NEW METHOD TO EXPLORE EVOLUTIONARY RELATIOSHIPS BETWEEN PROTEIN STRUCTURES |
| Natalja Kurbatova- EBI |
| No additional authors |
| Short Abstract: We have developed a new method for exploring evolutionary relations between protein structures by navigating through the fold space under assumption that protein structures have evolved by a stepwise mutation processes. This method is based on the ESSM algorithm for detecting structural mutations and construction of fold space graphs. |
| Long Abstract: Click Here |
| Poster R04 |
| Prediction of glycosylation sites in proteins |
| Karin Julenius- Karolinska Institutet |
| No additional authors |
| Short Abstract: Protein glycosylation is more abundant and structurally diverse than all other types of post-translational modifications. We develop prediction methods that recognize glycosylation sites in proteins from amino acid sequence alone. All our prediction servers are made publically available at www.cbs.dtu.dk/services, the most recent being NetPGlyc, a predictor of proteoglycan sites. |
| Long Abstract: Click Here |
| Poster R05 |
| A new systematic approach to identify functions of human extracellular proteins using yeast |
| Solip Park- POSTECH |
| Ok-Kyu Song (POSTECH, Life science); Hyung-Jin Lee (POSTECH, Life science); Vit Kim (POSTECH, Life science); Jae-Seong Yang (POSTECH, I-Bio); Sanguk Kim (POSTECH, Life science); Sung Key Jagn (POSTECH, Life science); |
| Short Abstract: Cell signaling, differentiation and proliferation are governed by extracellular proteins. Despite their functions importance, a large part of the proteins are remained unknown. Here, we present a new approach to determine functions of mammalian proteins using co-cultivation of yeast and mammalian cells named Zymogand system. |
| Long Abstract: Click Here |
| Poster R06 |
| X-Tracker: A Generic Quantitation Tool for MS-based Proteomics |
| Luca Bianco- Cranfield University |
| Luca Bianco (Bioinformatics Group, Cranfield Health); Conrad Bessant (Bioinformatics Group, Cranfield Health); |
| Short Abstract: X-Tracker is a new piece of software allowing Mass Spectrometry-based protein quantitation. Through an abstraction of the main steps involved in quatitation, X-Tracker is able to support all the current quantitative protocols, both at MS or Tandem-MS level, and provide a flexible, platform-independent and easy-to-use quantitation environment. |
| Long Abstract: Click Here |
| Poster R07 |
| Model-based Imputation of Missing Data in Bottom-Up MS-Based Proteomics |
| Yuliya Karpievitch- Texas A&M University |
| Jeff Stanley (Texas A&M, Statistics); Thomas Taverner (PNNL, Biological Sciences); Jianhua Huang (Texas A&M, Statistics); Joshua Adkins (PNNL, Biological Sciences); Charles Ansong (PNNL, Biological Sciences); Fred Heffron (Oregon Health and Science University, Microbiology); Hyunjin Yoon (Oregon Health and Science University, Microbiology); Thomas Metz (PNNL, Biological Sciences); Wei-Jun Qian (PNNL, Biological Sciences); Dick Smith (PNNL, Biological Sciences); Alan Dabney (Texas A&M, Statistics); |
| Short Abstract: We present a model-based approach for filtering low quality proteins and peptides and then imputing the missing values. Our likelihood model accounts for the fact that many peptide measurements will be unobserved, due to (1) random “missingness” and (2) falling below the detection limit, i.e. censoring. |
| Long Abstract: Click Here |
| Poster R08 |
| Understanding phytocystatin structure/function relationships through homology modeling |
| Juan Vorster- University of Pretoria |
| Özlem Tastan Bishop (University of Pretoria, Biochemistry); Urte Schlüter (University of Pretoria, Plant Science); Karl Kunert (University of Pretoria, Plant Science); Dominique Michaud (Université Laval, Département de Phytologie); |
| Short Abstract: Amino acid substitutions at positively selected sites were performed on a model cystatin and shown to modulate the inhibitory potency against. Using a homology modeling approach we investigate structure/function relationships between the mutant cystatins and various cysteine proteases, with the aim of better understanding their mode of action. |
| Long Abstract: Click Here |
| Poster R09 |
| Detecting specificity residues in protein interactions |
| Qiang Luo- University of Oxford |
| Rebecca Hamer (University of Oxford, Department of Statistics); Charlotte Deane (University of Oxford, Department of Statistics); Gesine Reinert (University of Oxford, Department of Statistics); |
| Short Abstract: Detection of residues which determine the specificity of protein-protein interactions is currently non trivial. We propose a novel algorithm which considers a protein as a network with 20 types of nodes and show improved results over existing methods. |
| Long Abstract: Click Here |
| Poster R10 |
| Adaptation of viruses towards their hosts -A proteome scale analysis |
| Iris Bahir- Hebrew University |
| Michal Linial (Hebrew University, Biological Chemistry); |
| Short Abstract: Viral evolution is dominated by an extreme high mutation rate, a large population sizeand by the inherent ability for fast exchange of genetic material. We tested the forces that shape viruses by monitoring all pairs of amino acid distribution and codon usage for viruses and hosts. The significant findings are discussed. |
| Long Abstract: Click Here |
| Poster R11 |
| Iterative precursor ion selection for LC-MS/MS based shotgun proteomics |
| Alexandra Zerck- Max Planck Institute for Molecular Genetics |
| Johan Gobom (University of Gothenborg/Sahlgrenska University Hospital, Department of Neuroscience and Physiology); Hans Lehrach (Max Planck Institute for Molecular Genetics, Vertebrate Genomics); Knut Reinert (FU Berlin, Department for Computer Science); Eckhard Nordhoff (Max Planck Institute for Molecular Genetics, Vertebrate Genomics); |
| Short Abstract: We present a result-driven, iterative approach for precursor ion selection forLC-MS/MS based shotgun proteomics. In our approach identification results of previous iterations guide the precursor ionselection. This way the efficiency of an MS/MS analysis is significantlyincreased, as data redundancy and analysis time are reduced. |
| Long Abstract: Click Here |
| Poster R12 |
| Graph theoretic properties of known protein complexes |
| Suzanne Gallagher- University of Colorado |
| Debra Goldberg (University of Colorado, Computer Science); |
| Short Abstract: We examined protein complexes in the protein-protein interaction network in order to determine what graph theoretic properties correspond to complexes. We examined approximately 150 known protein complexes from MIPS and iPFam and looked at edge density, clustering coefficient, betweenness centrality, vertex and edge connectivity, and subgraph properties for each. |
| Long Abstract: Click Here |
| Poster R13 |
| A Bayeisan Approach to the Quantification of Overlapping Peptides in a MALDI-TOF Mass Spectrum |
| Qi Zhu- I-Biostat |
| Adetayo Kasim (I-Biostat, Universiteit Hasselt); Dirk Valkenborg (I-Biostat, Katholieke Universiteit Leuven); Ivy Jansen (I-Biostat, Universiteit Hasselt); Tomasz Burzykowski (I-Biostat, Universiteit Hasselt); |
| Short Abstract: In MALDI-TOF mass spectra, it occurs that peptide peaks coincide with each other. The quantification of relative abundances and exact masses of these overlapping peptides is problematic. We propose a Bayesian model to address this problem and apply the method to real-life data sets from a controlled mass spectrometry experiment. |
| Long Abstract: Click Here |
| Poster R14 |
| Confirming alternative protein isoforms in Drosophila |
| Michael Liam Tress- Cnio |
| Michael Tress (Spanish National Cancer Centre (CNIO), Structural and Biological Computation); Alfonso Valencia (Spanish National Cancer Centre (CNIO), Structural and Biological Computation); Bernd Bodenmiller (ETH , Institute of Molecular Systems Biology ); Ruedi Aebersold (ETH , Institute of Molecular Systems Biology ); |
| Short Abstract: Two recent large scale proteomics studies generated extensive peptide catalogs from the Drosophila melangaster proteome. The analysis of this proteomic data confirmed the presence of multiple alternative gene products for over a hundred Drosophila genes. The analysis highlights the growing importance of proteomics in the validation of predicted proteins. |
| Long Abstract: Click Here |
| Poster R15 |
| Crystal structures of thymidylate kinase from Sulfolobus tokodaii and Aquifex aeolicus |
| Jigisha Darbha- Vellore Institute of Technology |
| J Jeyakanthan (National Synchrotron Radiation Research Center, 101 Hsin-Ann Road, Hsinchu Science Park, Hsinchu 30076, -); S.P Kanaujia (Indian Institute of Science, Bangalore 560 012, Bioinformatics Centre, Supercomputer Education and Research Centre); Z.A Rafi (Madurai Kamaraj University, Madurai 625 021, Bioinformatics Centre, School of Biotechnology ); N Nakagawa (RIKEN SPring-8 Center, Harima Institute, 1-1-1 Kouto, Sayo, Hyogo 679-5148, Graduate School of Science Osaka Univ., 1-1 Yamadaoka, Suita, Osaka, 565-0871, -); A Shinkai (RIKEN SPring-8 Center, Harima Institute, 1-1-1 Kouto, Sayo, Hyogo 679-5148, -); S Kuramitsu (RIKEN SPring-8 Center, Harima Institute, 1-1-1 Kouto, Sayo, Hyogo 679-5148, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, -); K Sekar (Indian Institute of Science, Bangalore 560 012, Bioinformatics Centre, Supercomputer Education and Research Centre); S Yokoyama (RIKEN SPring-8 Center, Harima Institute, 1-1-1 Kouto, Sayo, Hyogo 679-5148, Genomic Sciences Center, Yokohama Institute, RIKEN, 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Department of Biophysics and Biochemistry, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, -); |
| Short Abstract: Our report provides insights into the structural features of thymidylate kinase from two thermophilic microorganisms, Sulfolobus tokodaii and Aquifex aeolicus. |
| Long Abstract: Click Here |
| Poster R16 |
| Improving protein identification by MsPI using peak intensity |
| Alessandra Tiengo- Università degli Studi di Pavia |
| Nicola Barbarini (Università degli Studi di Pavia, Dipartimento di Informatica e Sistemistica); Sonia Troiani (Nerviano Medical Sciences, Biotechnology Department); Luisa Rusconi (Nerviano Medical Sciences, Biotechnology Department); Paolo Magni (Università degli Studi di Pavia, Dipartimento di Informatica e Sistemistica); |
| Short Abstract: This work presents MsPI, a software tool developed to perform protein identification by Peptide Mass Fingerprinting approach. Compared with other software tools, MsPI shows better performance, especially when are not considered only the masses of the peak list but also the intensity values. |
| Long Abstract: Click Here |
| Poster R17 |
| A Robust Statistical Approach for Detecting Differential Protein Expression in iTRAQ MS-Experiments |
| Holger Froehlich- Cellzome AG |
| Marcus Bantscheff (Cellzome AG, ); Gerard Joberty (Cellzome AG, ); Yann Abraham (Cellzome AG, ); Judith Schlegl (Cellzome AG, ); Seon-Hi Jang (Max-Planck Institute for Molecular Genetics, ); Bodo Lange (Max-Planck Institute for Molecular Genetics, ); Gerard Drewes (Cellzome AG, ); |
| Short Abstract: We devise a robust statistical framework for iTRAQ MS data normalization and assessment of differentially expressed proteins. Normalization is carried out via a median polish procedure followed by a robust linear model fitted to the residuals. For differential protein expression we use limma. |
| Long Abstract: Click Here |
| Poster R18 |
| On the beta binomial model for spectral count data in label-free tandem mass spectrometry-based proteomics |
| Thang Pham- VU University Medical Center |
| Sander Piersma (VU University Medical Center, OncoProteomics); Marc Warmoes (VU University Medical Center, OncoProteomics); Connie Jimenez (VU University Medical Center, OncoProteomics); |
| Short Abstract: We propose to use the beta-binomial distribution for differential analysis of protein abundances expressed in spectral counts in label-free mass spectrometry-based proteomics. The beta binomial test performs favorably in comparison to other methods on several datasets. A software package is implemented for parameter estimation and inference of beta-binomial models. |
| Long Abstract: Click Here |
| Poster R19 |
| Novel cancer biomarkers identified by a high through-put immuno-proteomic approach |
| Andrea Pierleoni- Externautics |
| Renata Grifantini (Externautics, R&D); Alberto Grandi (Externautics, R&D); Susanna Campagnoli (Externautics, R&D); Renzo Nogarotto (Externautics, R&D); Piero Pileri (Externautics, R&D); Elena Canidio (Primm, R&D); Davide Cattaneo (Primm, R&D); Massimiliano Pagani (Primm, R&D); Paolo Sarmientos (Externautics - PRIMM, R&D); Sergio Abrignani (INGM, Istituto Nazionale Genetica Molecolare); Guido Grandi (Externautics, Scientific Advisory Board); Giuseppe Viale (European Institute of Oncology and University of Milan , Division of Pathology); |
| Short Abstract: 8 novel cancer-specific biomarkers were identified by a high through-put immuno-proteomic approach, based on the direct detection of tumor-associated-proteins on clinical tumor tissues by immunohistochemistry. The screening is sill in progress and a library of 1600 mouse antisera is currently been tested versus the most common human cancer tissues. |
| Long Abstract: Click Here |
| Poster R20 |
| ProSE - a Rich Internet Application to securely Store, Organise, and Analyse Quantitative Proteomics Experiments |
| Stefan Albaum- Bielefeld University |
| Heiko Neuweger (Bielefeld University, Computational Genomics, Center for Biotechnology); Sita Lange (Bielefeld University, Computational Genomics, Center for Biotechnology); Dominik Mertens (Bielefeld University, Computational Genomics, Center for Biotechnology); Jörn Kalinowski (Bielefeld University, Institute for Genome Research and Systems Biology (IGS), Center for Biotechnology); Tim W. Nattkemper (Bielefeld University, Biodata Mining & Applied Neuroinformatics Group, Faculty of Technology); Alexander Goesmann (Bielefeld University, Computational Genomics, Center for Biotechnology); |
| Short Abstract: Tandem mass spectrometry coupled to liquid chromatography in combination with stable isotope labeling is able to measure the expression of hundreds of peptides in one experiment. To cope with the arising amounts of data and help in the conduction of these experiments we have developed the web application ProSE. |
| Long Abstract: Click Here |
| Poster R21 |
| Epitope mapping of monospecific polyclonal antisera raised against KRAB zink finger proteins |
| Hans Thiesen- Institute of Immunology |
| Peter Lorenz (University of Rostock, Institute of Immunology); Cristina Al-Khalili Szigyarto (Royal Institute of Technology (KTH), AlbaNova University Center); Mathias Uhlén (Royal Institute of Technology (KTH), AlbaNova University Center); |
| Short Abstract: KRAB C2H2 zinc finger (ZNF) proteins constitute the largest mammalian class of transcriptional regulators with repression potential, see database SysZNF. High affinity antibody tools are essential prerequisites to establish tissue expression profiles. Peptide microarrays were used to pinpoint specificities and cross-reactivities of monovalent affinity-purified antibodies against 54 KRAB ZNF proteins. |
| Long Abstract: Click Here |
| Poster S01 |
| Conserved regulatory processes revealed by RNA half-life |
| Caroline Friedel- Ludwig-Maximilians-Universität München |
| Lars Dölken (Ludwig-Maximilians-Universität München, Max von Pettenkofer-Institut); Zsolt Ruzsics (Ludwig-Maximilians-Universität München, Max von Pettenkofer-Institut); Ulrich H. Koszinowski (Ludwig-Maximilians-Universität München, Max von Pettenkofer-Institut); Ralf Zimmer (Ludwig-Maximilians-Universität München, LFE Bioinformatik, Institut für Informatik); |
| Short Abstract: We determined precise transcript half-lives using a novel approach for measuring both newly transcribed and total RNA. Our results show that transcript half-life is conserved and specifically correlated to gene function and regulation. This allows the identification of unknown mechanisms in transcriptional regulation for protein complexes and important cellular processes. |
| Long Abstract: Click Here |
| Poster S02 |
| Comparison and improvement of models for the binding site of transcription factor p53 |
| Ji-Hyun Lim- University of St Andrews |
| Richard Iggo (University of Bordeaux, INSERM Unit U916, Institut Bergonie); Daniel Barker (University of St Andrews, School of Biology); |
| Short Abstract: A more accurate characterisation of the p53 response element may help us better understand and predict functional p53 binding sites. To improve the p53 response element model we test methods based on PWMs, hidden Markov models, information theory and more sophisticated approaches incorporating dependencies between the motif base positions. |
| Long Abstract: Click Here |
| Poster S03 |
| Exploring gene regulation through PARCDB-eQTL workflow |
| Priscila Darakjian- Oregon Health and Science University |
| Sunita Kawane (Oregon Health & Science University, BMIP); Daniel Bottomly (Oregon Health & Science University, BMIP); Nicole Walter (Oregon Health & Science University, Behavioral Neuroscience, Portland Alcohol Research Center); Robert Hitzemann (Oregon Health & Science University, Behavioral Neuroscience, Portland Alcohol Research Center); Shannon McWeeney (Oregon Health & Science University, OHSU Knight Cancer Institute); |
| Short Abstract: Expression quantitative trait loci (eQTL) analysis has aided our understanding of gene regulation and gene regulatory networks. To maximize the potential of such data, we have developed a computational workflow that allows dynamically mining eQTL data (based on Affymetrix and Illumina gene expression) for cis and trans-regulated genes. |
| Long Abstract: Click Here |
| Poster S04 |
| Systematic Analysis of Human 5’UTR Introns Reveals Their Importance in Expression |
| Can Cenik- Harvard Medical School |
| Adnan Derti (Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology ); Joe Mellor (Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology ); Gabriel Berriz (Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology ); Frederick Roth (Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology ); |
| Short Abstract: In a genome-scale analysis, we find that 5'UTR introns have a profound length-dependent effect on expression and genes with 5'UTR introns are overrepresented among regulatory genes. Our results have implications for the evolution of these much neglected class of introns |
| Long Abstract: Click Here |
| Poster S05 |
| A probabilistic model for competitive binding of transcription factors |
| Kirsti Laurila- Tampere University of Technology |
| Harri Lähdesmäki (Tampere University of Technology, Department of Signal Processing); |
| Short Abstract: Transcriptional regulation is to a large extent controlled by transcription factors binding to DNA. We have developed a probabilistic model that predicts simultaneously binding of several transcription factors. Modeling results show improvement compared to the cases where the individual prediction results of individual predictions are combined. |
| Long Abstract: Click Here |
| Poster S06 |
| Analysis of Chromatin Dynamics Using Public Large-scale Nucleosome Maps |
| Yoshiaki Tanaka- University of Tokyo |
| Itsuki Yoshimura (University of Tokyo, Medicine); Kenta Nakai (University of Tokyo, Medical Genome Sciences); |
| Short Abstract: Nucleosome organization is essential for understanding cellular processes such as transcription and replication, but it is not fully understood which nucleosomes are more dynamic or static. In this study, we merged multiple genome-scale nucleosome maps, and shows new aspects of chromatin statuses. |
| Long Abstract: Click Here |
| Poster S07 |
| Pseudogenes as a source of trans-NATs that regulate their parental genes |
| Enrique Muro- Max-Delbrück-Centrum für Molekulare Medizin |
| Enrique M. Muro (Max-Delbrück-Centrum für Molekulare Medizin , Computational Biology and Data Mining lab); Miguel A. Andrade-Navarro (Max-Delbrück-Centrum für Molekulare Medizin , Computational Biology and Data Mining lab); |
| Short Abstract: We present the hypothesis that pseudogenes, after some evolution, could be a source of natural antisense transcripts that target and regulate their respective parental genes (trans- NATs). When a pseudogene is produced (duplicated or retrotransposed), a putative trans- NAT to the parental gene is already there by default if the parental gene had already coded a cis-NAT; further evolution could erase or tune any of the two NAT copies. In order to find evidence for this hypothesis we used the public dataset of human ESTs stored at the NCBI’s GenBank database and made a genome wide screening of pseudogenes following our experimentally verified method [1]. We found 180 trans- NATs inside pseudogenes, which are transcribed and are potential candidates to regulate the respective parental genes. We aligned our candidates against their respective parental genes and compared their sequences to study the mutations that appeared after the pseudogene formation. If the trans-NAT had no functionality a flat pattern of conservation should have been obtained. Instead, we found high conservation in a region of 300 nucleotides upstream the 3’-end of the trans-NAT that points to a functional role. We illustrate our results with details about some of the cases found. The method is new and original and there are only few experimental evidences that support this work. The method and a complete list of predictions will be freely available. |
| Long Abstract: Click Here |
| Poster S08 |
| Identifying targets of transcriptionally regulated transcription factors using dynamical models |
| Antti Honkela- Helsinki University of Technology |
| Neil D. Lawrence (University of Manchester, School of Computer Science); Magnus Rattray (University of Manchester, School of Computer Science); |
| Short Abstract: We apply a Gaussian process cascaded differential equation regulationmodel to identify targets of transcriptionally regulated transcriptionfactors from wild type time series expression data. The results showsignificant improvements over ranking by differential expression inknock-outs and other alternative methods. |
| Long Abstract: Click Here |
| Poster S09 |
| Detecting Condition-Specific Transcription Regulators using Linear Modeling and Combinatorial Search |
| Konstantin Tretjakov- University Of Tartu |
| Jaak Vilo (University of Tartu, Institute of Computer Science); |
| Short Abstract: We consider the problem of computational reconstruction of transcriptional regulatory networks and formulate it as a task of detecting a small set of influential transcriptional regulators, which can appropriately represent the expression of all genes in a given microarray dataset. Experiments show that this approach can lead to fruitful results. |
| Long Abstract: Click Here |
| Poster S10 |
| Heavy metal resistance in Cupriavidus metallidurans: towards the reconstruction of regulatory networks |
| Pieter Monsieurs- SCK-CEN |
| Abderrafi Benotmane (SCK-CEN, Molecular and Cellular Biology); Sebastien Monchy (SCK-CEN, Molecular and Cellular Biology); Paul Janssen (SCK-CEN, Molecular and Cellular Biology); Rob Van Houdt (SCK-CEN, Molecular and Cellular Biology); Hugo Moors (SCK-CEN, Molecular and Cellular Biology); Natalie Leys (SCK-CEN, Molecular and Cellular Biology); Max Mergeay (SCK-CEN, Molecular and Cellular Biology); |
| Short Abstract: The soil bacterium Cupriavidus metallidurans CH34 can survive in harsh environments containing high concentrations of heavy metals. High-throughput data suggest that a complex regulatory network is underlying the heavy metal resistance. This transcriptional regulation can be deciphered using a combination of gene expression and sequence motif analysis. |
| Long Abstract: Click Here |
| Poster S11 |
| Analysing ChIPseq Datasets of Transcription Factor Binding Sites in the Cloud |
| Caroline Johnston- Kings College London |
| Diogo Castro (NIMR, Molecular Neurobiology); Daniella Dreschel (NIMR, Molecular Neurobiology); Angela Bithell (NIMR, Molecular Neurobiology); Francois Guillemot (NIMR, Molecular Neurobiology); Noel Buckley (KCL, Neuroscience); |
| Short Abstract: We used ChIPseq to investigate the binding targets of transcription factors involved in the regulation of neural cell development. Using compute resources from Amazon EC2, we have compared the performance of a number of alignment and peak-finding algorithms on our data. |
| Long Abstract: Click Here |
| Poster S12 |
| Computational simulation of transcription factor binding for the prediction of regulatory regions in DNA sequences |
| Rebecca Hunt Newbury- Center for Molecular Medicine and Therapeutics/Child and Family Research Institute, University of British Columbia |
| David Arenillas (Centre for Molecular Medicine and Therapeutics/Child and Family Research Institute, University of British Columbia, Department of Medical Genetics); Peter Sudmant (Centre for Molecular Medicine and Therapeutics/Child and Family Research Institute, University of British Columbia, Department of Medical Genetics); Dimas Yusuf (Centre for Molecular Medicine and Therapeutics/Child and Family Research Institute, University of British Columbia, Department of Medical Genetics); Diane Wu (Centre for Molecular Medicine and Therapeutics/Child and Family Research Institute, University of British Columbia, Department of Medical Genetics); Wyeth Wasserman (Centre for Molecular Medicine and Therapeutics/Child and Family Research Institute, University of British Columbia, Department of Medical Genetics); |
| Short Abstract: Transcription factors (TFs) are key regulatory proteins in gene expression, controlling cell differentiation and transient environmental responses. We introduce a transcriptional regulation simulation that incorporates TF searching of DNA for target sites and interactions between TFs, ultimately reporting the occupancy of a TF within a region of DNA. |
| Long Abstract: Click Here |
| Poster S13 |
| Exploring the Genetics of Gene Expression with Random Forests |
| Jacob Michaelson- TU Dresden |
| Rudi Alberts (Helmholtz Centre for Infection Research, ); Klaus Schughart (Helmholtz Centre for Infection Research, ); Andreas Beyer (Biotechnology Center, TU Dresden, Cellular Networks and Systems Biology); |
| Short Abstract: The use of Random Forests as an eQTL mapping method is discussed, and its ability to recover known pathway information is compared with widely-used eQTL mapping methods. We also present a novel means for detecting multi-locus interactions using Random Forests. |
| Long Abstract: Click Here |
| Poster S14 |
| A Transcription Factor Affinity Based Code for Mammalian Transcription Initiation |
| Molly Megraw- Duke University |
| Fernando Pereira (University of Pennsylvania, Computer Science); Shane Jensen (University of Pennsylvania, Statistics); Artemis Hatzigeorgiou (Alexander Fleming Research Institute, Molecular Oncology); Uwe Ohler (Duke University, Institute for Genome Sciences and Policy); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster S15 |
| Global mapping of protein-DNA interactions in vivo by digital genomic footprinting |
| Xiaoyu Chen- University Of Washington |
| Jay Hesselberth (University of Washington, Genome Sciences); Zhihong Zhang (University of Washington, Genome Sciences); Peter Sabo (University of Washington, Genome Sciences); Richard Sandstrom (University of Washington, Genome Sciences); Alex Reynolds (University of Washington, Genome Sciences); Robert Thurman (University of Washington, Genome Sciences); Shane Neph (University of Washington, Genome Sciences); Michael Kuehn (University of Washington, Genome Sciences); William Noble (University of Washington, Genome Sciences); Stanley Fields (University of Washington, Genome Sciences); John Stamatoyannopoulos (University of Washington, Genome Sciences); |
| Short Abstract: We developed a digital approach to assay regulatory proteinoccupancy on DNA in vivo by dense mapping ofDNaseI cleavages from intact nuclei using massivelyparallel DNA sequencing. Analysis of DNaseI cleavagesacross the yeast genome revealed thousandsof regulatory protein footprints, enabling de novoderivation of factor binding motifs and the identification ofnew binidng sites for major regulators. |
| Long Abstract: Click Here |
| Poster S16 |
| Identifying switches of combinatorial regulation between different cellular conditions |
| Florian Markowetz- Cancer Research UK Cambridge Research Institute |
| Ewa Szczurek (Max-Planck Institute for Molecular Genetics, Computational Molecular Biology); Irit Gat-Viks (Broad Institute of MIT and Harvard, Computational Biology); Martin Vingron (Max-Planck Institute for Molecular Genetics, Computational Molecular Biology); |
| Short Abstract: Understanding molecular changes between different cellular conditions is an important step in elucidating disease mechanisms, including cancer. We propose a pathway-centric approach to identify how transcriptional regulation downstream of a signalling pathway changes between conditions by combining prior knowledge on the pathway structure with transcriptional phenotypes of gene perturbation experiments. |
| Long Abstract: Click Here |
| Poster S18 |
| Promatch: A Computational Method for Identifying Conserved Transcription Factor Binding Sites |
| Quinn Snell- Brigham Young University |
| W. Evan Johnson (Brigham Young University, Statistics); Mark Clement (Brigham Young University, Computer Science); Colin Rogerson (Brigham Young University, Statistics); Kendell Clement (Brigham Young University, Computer Science); Susan Mango (University of Utah, Oncological Science); |
| Short Abstract: Functional transcription factor binding sites are often conserved multiple species. We have developed a method to incorporate the conservation scores into motif searching. We have shown that the method is highly effective in finding important binding sites. We have implemented our method into a user-friendly web server. |
| Long Abstract: Click Here |
| Poster S19 |
| In silico identification of a core regulatory network of OCT4 in human embryonic stem cells using an integrated approach |
| Lukas Chavez- Max-Planck-Institute for Molecular Genetics |
| Abha Bais (Max-Planck-Institute for Molecular Genetics, Department of Vertebrate Genomics); James Adjaye (Max-Planck-Institute for Molecular Genetics, Department of Vertebrate Genomics); Ralf Herwig (Max-Planck-Institute for Molecular Genetics, Department of Vertebrate Genomics); |
| Short Abstract: We have carried out an integrated analysis of high-throughput data (ChIP-on-chip and RNAi experiments along with promoter sequence analysis of putative target genes) and identified a core OCT4 regulatory network in human embryonic stem cells consisting of 33 target genes. |
| Long Abstract: Click Here |
| Poster S20 |
| In silico discovery of long-range cis-regulatory modules in humans |
| Geoff Macintyre- University of Melbourne |
| James Bailey (University of Melbourne, Computer Science and Software Engineering); Adam Kowalczyk (NICTA, Cancer Genomics); Izhak Haviv (Baker IDI Heart and Diabetes Institute, The Blood and DNA profiling Facility); |
| Short Abstract: We provide an in silico approach that accurately predicts interacting transcription factors (TFs) and their cis-regulatory module (CRM) locations in humans. Our method is successful in identifying long-range CRMs (searches 800kb encompassing target genes). Model output provides candidate interacting TFs for further experimental analysis of gene regulatory programs. |
| Long Abstract: Click Here |
| Poster S21 |
| Analysis of alternative splicing by next generation sequencing |
| Richard Hugues- Max Planck Institute for Molecular Genetic |
| Marcel H. Schulz (Max Planck Institute for Molecular Genetic, Computational Molecular Biology); Marc Sultan (Max Planck Institute for Molecular Genetic, Vertebrate Genomic); Asja Nürnberger (Max Planck Institute for Molecular Genetic, Vertebrate Genomic); Sabine Schrinner (Max Planck Institute for Molecular Genetic, Vertebrate Genomic); Daniela Balzereit (Max Planck Institute for Molecular Genetic, Vertebrate Genomic); Emilie Dagand (Max Planck Institute for Molecular Genetic, Vertebrate Genomic); Hans Lehrach (Max Planck Institute for Molecular Genetic, Vertebrate Genomic); Stefan haas (Max Planck Institute for Molecular Genetic, Computational Molecular Biology); Martin Vingron (Max Planck Institute for Molecular Genetic, Computational Molecular Biology); Marie-Laure Yaspo (Max Planck Institute for Molecular Genetic, Computational Molecular Biology); |
| Short Abstract: Second generation sequencing is now opening unprecedented new routes to address the analysis of entire transcriptomes. Here, we developped methods allowing the prediction and quantification of alternative splicing events from RNA-Seq data and validated a significant number of prediction by RT-PCR. |
| Long Abstract: Click Here |
| Poster S22 |
| How to predict the role of metabolites in sensing and signaling? |
| Sebastian Klie- Max-Planck Institute of Molecular Plant Physiology |
| Zoran Nikoloski (University of Potsdam, Institute of Biology and Biochemistry); Joachim Selbig (University of Potsdam, Institute of Biochemistry and Biology); |
| Short Abstract: Recent advances of high-throughput technologies, couple with existing structured biological knowledge, render it possible to predict the role of metabolites in sensing and signaling. Here, we propose a data-driven network-based approach for predicting putative candidates for sensing and signaling molecules based on data sets from E. coli. |
| Long Abstract: Click Here |
| Poster S23 |
| A fast and ?exible tool for 3C primer set generation |
| Sebastian Fröhler- Max-Delbrueck-Center for Molecular Medicine |
| Christoph Dieterich (Max-Delbrueck-Center for Molecular Medicine, Berlin Institute for Medical Systems Biology); |
| Short Abstract: We present the very first fully automated 3Cprimer design suite. Our software is highly flexiblemaking it useful for various variants of 3C.By using in-silico pcr, we efficiently screen a vastamount of candidate primer pair combinations for theoptimal set of primer pairs.We will present our algorithms and evaluate oursoftware in a wet-lab 3C experiment. |
| Long Abstract: Click Here |
| Poster S24 |
| Unravelling patterns of transcription factor binding sites |
| Anna-Lena Kranz- IPMB/University of Heidelberg |
| Roland Eils (DKFZ/University of Heidelberg/IPMB/Bioquant, Theoretical Bioinformatics/Bioinformatics and Functional Genomics); Rainer Koenig (University of Heidelberg/IPMB/DKFZ, Bioinformatics and Functional Genomics/Theoretical Bioinformatics); |
| Short Abstract: To gain new insights into transcriptional regulation we conducted an in silico promoter scan on the human genome. The distribution of binding sites of transcription factors showed distinct binding patterns which, in combination with networks of transcription factor interactions, may indicate new binding hypotheses of transcription factors to the DNA. |
| Long Abstract: Click Here |
| Poster S25 |
| m:Profiler - A Web Tool for Regulatory Motif Analyses |
| Meelis Kull- University of Tartu |
| Mirko Adari (University of Tartu, Department of Computer Science); Aivo Paas (University of Tartu, Department of Computer Science); Indrek Tamming (University of Tartu, Department of Computer Science); Jaak Vilo (University of Tartu, Department of Computer Science); |
| Short Abstract: m:Profiler is a web tool to perform computational analyses related to regulatory motifs and visualize the results.It has a set of built-in types of analyses, e.g. the enrichment analysis of all Transfac motifs in a given list of promoters.Analyses and visualizations can include data about TSSs, CRMs, chromatin, conservation etc. |
| Long Abstract: Click Here |
| Poster T1 |
| Modeling integrated biochemical networks: methods, advances and perspectives |
| Nuno Tenazinha- Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento (Lisboa) |
| Susana Vinga (Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento (Lisboa), Knowledge Discovery and Bioinformatics Group (KDBIO)); |
| Short Abstract: Signaling networks, gene regulation and metabolism have frequently been modeled independently. However, capturing their intertwinement is a key step for understanding how cellular systems develop integrated responses to their dynamically changing environment. We herein review current methodologies for modeling and analyzing integrated biochemical networks, illustrating their potentials with successful case-studies. |
| Long Abstract: Click Here |
| Poster U01 |
| TATA-variant identification, characterization and functional classification in plant genomes |
| Virginie BERNARD- URGV |
| Véronique BRUNAUD (URGV, bioinformatics); Alain LECHARNY (URGV, bioinformatics); |
| Short Abstract: Taking advantages of the TATA-box topological constraints we identified TATA-variants sharing the same constraints and being conserved in Arabidopsis thaliana and Oryza sativa. This work led to TATA-variant characterization distinguishing some motifs relative to the specific function, structure and expression of their related genes. |
| Long Abstract: Click Here |
| Poster U02 |
| Significance of hidden Markov model results |
| Lee Newberg- Wadsworth Center, New York State Department of Health |
| No additional authors |
| Short Abstract: For hidden Markov model / dynamic programming algorithm scans of large databases of sequence data, the ability to quickly estimate p-values at the 1e-12 level or smaller is necessary. We present a general approach that has quickly estimated p-values as low as 1e-4000. |
| Long Abstract: Click Here |
| Poster U03 |
| SNPlexViewer- a solution towards cost effective traceability system |
| Eyal Seroussi- The Agricultural Research Organization (ARO), Volcani Center |
| Yanir Seroussi (Monash University, Clayton School of Information Technology); Andrey Shirak (The Agricultural Research Organization (ARO), Volcani Center, Institute of Animal Sciene); Baruch Karniol (The Agricultural Research Organization (ARO), Volcani Center, Institute of Animal Sciene); |
| Short Abstract: DNA-based-traceability uses the animal own DNA-code for identity control. For this purpose we multiplexed 25 SNPs and to further decrease SNaPshot-genotyping expenses we introduced software, which facilitates the analysis of trace-files without size-standards. SNPlexViewer improves genotyping performance by aligning two trace-chromatograms while embedding within a normalized target-trace-file the reference size-standards. |
| Long Abstract: Click Here |
| Poster U04 |
| Investigation of a simple heuristic improving the speed of statistical alignments |
| Jesper Nielsen- Aarhus University |
| Rune Lyngsø (University of Oxford, Department of Statistics); Christian Pedersen (Aarhus University, Bioinformatics Research Center); Jotun Hein (University of Oxford, Department of Statistics); |
| Short Abstract: We investigate a simple heuristic for speeding up statisticalalignments. The idea is to use the results from pairwise alignmentsto estimate which multiple alignments are likely before actuallycomputing them. We investigate several ways to do this and achieve asignificant speed-up. |
| Long Abstract: Click Here |
| Poster U05 |
| Refinement of structure-based sequence alignments by Seed Extension |
| Chin-Hsien (Emily) Tai- National Cancer Institute, NIH |
| Changhoon Kim (National Cancer Institute, NIH, Center for Cancer Research); Byungkook Lee (National Cancer Institute, NIH, Center for Cancer Research); |
| Short Abstract: Refinement with Seed Extension (RSE) is a new procedure for refining a structure-based sequence alignment using a Seed Extension algorithm. With negligible increases in computation time, it improved the average accuracy of sequence alignments from all nine popular structure comparison/alignment programs, when tested against NCBI’s CDD alignments. |
| Long Abstract: Click Here |
| Poster U06 |
| Software tool for bulk annotation of genomic loci |
| Mali Salmon- EMBL-EBI |
| No additional authors |
| Short Abstract: Here we describe a collection of software tools developed for the efficient annotation of genomic loci. The programs automatically identify key features of interest, such as the location of experimental peaks within genes, their proximity to up- or downstream transcription start sites, and the presence of binding site motifs |
| Long Abstract: Click Here |
| Poster U07 |
| Multiple Motif Scanning to Identify Methyltransferases |
| Tanya Petrossian- University of California, Los Angeles |
| Steve Clarke (UCLA, Department of Chemistry and Biochemistry and the Molecular Biology Institute); |
| Short Abstract: This study seeks to refine the methyltransferase database by using the novel “Multiple Motif Scanning” program. HMM profiles and secondary structures were utilized to identify AdoMet-binding motifs. Statistical examination of these sequences allowed for motif refinement. Additionally, clustering analysis revealed probable substrates for the putative methyltransferases. |
| Long Abstract: Click Here |
| Poster U08 |
| Sequence context-specific profiles for homology searching |
| Andreas Biegert- Gene Center, LMU Munich |
| Johannes Soeding (Gene Center, LMU Munich, Computational Biology); |
| Short Abstract: In standard sequence searches, amino acids are compared one by one. We derive context-specific amino acid similarities from short windows centered on each query sequence residue. By employing our context-specific similarities in combination with NCBI BLAST, CS-BLAST achieves two-fold increased sensitivity at the same specificity and speed. |
| Long Abstract: Click Here |
| Poster U09 |
| Optimized pipeline for the analysis of mircoRNA sequences obtained from next-generation sequencing technologies |
| Marcel Grunert- Max Planck Institute for Molecular Genetics |
| Markus Schueler (Max Planck Institute for Molecular Genetics, Vertebrate Genomics / Computational Molecular Biology); Ilona Dunkel (Max Planck Institute for Molecular Genetics, Vertebrate Genomics); Silke Sperling (Max Planck Institute for Molecular Genetics, Vertebrate Genomics); |
| Short Abstract: We present an optimized data analysis pipeline for the processing and analysis of small RNA sequences obtained from Solexa next-generation sequencing data. The pipeline includes quality control, statistical reporting, whole genome mapping, several filtering steps, profiling of small RNAs by database annotations, and finally, the prediction of novel microRNAs. |
| Long Abstract: Click Here |
| Poster U10 |
| WebLab: a data-centric, knowledge-sharing bioinformatic platform |
| Ge Gao- Peking University |
| Xiaoqiao Liu (Peking University, Center for Bioinformatics, School of Life Sciences); Jianmin Wu (Peking University, Center for Bioinformatics, School of Life Sciences); Jun Wang (Peking University, Center for Bioinformatics, School of Life Sciences); Xiaochun Liu (Peking University, Center for Bioinformatics, School of Life Sciences); Shuqi Zhao (Peking University, Center for Bioinformatics, School of Life Sciences); Zhe Li (Peking University, Center for Bioinformatics, School of Life Sciences); Lei Kong (Peking University, Center for Bioinformatics, School of Life Sciences); Xiaocheng Gu (Peking University, Center for Bioinformatics, School of Life Sciences); Jingchu Luo (Peking University, Center for Bioinformatics, School of Life Sciences); |
| Short Abstract: In order to support biological researches, we have developed WebLab, a data-centric knowledge-sharing bioinformatic platform. Besides plentiful types of analysis tools, WebLab provides powerful data management function for both experimental data and scientific literature. Flexible sharing mechanism and group strategy are also provided to facilitate collaborative team work. |
| Long Abstract: Click Here |
| Poster U11 |
| ENTROPIC PROFILER – efficient whole genome analysis using information theory and statistical concepts |
| Susana Vinga- INESC-ID |
| Francisco Fernandes (INESC-ID, KDBIO); Ana T Freitas (INESC-ID/IST, KDBIO); Jonas S Almeida (MDAnderson Cancer Center, Biostat Appl Math); |
| Short Abstract: Entropic Profiles (EP) are local information plots that indicate overall conservation of motifs in genomes. They are based on Information Theory concepts, in particular the Renyi entropy of biological sequences. The present tool implementation, based on new data structures and algorithmic simplifications, allows to process whole genomes in few minutes. |
| Long Abstract: Click Here |
| Poster U12 |
| ADAPTdb/ADAPT - A Framework for the Analysis of ARISA Data Sets |
| Robert Schmieder- San Diego State University |
| Matthew Haynes (San Diego State University, Biology); Elizabeth Dinsdale (San Diego State University, Biology); Forest Rohwer (San Diego State University, Biology); Robert Edwards (San Diego State University, Computer Science); |
| Short Abstract: ADAPTdb/ADAPT presents a web-based system for the automatic analysis of ARISA data sets. The database ADAPTdb stores and maintains ITS regions along with information about their source organisms. ADAPT uses ADAPTdb to taxonomically characterize ARISA data sets. Additionally, ADAPT performs pathogenic and autotrophic/heterotrophic comparisons of organisms among different ARISA samples. |
| Long Abstract: Click Here |
| Poster U13 |
| Mining unique-m substrings from genomes |
| Kai Ye- European Bioinformatics Institute |
| Qilan Li (Leiden/Amsterdam Centre for Drug Research, Medicinal Chemistry); Ad IJzerman (Leiden/Amsterdam Centre for Drug Research, Medicinal Chemistry); Zhenyu Jia (University of California, Irvine, Department of Pathology and Laboratory Medicine); Paul Flicek (European Bioinformatics Institute, PANDA); Rolf Apweiler (European Bioinformatics Institute, PANDA); |
| Short Abstract: Information about unique substrings of genomes is fundamental but not sufficient for many genetic investigations. We propose an efficient (time and space) pattern growth approach to systematically mine all unique-m substrings, which have exactly one perfect match in the genome while all approximate matches must have more than m mismatches. |
| Long Abstract: Click Here |
| Poster U14 |
| LOCAS - a new lowest coverage assembler to support resequencing with ultra-short reads |
| Juliane Klein- University of Tuebingen |
| Korbinian Schneeberger (Max Planck Institute for Developmental Biology, Department of Molecular Biology); Stephan Ossowski (Max Planck Institute for Developmental Biology, Department of Molecular Biology); Detlef Weigel (Max Planck Institute for Developmental Biology, Department of Molecular Biology); Daniel H. Huson (University of Tuebingen, Faculty of Computer Science); |
| Short Abstract: We present LOCAS, a new assembly tool for short read sequence data. Incontrast to existing short read assemblers, which assume highcoverage of reads, LOCAS is aimed at assembling low-coveragedatasets. LOCAS is particularly suited forresequencing projects. We are using it in an Arabidopsis resequencingproject (1001 genomes). |
| Long Abstract: Click Here |
| Poster U15 |
| Evaluation of Association Measures for Motif Discovery |
| Pedro Ferreira- Centre for Genomic Regulation |
| Roderic Guigó (Centre for Genomic Regulation, Genome Bioinformatics Lab); |
| Short Abstract: Combinatorial motif discovery algorithms rely on association measures to assess the strength of co-occurrence between simple motifs. We surveyed 14 association measures previously applied in bioinformatics, data mining and language processing and performed an empirical evaluation in artificially generated datasets in order to better understand there similarities and differences. |
| Long Abstract: Click Here |
| Poster U16 |
| Command-line-based integration of online bioinformatics resources |
| Kazuki Oshita- Institute for Advanced Biosciences, Keio University |
| Masaru Tomita (Institute for Advanced Biosciences, Keio University, Environment and Information Studies); Kazuharu Arakawa (Institute for Advanced Biosciences, Keio University, Graduate School of Media and Governance); |
| Short Abstract: Here we present a software package that maps online bioinformatics resources as UNIX command-line tools that can be pipelined using EMBOSS Ajax Command Definition ontologies. The software package currently contains more than 50 tools, and is freely available from http://www.g-language.org/. |
| Long Abstract: Click Here |
| Poster U17 |
| Biological sequence motif discovery using feature selection in Conditional Random Field |
| Thanh Hai Dang- University of Antwerp |
| Alain Verschoren (University of Antwerp, Department of Mathematics and Computer Science); Kris Laukens (University of Antwerp, Department of Mathematics and Computer Science); |
| Short Abstract: Motif discovery plays important role in molecular biology. Most of computational methods developed so far are limited to gapless motifs and independent assumption between the positions within sequences. We hereby introduce a motif discovery method using feature selection in Conditional Random Field (CRF), which overcomes the above mentioned limitations. |
| Long Abstract: Click Here |
| Poster U18 |
| Computational motif discovery using extreme-valuedtuples from mutual information profiles |
| Sara Garcia- Signal Processing Laboratory, IEETA |
| Armando Pinho (Signal Processing Laboratory, IEETA, University of Aveiro); Holger Kantz ( Max Planck Institute for the Physics of Complex Systems, Nonlinear Time Series Analysis ); |
| Short Abstract: We propose a new methodology for computational motif discovery based on extreme-valued tuples, using information theory for assessing optimal tuple information measures based on the formalism of Shannon's entropy, and extreme value statistics for providing a framework for threshold-based selecting criteria. |
| Long Abstract: Click Here |
| Poster U19 |
| Application of VAMSAS enabled tools for the investigation of protein evolution. |
| James Procter- University of Dundee |
| Iain Milne (Scottish Crop Research Institute, Bioinformatics); Frank Wright (Biomathematics and Statistics, Scotland, Genetics); Pierre Marguerite (European Bioinformatics Institute, MSD); Andrew Waterhouse (Riken, Genome Sciences Centre); Dominik Lindner (Scottish Crop Research Institute, Bioinformatics); David Martin (University of Dundee, School of Life Sciences Research); Tom Oldfield (European Bioinformatics Institute, MSD); David Marshall (Scottish Crop Research Institute, Bioinformatics); Geoff Barton (University of Dundee, School of Life Sciences Research); |
| Short Abstract: Protein evolutionary analysis often involves the use of many programs.We demonstrate how it can be performed effectively using applicationsthat have been modified to dynamically exchange data; via the 'Visualization and Analysis of Molecular Sequences, Alignments, andStructures\\\\\\\\\\\\\\\' (VAMSAS) framework. |
| Long Abstract: Click Here |
| Poster U20 |
| Kalign2: high-performance multiple alignment of protein and nucleotide sequences allowing external features |
| Oliver Frings- Stockholm University |
| Timo Lassmann (Stockholm University, Stockholm Bioinformatics Center); Erik Sonnhammer (Stockholm University, Stockholm Bioinformatics Center); |
| Short Abstract: To make Kalign a versatile tool for large-scale alignment studies, we have dramatically improved its computational properties, while maintaining its high accuracy. Kalign 2 now supports the alignment of nucleotide sequences, and a newly introduced extension allows to include sequence annotation into the alignment process to improve alignment accuracy. |
| Long Abstract: Click Here |
| Poster U21 |
| A novel ab initio method finding microRNA clusters |
| Anthony Mathelier- CNRS-UPMC |
| Alessandra Carbone (CNRS-UPMC, Informatique); |
| Short Abstract: MicroRNAs are a class of endogenes whose expression profiles reflect origin and differentiation state of human cancers and tumours. We propose a novel ab initio approach searching for clusterized paralogous microRNAs in highly dense palindromic regions. miRNA precursors discrimination is based on 5 (physical and combinatorial) conditions only. |
| Long Abstract: Click Here |
| Poster U22 |
| G-language Genome Analysis Environment Version 2: Integrated workbench for computational genome sequence analysis |
| Kazuharu Arakawa- Institute for Advanced Biosciences, Keio University |
| Masaru Tomita (Institute for Advanced Biosciences, Keio University, Department of Environment and Information Studies); |
| Short Abstract: G-language Genome Analysis Environment is a software package written in Perl for genome sequence analysis compatible with BioPerl, especially focusing on bacterial genomes. Here we present the second version of the software, implemented with interactive shell and more than 200 analysis programs. The software is freely available at http://www.g-language.org/. |
| Long Abstract: Click Here |
| Poster U23 |
| The CluSTr database in 2009 |
| Craig McAnulla- EMBL - European Bioinformatics Institute |
| John Maslen (EMBL - European Bioinformatics Institute, InterPro team); Antony Quinn (EMBL - European Bioinformatics Institute, InterPro team); Sarah Hunter (EMBL - European Bioinformatics Institute, InterPro team); |
| Short Abstract: The CluSTr database offers an automatic classification of proteins from UniProtKB and other databases into groups of related proteins. The clustering is based on analysis of all pairwise similarities between protein sequences. New developments in CluSTr will be presented, including increased coverage, new protein datasets, and extended website functionality. |
| Long Abstract: Click Here |
| Poster U24 |
| Novel miRNA identification and target gene prediction in Glycine Max |
| Trupti Joshi- University of Missouri-Columbia |
| No additional authors |
| Short Abstract: We identified over 50 novel miRNAs from Illumina SBS sequencing of seven tissues in soybean, and validated some computationally predicted putative target genes. We also developed a soybean genome browser and incorporated the small RNA libraries, along with Solexa transcriptome sequencing data. The genome browser can be accessed at http://genomebrowser.missouri.edu/cgi-bin/hgGateway. |
| Long Abstract: Click Here |
| Poster U25 |
| Extraction of transcription factor binding sites from ChIP-Seq data through de novo TFBS motif identification. Application for EWS-Fli1 oncogenic transcription factor. |
| Valentina Boeva- Institut Curie |
| Noëlle Guillon (Institut Curie, Genetics and Biology of Cancers ); Franck Tirode (Institut Curie, Genetics and Biology of Cancers ); Olivier Delattre (Institut Curie, Genetics and Biology of Cancers ); Emmanuel Barillot (Institut Curie, Bioinformatics, biostatistics, epidemiology and computational systems biology of cancer); |
| Short Abstract: We propose a new algorithm for ChIP-Seq data analysis. It enables binding site extraction without the setting of an explicit threshold on the DNA fragment coverage. On EWS-Fli1 data, the algorithm showed significantly increased peak selection sensitivity with a very minor increase in the expected number of false positive hits. |
| Long Abstract: Click Here |
| Poster U26 |
| Revealing the Density-based Clustering Structure of the SwissProt database |
| Gabor Ivan- PhD Student |
| Vince Grolmusz (Eotvos Lorand University, Department of Computer Science); |
| Short Abstract: We classified 389046 sequences occurring in SwissProt using the OPTICS algorithm. We proposed a colouring scheme that is based on taxonomy information and helps analyzing the composition of clusters. We validated our results with the Pfam database using an OPTICS-specific quality measure and concluded that we obtained clusters of high quality. |
| Long Abstract: Click Here |
| Poster U27 |
| Identification of double coding regions in papillomaviruses based on nucleotide frequencies |
| Sten Ilmjärv- University of Tartu |
| Aare Abroi (Estonian Biocentre, .); Jaak Vilo (Quretec Ltd, .); Hedi Peterson (Quretec Ltd, .); |
| Short Abstract: Double coding regions in mammalian genomes have been widely studied due to frequent alternative splicing. We have identified double coding regions in papillomaviruses using amino acid sequence alignment based DNA conservation scoring. By comparing theoretical and real nucleotide frequencies we identified overlapping coding sequences for various papilloma types. |
| Long Abstract: Click Here |
| Poster U28 |
| Assessing Differences among Next-Generation Sequencing Software for Genomic Resequencing Alignment and Detection of Variation |
| James Cavalcoli- University of Michigan |
| Edgar Otto (University of Michigan, Pediatric Nephrology); James MacDonald (University of Michigan, Human Genetics); Friedhelm Hildebrandt (University of Michigan, Pediatrics); Gilbert Omenn (University of Michigan, Internal Medicine); |
| Short Abstract: While resequencing a portion of Human Chr19 to identify disease-causing variants, we assessed the capacity and variability of a number of next-generation sequence analysis software tools for their ability to align, assemble, and detect genomic variations (polymorphisms and indels) compared to the reference genome (hg18 build 36.3). |
| Long Abstract: Click Here |
| Poster U29 |
| An approach to subfamily assignment for large protein families |
| Yaoqing Shen- Universite de Montreal |
| Gertraud Burger (Universite de Montreal, Biochemistry); Franz Lang (Universite de Montreal, Biochemistry); |
| Short Abstract: We report a comprehensive bioinformatics analysis of the acyl-CoA dehydrogenase family (ACAD) family. We identified over 800 ACAD homologs from 250 species, recognized the subfamilies they belong to, compiled their taxonomic profiles, and traced back the evolution of the ACAD family. |
| Long Abstract: Click Here |
| Poster U30 |
| Characterization of transcriptome splicing structure using high-throughput RNA-seq |
| Jinze Liu- University of Kentucky |
| Kai Wang (University of Kentucky, Computer Science); Stephen Coleman (University of Kentucky, Veterinary Science); James Macleod (University of Kentucky, Veterinary Science); Jan Prins (University of North Carolina at Chapel Hill, Computer Science); |
| Short Abstract: MAPSPAN robustly identify splices in the transcriptome sampled via RNA-seq short reads. A novel unsupervised algorithm maps spliced reads onto the reference genome. Compared with existing approaches, MAPSPAN demonstrates higher sensitivity and selectivity in identifying splices and their coverage on known datasets. |
| Long Abstract: Click Here |
| Poster U31 |
| Does average viral genome sizes covary with that of microbes? A novel method applied to 150 metagenomes |
| Florent Angly- San Diego State University |
| Dana Willner (San Diego State University, Biology); Robert Schmieder (San Diego State University, Computer Science); Rebecca Vega-Thurber (Florida International University, Biology Department); Rob Edwards (San Diego State University, Computer Science); Forest Rohwer (San Diego State University, Biology); |
| Short Abstract: Viral genome vary in length by 1000X and are subject to different environmental pressures than microbes. We developed a method to estimate viral average genome size and applied it to 150 metagenomes to produce estimates for different biomes and verify if it covaries with microbial average genome size. |
| Long Abstract: Click Here |
| Poster U32 |
| Increasing Short Read Mapping Speed by Masking of Residues Sequence Reads |
| Stefan Henz- Max Planck Institute for Developmental Biology |
| Fabio de Bona (Friedrich Miescher Laboratory, Machine Learning in Biology); Stefan R. Henz (Max Planck Institute for Developmental Biology, Molecular Biology); Korbinian Schneeberger (Max Planck Institute for Developmental Biology, Molecular Biology); Stephan Ossowski (Max Planck Institute for Developmental Biology, Molecular Biology); Detlef Weigel (Max Planck Institute for Developmental Biology, Molecular Biology); Gunnar Rätsch (Friedrich Miescher Laboratory, Machine Learning in Biology); |
| Short Abstract: Next generation sequencing technologies produce massive amounts of shortsequence reads with varying quality of their positions which slow-down thealignment as many possible mismatches have to be considered.We employ a machine-learning-based algorithm, RTrim, performing areads' segmentation into mappable and unmappable regions. By appropriately maskinglow-quality positions we can map these reads quicker since fewer mismatches are required. |
| Long Abstract: Click Here |
| Poster U33 |
| Phylogeny in vertebrates of PEDF |
| Shivam sidana- JMIT |
| Niket ladha (JMIT, chemical); |
| Short Abstract: The PEDF gene first appears in vertebrates and our studies suggest that theregulation and biological actions of this gene are preserved across vertebrates. This analysis of the PEDF gene across phyla provides new information that will aid furthercharacterization of common functional motifs of this serpin in biological processes |
| Long Abstract: Click Here |
| Poster U34 |
| Algebraic approach to DNA sequence homology assessment |
| Andrzej Brodzik- The MITRE Corporation |
| No additional authors |
| Short Abstract: We investigate difference sets and related combinatorial objects as models for novel DNA sequence homology markers. We construct representations of DNA sequences in the difference set space, and compute their alignment. This procedure permits identification of homologous DNA sequences in a small fraction of the time required by standard methods. |
| Long Abstract: Click Here |
| Poster U35 |
| DistanceScan and Nash: Two novel tools for promoter analysis |
| Ekaterina Shelest- HKI, Hans Knoell Institute |
| Eugen Fazius (HKI, Hans Knoell Institute, Bioinformatics and systems biology); Vladimir Shelest (HKI, Hans Knoell Institute, Bioinformatics and systems biology); Reinhard Guthke (HKI, Hans Knoell Institute, Bioinformatics and systems biology); |
| Short Abstract: Nash is a motif-discovery tool based on a novel approach to the prediction of transcription factor binding sites (TFBS), which is alternative to widely used PWMs and HMMs. DistanceScan utilizes the method of distance distributions of TFBS pairs. It allows to select the functional combinations of motifs on non-random distances. |
| Long Abstract: Click Here |
| Poster U36 |
| Promoters and The Transcription Factors - a Simple Relation via The miRNA |
| Chanchal Mitra- University of Hyderabad |
| Padmavathi Putta (University of Hyderabad, Biochemistry); Luciano Milanesi (Institute of Biomedical Technology, Bioinformatics); |
| Short Abstract: We have identified a relatively small set of GC-rich 6-nucleotide and 7-nucleotidesequences around the TSS in human promoter sequences. These sequences are distributed on both sides of the TSS and are likely to be involved in recognition and binding of various factors. They are relatively uncommon elsewhere. |
| Long Abstract: Click Here |
| Poster U37 |
| ncSOLID a R package for non coding RNA digital sequencing |
| Raffaele Calogero- University of Torino |
| Cristina Della Beffa (University of Torino, Dipartimento di Scienze Cliniche e Biologiche); Francesca Cordero (University of Torino, Dipartimento di Scienze Cliniche e Biologiche); |
| Short Abstract: ncSOLID is a package for quantitative secondary analysis of non-coding transcriptome sequencing data generated with SOLID next-gen sequencing platform. The philosophy of the package is the organization of rna-seq data in a structure that allows the statistical detection of differential expression for ncRNAs, e.g. micro RNAs within Bioconductor framework. |
| Long Abstract: Click Here |
| Poster U38 |
| SeqAn - An efficient C++ library for sequence analysis |
| David Weese- Free University of Berlin |
| Tobias Rausch (International Max Planck Research School for Computational Biology and Scientific Computing, Molecular Genetics); Marcel Schulz (International Max Planck Research School for Computational Biology and Scientific Computing, Molecular Genetics); Anne-Katrin Emde (Free University of Berlin, Computer Science); Andreas Döring (Free University of Berlin, Computer Science); Knut Reinert (Free University of Berlin, Computer Science); |
| Short Abstract: SeqAn is an open source C++ library of efficient algorithms and data structures for the analysis of biological sequences. Using a template-based library design, SeqAn aims at providing (1) algorithms that are generic, fast and extensible and (2) data structures that allow the rapid prototyping of novel sequence analysis methods. |
| Long Abstract: Click Here |
| Poster U39 |
| Efficient computation of good neighbor seeds |
| LUCIAN ILIE- University of Western Ontario |
| SILVANA ILIE (Ryerson University, Mathematics); |
| Short Abstract: The current state of the art of homology search involves the use of (multiple) spaced seeds. Particularly important are the neighbor seeds which combine high sensitivity with reduced space. We give the only polynomial-time algorithm that computes better neighbor seeds than previous ones while being several orders of magnitude faster. |
| Long Abstract: Click Here |
| Poster U40 |
| Genome-wide computational analysis of eukaryotic core promoters |
| Holger Hartmann- Gene Center Munich |
| Claudia Gugenmus (Gene Center Munich, AG Soeding); Johannes Soeding (Gene Center Munich, AG Soeding); |
| Short Abstract: We have developed a sensitive method for core promoter analysis and detected all currently known but also several previously unknown motifs in yeast, fly and human. For yeast our results show that the core promoter is aligned to the +1 nucleosome rather than to the TSS. |
| Long Abstract: Click Here |
| Poster U41 |
| An new bioinformatics analysis tools framework at EMBL-EBI |
| Mickaël Goujon- European Bioinformatic Institute |
| Hamish McWilliam (European Bioinformatic Institute, External Services); Franck Valentin (European Bioinformatic Institute, External Services); Weizhong Li (European Bioinformatic Institute, External Services); Robert Langlois (European Bioinformatic Institute, External Services); Rodrigo Lopez (European Bioinformatic Institute, External Services); |
| Short Abstract: The popular framework to run analytical tools at the European Bioinformatic Institute has been redesigned to improve the user experience. The existing web interface and web services API have been reviewed and simplified to accommodate a larger audience and provide new and unique features that will greatly benefit the end-user. |
| Long Abstract: Click Here |
| Poster U42 |
| Development of SOLiD SAGE and tag counting and identification software |
| Xiequn Xu- Life Technologies |
| Patrick Gilles (Life Technologies, R&D ASA); Jennifer Kilzer (Life Technologies, R&D ASA); Kevin Clancy (Life Technologies, R&D ASA); Adam Harris (Life Technologies, R&D ASA); Rob Bennett (Life Technologies, R&D ASA); |
| Short Abstract: We developed the SOLiDTM SAGE kit by modifying serial analysis of gene expression (SAGE) to produce longer tags and adapting it to SOLiDTM sequencing platform. Easy-to-use software with a graphical user interface has also been developed for the post-sequencing data analysis for labs with moderate computational resources. |
| Long Abstract: Click Here |
| Poster U43 |
| EMBOSS: European Molecular Biology Open Software Suite |
| Peter Rice- European Bioinformatics Institute |
| Alan Bleasby (European Bioinformatics Institute, Rice Group); Jon Ison (European Bioinformatics Institute, Rice Group); Mahmut Uludag (European Bioinformatics Institute, Rice Group); |
| Short Abstract: EMBOSS is a mature package of software tools developed for the molecular biology community. It includes a comprehensive set of applications and C libraries for molecular sequence analysis and other tasks and integrates popular third-party software packages under consistent interfaces. |
| Long Abstract: Click Here |
| Poster U44 |
| Base-pairing profile local alignment kernels for functional RNA analyses |
| Kengo Sato- Japan Biological Informatics Consortium (JBIC) |
| Yutaka Saito (Keio University, Department of Biosciences and Informatics); Yasubumi Sakakibara (Keio University, Department of Biosciences and Informatics); |
| Short Abstract: We developed base-pairing profile local alignment (BPLA) kernels for discrimination and detection of functional RNA sequences using SVMs, and confirmed the effectiveness of our method by not only computational experiments but also expression analysis via qRT-PCR. |
| Long Abstract: Click Here |
| Poster U45 |
| Comparison of assembly strategies for high throughput de novo sequencing of bacterial genomes |
| Frank Panitz- University of Aarhus |
| Pernille Andersen (Faculty of Agricultural Sciences, Aarhus University, Department of Genetics and Biotechnology); Jakob Hedegaard (Faculty of Agricultural Sciences, Aarhus University, Department of Genetics and Biotechnology); Christian Bendixen (Faculty of Agricultural Sciences, Aarhus University, Department of Genetics and Biotechnology); Frank Panitz (Faculty of Agricultural Sciences, Aarhus University, Department of Genetics and Biotechnology); |
| Short Abstract: Different strategies were applied to generate optimal assemblies for two bacterial genome sequences based on de-novo sequencing using high-throughput 454 and Solexa paired-end reads. The quality of the hybrid assembly was assessed by the longest average contig size and also supported by gene prediction and comparative analysis to related genomes. |
| Long Abstract: Click Here |
| Poster U46 |
| Determining the Reading Frame in Short DNA Fragments |
| Hochul Lee- San Diego State University |
| Peter Salamon (San Diego State University, Mathematics); Rob Edwards (San Diego State University, Center for Microbial Sciences); Forest Rohwer (San Diego State University, Biology); Ben Felts (San Diego State University, Computational Science Research Center); Sajia Akhter (San Diego State University, Computational Science Research Center); |
| Short Abstract: We describe an implementation and preliminary tests for an intelligent algorithm to select the protein-encoding reading frame in short fragments of DNA without relying on extrinsic information. The system will speed up current computational analyses and apply many new analytical methods to metagenomic datasets. |
| Long Abstract: Click Here |
| Poster U47 |
| The GNUMAP Algorithm: Probabilistic Mapping of Oligonucleotides from Next-Generation Sequencing |
| Nathan Clement- Brigham Young University |
| Mark Clement (Brigham Young University, Computer Science); Quinn Snell (Brigham Young University, Computer Science); Evan Johnson (Brigham Young University, Statistics); |
| Short Abstract: GNUMAP addresses the analyses problems presented by an increase in the quantity of sequence data from next-generation sequencing technologies. The probabilistic nature of the mapping algorithm implemented in GNUMAP provides an accurate and efficient method for mapping large numbers of short sequences to a genome. |
| Long Abstract: Click Here |
| Poster U48 |
| A novel predictor of mucin-type O-glycosylation sites |
| Yong-Zi Chen- china agricultural university |
| No additional authors |
| Short Abstract: we attempted to improve the prediction of O-glycosylation sites in mammalian proteins by seeking a new encoding scheme, named CKSAAP encoding. With the ability of reflecting characteristics of the sequences surrounding mucin-type O-glycosylation sites, and with the assistance of Support VectorMachine (SVM), the result showed that this method was more powerful than the other methods. |
| Long Abstract: Click Here |
| Poster U49 |
| Raccess: A tool for genome-scale computation of structural accessibility of RNA transcripts. |
| Hisanori Kiryu- Computational Biology Research Center, AIST |
| Toutai Mituyama (Computational Biology Research Center, AIST, RNA Informatics Team); Kiyoshi Asai (University of Tokyo , Department of Computational Biology); |
| Short Abstract: We have developed a tool called Raccess for computing the accessibility of potential transcripts based on the Turner energy model of secondary structures. We have applied our tool to the entire human genome, and have analyzed the structural constraints imposed on the messenger RNAs and ancestral repeats. |
| Long Abstract: Click Here |
| Poster U50 |
| Conserved Sequences of West Nile Viral Proteins as candidate targets for vaccine design |
| TinWee Tan- National University of Singapore |
| QiYing Koo (National University of SIngapore, Biochemistry); M. Asif Khan (National University of SIngapore, Biochemistry); Shweta Ramdas (National University of Singapore, Biochemistry); Keun-Ok Jung (Johns Hopkins University School of Medicine, Pharmacology and Molecular Sciences); Jerome Salmon (Johns Hopkins University School of Medicine, Pharmacology and Molecular Sciences); Olivo Miotto (University of Oxford, MRC Centre for Genomics and Global Health); Vladimir Brusic (Dana-Farber Cancer Institute, Cancer Vaccine Center); J Thomas August (Johns Hopkins University School of Medicine, Pharmacology and Molecular Sciences); |
| Short Abstract: The focus of this study is to identify and characterize WNV protein regions that have exhibited strong conservation throughout the recorded history of the virus, and that are potential targets of T-cell immune responses, using various bioinformatics-based methods and correlation with available experimental data. |
| Long Abstract: Click Here |
| Poster U51 |
| Evolution of antigenic variant gene families within Plasmodium species |
| Diego Diez- Kyoto University |
| Nelson Hayes (Kyoto University, Kanehisa Laboratory); Susumu Goto (Kyoto University, Kanehisa Laboratory); |
| Short Abstract: We retrieved sequences involved in antigenic variation from different Apicomplexa and performed Pfam domain analysis. We found a gene family, which has undergone differential expansion in five Plasmodium species. We describe sequence and phylogenetic analyses on these families, revealing clues about the evolution of antigenic multi-gene families in other pathogens. |
| Long Abstract: Click Here |
| Poster U52 |
| CARMA: Correction and Reference Morphing Algorithm |
| Thomas Otto- Wellcome Trust Sanger Institute |
| Mandy Sanders (Wellcome Trust Sanger Institute , Pathogen Genomics); Matt Berriman (Wellcome Trust Sanger Institute, Pathogen Genomics); Chris Newbold (John Radcliffe Hospital, Institute of Molecular Medicine); |
| Short Abstract: Second generation sequencing technology enables deep, low cost resequencing across multiple strains and species. We have developed an algorithm that iteratively maps short reads to a reference sequence. At each cycle, CARMA attempts to correct errors, or morph the reference into a new strain, and then evaluates its success. |
| Long Abstract: Click Here |
| Poster U53 |
| CentroidFold: Predictions of RNA Secondary Structure for Estimating Accurate Base-pairs |
| Michiaki Hamada- Mizuho Information & Research Institute, Inc |
| Kengo Sato (Japan Biological Informatics Consortium, JBIC); Hisanori Kiryu (National Institute of Advanced Industrial Science and Technology (AIST), Computational Biology Research Center); Toutai Mituyama (National Institute of Advanced Industrial Science and Technology (AIST), Computational Biology Research Center); Kiyoshi Asai (University of Tokyo, Graduate School of Frontier Sciences); |
| Short Abstract: We developed software called CentroidFold for secondary structure predictionof RNA sequences, which includes the centroid estimator used in Sfoldas a special caseand is theoretically superior to MEA estimator used in CONTRAfold.A web server and stand-alone software are freely available athttp://www.ncrna.org/centroidfold/ |
| Long Abstract: Click Here |
| Poster U54 |
| On the quality of established datasets for benchmarking sequence database search and low-complexity handling tools: the ASTRAL compendium test case |
| Ioannis Kirmitzoglou- University Of Cyprus |
| Vasilis Promponas (University of Cyprus, Department of Biological Sciences); |
| Short Abstract: Benchmarking of sequence database search tools serves to establish protocols for routine or more elaborate searches. Low complexity regions (LCRs) complicate this procedure, requiring special handling.We provide new insights on validating the performance of relevant methods, taking into account LCRs, based on the widely used ASTRAL compendium datasets. |
| Long Abstract: Click Here |
| Poster U55 |
| The SSAHA2 software pipeline for the mapping of DNA sequencing reads and genotype calling |
| Hannes Ponstingl- Wellcome Trust Sanger Institute |
| Yong Gu (Wellcome Trust Sanger Institute, Sequencing Informatics); Zemin Ning (Wellcome Trust Sanger Institute, Sequencing Informatics); |
| Short Abstract: The SSAHA2 software pipeline efficiently maps DNA sequencing reads onto a genomic reference sequence. A genotype call of the consensus sequence can be produced taking into account a heuristic score of the mapping quality. Reads from most types of sequencing platforms are supported including paired-end sequencing reads. |
| Long Abstract: Click Here |
| Poster U56 |
| EMLIB: a C++ library to manage transcripts and genomic variations |
| Matteo Cereda- Scientific Institute IRCCS E.Medea |
| Manuela Sironi (Scientific Institute IRCCS E.Medea, Bioinformatics Laboratory); Uberto Pozzoli (Scientific Institute IRCCS E.Medea, Bioinformatics Laboratory); |
| Short Abstract: EMLIB is a C++ library containing a novel hierarchy of classes useful to define transcripts, to manage sequence variations and to calculate position-specific quantitative features in a “variation dependent” way. EMLIB provides an intuitive and powerful environment to gain insights about the effect of genomic variations. |
| Long Abstract: Click Here |
| Poster U57 |
| BioHDF: Open binary file formats for large-scale data management - Project Update |
| Mark Welsh- Geospiza, Inc. |
| Todd Smith (Geospiza, Inc., CEO); N. Eric Olson (Geospiza, Inc., Product Development); Mike Folk (The HDF Group, -); |
| Short Abstract: BioHDF extends a mature Open Source technology for the storage of scientific data, Hierarchical Data Format, with features specific to Next Generation Sequencing. Initial prototyping of BioHDF has demonstrated clear benefits to storing sequences and their reference alignments in this structured binary format, including file compression and fast data retrieval. |
| Long Abstract: Click Here |
| Poster U58 |
| Sequence analysis scale-up and acceleration using Grid and Cloud Computing yield efficient analyses of HIV-1 variants and other viruses |
| TinWee Tan- National University of Singapore |
| Yongli Hu (National University of Singapore, Biochemistry); Shen Jean Lim (National University of Singapore, Biochemistry); M Asif Khan (National University of Singapore, Biochemistry); Mark De Silva (National University of Singapore, Biochemistry); Kuan Siong Lim (National University of Singapore, Biochemistry); Martti Tammi (National University of Singapore, Biochemistry); J Thomas August (Johns Hopkins University School of Medicine, Pharmacology and Molecular Sciences); |
| Short Abstract: Sequence inundation in current paradigm affects the speed and scalability of immunoinformatics-driven sequence analysis of infectious agents such as HIV-1. To overcome these restrictions, we have customized and benchmarked bioinformatics analyses on Grid and Cloud computing and obtained good results of enhanced efficacy and scalability. |
| Long Abstract: Click Here |
| Poster U59 |
| Comparative analysis of local compositional complecity in plant encoded proteins |
| Vasilis Promponas- University of Cyprus |
| Eleni Mytilineou (University of Cyprus, Department of Biological Sciences); Ioannis Kirmitzoglou (University of Cyprus, Department of Biological Sciences); |
| Short Abstract: Different approaches have identified numerous low complexity regions (LCR) in protein sequences. However, few systematical studies exist for elucidating their possible biological significance.We take advantage of the completetion of two model plant organism genomes to investigate their functional roles and the mechanisms responsible for LCR appearance, maintenance or modification. |
| Long Abstract: Click Here |
| Poster U60 |
| Detecting biases in Next Generation Sequence data |
| Rudiger Brauning- AgResearch |
| Anar Khan (AgResearch, Bioinformatics, Mathematics and Statistics); Ken Dodds (AgResearch, Bioinformatics, Mathematics and Statistics); Jo-Ann Stanton (Anatomy and Structural Biology, University of Otago); Chris Mason (Anatomy and Structural Biology, University of Otago); |
| Short Abstract: A recent study (1) looked at systematic bias in amplicon sequencing by NGS platforms. We look at WGS data generated for the Watson genome project using the 454 platform. After filtering for identical reads we specifically analyse bias at the beginning of each sequence read.(1) Harismendy et al., Genome Biology 2009, |
| Long Abstract: Click Here |
| Poster U61 |
| VARiD: Variation Detection in Color-Space and Letter-Space |
| Adrian Dalca- University of Toronto |
| Michael Brudno (University of Toronto, Computer Science); |
| Short Abstract: We present VARiD - a Hidden Markov Model for SNP and Indel identification with AB-SOLiD color-space and regular letter-space reads. VARiD combines both types of data in a single framework which allows for homozygous and heterozygous calls. On both simulated and real datasets VARiD demonstrates very high specificity and sensitivity. |
| Long Abstract: Click Here |
| Poster U62 |
| Statistically Significant Ranking of NGS Differential Peaks |
| Bryan Beresford-Smith- NICTA |
| Adam Kowalczyk (NICTA, VRL); Thomas Conway (NICTA, VRL); Izhak Haviv (Baker IDI Heart and Diabetes Institute, The Blood and DNA Profiling Facility); Richard Tothill (Baker IDI Heart and Diabetes Institute, The Blood and DNA Profiling Facility); |
| Short Abstract: Several statistics are presented for replacing ad hoc heuristics such as fold-ratio for the identification of differential peaks in NGS data. The statistical framework leads naturally to a power law for peak significance versus number of reads. The tests have been applied to ChIP-Seq data sets to demonstrate their usefulness. |
| Long Abstract: Click Here |
| Poster U63 |
| Prediction of Protein Disordered and Ordered Region |
| Meijing Li- Chungbuk national university |
| Yoon Kyeong Lee (Chungbuk National University, Signal Transduction and Systems Biology Laboratory); Jin Hyoung Park (Chungbuk National University, Database/Bioinformatics Laboratory); Heon Gyu Lee (Electronics and Telecommunications Research Institute, Postal& Logistics Research Dep.); Hak Yong Kim (Chungbuk National University, Signal Transduction and Systems Biology Laboratory); Keun Ho Ryu (Chungbuk National University, Database/Bioinformatics Laboratory); |
| Short Abstract: In this paper, we proposed emerging sequence-based prediction method for identifying protein disordered and ordered region from protein sequence. In the experiment, disordered sequence data: DisProt, ordered sequence data: PDB as training data. The test data is from CASP7. The experiment result is better than result of published prediction methods. |
| Long Abstract: Click Here |
| Poster U64 |
| Positive selection contributes to the emergence of new HIV-1 lineages while high substitution rates determines viral pathogenesis in epidemically linked patients |
| Elcio Leal- Federal University of Sao Paulo |
| No additional authors |
| Short Abstract: The contribution of HIV-1 diversity to AIDS was evaluated in epidemically linked individuals composed by one blood donor and two blood recipients. The same HIV-1 source, transmitted during blood transfusion, indicated positive selection as a key factor to the emergence of lineages while substitution rates determine the disease outcome. |
| Long Abstract: Click Here |
| Poster U65 |
| Benchmarking promoter prediction software |
| Thomas Abeel- VIB-UGent |
| Yvan Saeys (VIB-UGent, Plant Systems Biology); Yves Van de Peer (VIB-UGent, Plant Systems Biology); |
| Short Abstract: Recently many new promoter prediction programs (PPPs) have emerged, but a common benchmarking strategy is lacking. We propose a multi-faceted protocol as a gold standard for PPP evaluation. We benchmarked 17 PPPs and further investigated the best four. The importance of PPPs will only increase, as more genomes are sequenced. |
| Long Abstract: Click Here |
| Poster V01 |
| Dali server in 2009 |
| Liisa Holm- University of Helsinki |
| Hitomi Hasegawa (University of Helsinki, Institute of Biotechnology); |
| Short Abstract: The Dali server is a network service for comparing protein structures in 3D. It has been used to systematically scan newstructures against the Protein Data Bank (PDB) for some 15 years. In favourable cases, comparing 3D structures may reveal biologically interesting similarities that are not detectable by comparing sequences. |
| Long Abstract: Click Here |
| Poster V02 |
| A Protein Surface Comparing Method using Structure Factor |
| KWANG SU JUNG- CBITRC, CHUNGBUK NATIONAL UNIV |
| NAM HEE YU (CBITRC, CHUNGBUK NATIONAL UNIV, COMPUTER SCIENCE); KEUN HO RYU (CBITRC, CHUNGBUK NATIONAL UNIV, COMPUTER SCIENCE); YONG JE CHUNG (CBITRC, CHUNGBUK NATIONAL UNIV, LIFE SCIENCE); |
| Short Abstract: Proteins need to combine other substrates or proteins to perform their function, and proteins which have similar actives sites have similar function.We suggest a method to compare partial surfaces of proteins using structure factors and phase angles. Our work can be adopted to produce proteins which have more functionality. |
| Long Abstract: Click Here |
| Poster V03 |
| Public archive for structural variants. |
| Jonathan Hinton- European Bioinformatics Institute |
| Ilkka Lappalainen (EBI, EGA); Mario Caccamo (EBI, EGA); Lars Feuk (The Hospital for Sick Children, The Centre for Applied Genomics); Vasudev Kumanduri (EBI, EGA); Paul Flicek (EBI, Vertebrate Genomics); Margie Manker (The Hospital for Sick Children, The Centre for Applied Genomics); Steve Scherer (The Hospital for Sick Children, The Centre for Applied Genomics); |
| Short Abstract: In resent years we have seen an explosion in studies describing human structural variation. The increasing quality and quantity brings new insight to our understanding of the complexity of the human genome. We propose a permanent archive to store, accession and distribute the different types of experimentally identified structural variation. |
| Long Abstract: Click Here |
| Poster V04 |
| A new software to study atom-atom interactions in protein complex interfaces |
| Tomas Norambuena- Pontificia Universidad Catolica de Chile |
| Francisco Melo (Pontificia Universidad Catolica de Chile, Molecular Genetics and Microbiology); |
| Short Abstract: We have developed a new computer software intended for the analysis and study of binding interfaces in different molecular complexes such as protein-nucleic acids and protein-small ligands. The software is highly customizable and has many features to further characterize the type of interactions that occur at the complex interface. |
| Long Abstract: Click Here |
| Poster V05 |
| Toward the prediction of the survival of alternative splice variants of human proteins |
| Hedi Hegyi- Institute of Enzymology |
| Lajos Kalmar (Inst Enzymology, N/A); |
| Short Abstract: According to current estimations 95% of multi-exonic human genes undergo alternative splicing with 6 splice variants/protein. However, only 11 human isoform structures are in PDB. We analyze human splice variants for length and hydrophobic surface energies. We find several limiting constraints to apply to eliminate/confirm the survival of many isoforms. |
| Long Abstract: Click Here |
| Poster V06 |
| STRUCTURE-BASED PREDICTION OF ANTIBODY EPITOPES |
| Petr Ponomarenko- Novosibirsk State University, Russia |
| Ruben Abagyan (The Scripps Research Institute, Molecular Biology); Philip Bourne (University of California, Skaggs School of Pharmacy & Pharmaceutical Science and Sun Diego Supercomputer Center); Julia Ponomarenko (University of California, Skaggs School of Pharmacy & Pharmaceutical Science and Sun Diego Supercomputer Center); |
| Short Abstract: We present a novel method for antibody epitope prediction in protein antigens of given structure. The method uses sequence and structural properties of epitopes known from 3D structures of antibody-protein complexes and supervised machine learning. The performance of the method exceeds other available structure-based methods for antibody epitope prediction. |
| Long Abstract: Click Here |
| Poster V07 |
| Considerations for algorithm selection and experimental design in detection of copy number variations in cancer. |
| Beth Wilmot- Oregon Health & Science University |
| Ping-Hsun Hsieh (Oregon Health & Science University, Oregon Clinical and Translational Research Institute); Shannon McWeeney (Oregon Health & Science University, Oregon Clinical and Translational Research Institute, Div. of Biostatistics, Dept. of Public Health and Prev. Med); |
| Short Abstract: DNA copy number variations (CNVs) are a significant and ubiquitous source of human genetic variation in cancer. We used Affymetrix 6.0 SNP arrays to evaluate how the choice of algorithm and associated parameters impacted the analysis of acquired Uniparental Disomy (aUPD) in clinically phenotyped myeloproliferative disorder (MPD) patient samples. |
| Long Abstract: Click Here |
| Poster V08 |
| Identify the dynamic domain of protein by the protein fixed-point model |
| Chih-Hao Lu- China Medical University |
| No additional authors |
| Short Abstract: We have developed a hybrid approach combined with structure and dynamics features for classification of protein domains. We use the protein fixed-point model and the clustering method to cluster the residues which belong to the same dynamic domain. Our approaches are quite simple and efficient for protein domain decomposed. |
| Long Abstract: Click Here |
| Poster V09 |
| Identifying structural elements associated with RNA families sharing biological function |
| Miler Lee- University of Pennsylvania School of Medicine |
| Junhyong Kim (University of Pennsylvania, Biology); |
| Short Abstract: We explore the extent to which RNA structural motifs can be associated with biological function across different RNA families. Using a compact encoding, we decompose RNA structures into parts and show that particular motifs are enriched for functional attributes as defined by an ontology we automatically generate from Wikipedia. |
| Long Abstract: Click Here |
| Poster V10 |
| Homology modelling based protein functional residues prediction |
| Raquel Minardi- Genoscope / IG / CEA |
| No additional authors |
| Short Abstract: We propose a methodology to predict protein function based on structural data. We build 3D homology-based models for the family, computing and analyzing structural cavities using HMM, aligning their structures and clustering the family into subgroups of similar cavity residues profiles. After that we use a molecular docking approach with possible ligands. |
| Long Abstract: Click Here |
| Poster W001 |
| Linguistic Analysis of Unknown Metagenomic Sequences |
| Victor Seguritan- San Diego State University / Claremont Graduate University |
| No additional authors |
| Short Abstract: A method is needed to assign functions to unknown sequences which does not rely on sequence homology alone. The linguistic elements, syntax and semantics, of several model proteins will be used to assign functions to unknown metagenomes in a manner similar to the concept of understanding human language. |
| Long Abstract: Click Here |
| Poster W002 |
| From protein local structure prediction to local flexibility prediction: flexibility versus structural prediction errors. |
| Aurélie Bornot- INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Université Paris Diderot - Paris 7 |
| Catherine Etchebest (INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Université Paris Diderot - Paris 7, ); Alexandre G. de Brevern (INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Université Paris Diderot - Paris 7, ); |
| Short Abstract: In this study, we addressed the question of the structural “predictability” of a protein sequence with regards to its structural flexibility properties.Protein local structure dynamics were analyzed using X-ray experiments and molecular dynamics simulations. Finally, an original flexibility prediction method from protein sequence was proposed. |
| Long Abstract: Click Here |
| Poster W003 |
| Prediction of thermodynamic stability of transmembrane helices reveals architectural patterns of integral membrane proteins |
| Joke Reumers- Vrije Universiteit Brussel |
| Joost Schymkowitz (Vrije Universiteit Brussel, VIB Switch Laboratory); Frederic Rousseau (Vrije Universiteit Brussel, VIB Switch Laboratory); Luis Serrano (Centre for Genomic Regulation , Systems Biology Programme); |
| Short Abstract: With Casablanca we propose a statistical thermodynamics algorithm that predicts transmembrane helices based on simple structural assumptions and thus is able to distinguish structurally important helices from functional helices. We demonstrate the method is accurate on a large data set and can be used for genome wide screening. |
| Long Abstract: Click Here |
| Poster W004 |
| Sasichandran: A sequence specific dihedral angle database and evaluation tool |
| S. M. Minhaz Ud-Dean- University of Dhaka |
| MAHDI MOOSA (University of Dhaka, Genetic Engineering and Biotechnology); |
| Short Abstract: Estimation and prediction of dihedral angle can be used to validate both theoretically predicted and experimentally determined structures. This idea is used to develop a sequence specific dihedral angle prediction tool, Sasichandran. This tool can also evaluate a protein structure using information of sequence specific distribution of Ramachandran angles. |
| Long Abstract: Click Here |
| Poster W005 |
| Chemocavity: Specific Concavity in Protein Reserved for the Binding of Biologically Functional Small Molecules |
| Shinji Soga- Astellas Pharma Inc. |
| Hiroki Shirai (Astellas Pharma Inc., Molecular Medicine Research Laboratories, Drug Discovery Research); Masato Kobori (Astellas Pharma Inc., Molecular Medicine Research Laboratories, Drug Discovery Research); Noriaki Hirayama (Tokai University School of Medicine, Basic Medical Science and Molecular Medicine); |
| Short Abstract: Understanding what characteristics of the site determine the binding ability of a functional small molecule is not so easy. Here we introduced an index characterizing the binding site based on the concurrency rate of amino acid and identified a specific site on a protein for a particular functional small molecule. |
| Long Abstract: Click Here |
| Poster W006 |
| btmxMotif: A program to predict burial status motifs in transmembrane beta barrel strands based on expectation maximization |
| Sikander Hayat- Saarland University |
| No additional authors |
| Short Abstract: We employ expectation maximization as described in the MEME algorithm to discover motifs based on the predicted burial status of TM residues in Transmembrane beta-Barrel strands. The predicted burial status of TM residues is obtained using a statistical method named BTMX. |
| Long Abstract: Click Here |
| Poster W007 |
| Predicting protein function from domain content |
| Kristoffer Forslund- Stockholm Bioinformatics Centre |
| Erik Sonnhammer (Stockholm University, Stockholm Bioinformatics Centre); |
| Short Abstract: We present a framework for representing how sets of protein sequence domains give rise to protein function. This work extends previous approaches that map GO terms to Pfam domains by considering the functional implications of combinations of several domains. Probabilistic and rule-based models are evaluated and implemented as function predictors. |
| Long Abstract: Click Here |
| Poster W008 |
| Model Quality Assessment for Membrane Proteins |
| Sebastian Kelm- University of Oxford |
| Jiye Shi (UCB Group, ROC); Charlotte M. Deane (University of Oxford, Statistics); |
| Short Abstract: Membrane proteins are among the most important classes of drug targets, but experimentally obtaining their 3D structure is hard. Accuracte computational structure prediction is therefore of great value.With this aim in mind, we present a new suite of Model Quality Assessment Programmes for membrane proteins, which enable better model selection. |
| Long Abstract: Click Here |
| Poster W009 |
| Structure and evolution of protein allosteric sites |
| Alejandro Panjkovich- Institute of Biotechnology and Biomedicine, Universitat Autonoma de Barcelona |
| Xavier Daura (Catalan Institution for Research and Advanced Studies (ICREA), Institute of Biotechnology and Biomedicine (IBB), Universitat Autonoma de Barcelona); |
| Short Abstract: Protein ligand binding sites in general and allosteric sites in particular are of great interest, both in the applied context of drug development and in the academic understanding of allosterism. We performed a large-scale study on the evolution and structure of ligand binding sites, involving thousands of protein families. |
| Long Abstract: Click Here |
| Poster W010 |
| Relationships between the quality of homology models and the accuracy of ligand-protein docking results |
| Annalisa Bordogna- Universita' degli Studi di Milano - Bicocca |
| Alessandro Pandini (National Institute for Medical Research, London, Division of Mathematical Biology); Laura Bonati (Universita' degli Studi di Milano - Bicocca, DISAT); |
| Short Abstract: We investigated how the quality of homology models can affect the accuracy of ligand-docking experiments.Our results demonstrated that the quality of the modelled binding site, assessed by comparison to the native and the template protein structure, is an informative measure to predict the accuracy of the docking result. |
| Long Abstract: Click Here |
| Poster W011 |
| What kind of atoms are there? Natural atomic types from PDB and their relevance for structural modeling. |
| Enrico Pieroni- CRS4 |
| Maria Valentini (CRS4, Bioinformatics Lab); Detlef Walter Maria Hofmann (CRS4, Renewable Energy); |
| Short Abstract: We present a knowledge-based Force Field obtained by parsing PDB protein-ligand complexes to automatically identify natural atomic types and Force Field parameters. Advantages are: long range interactions automatically taken into account, interaction description relies only on natural interacting pairs, Hydrogen coordinates and partial charges calculations become obsolete. |
| Long Abstract: Click Here |
| Poster W012 |
| Computing Structures of Symmetric Homo-oligomeric Protein Complexes |
| Amarda Shehu- George Mason University |
| Christopher Miles (George Mason University, Computer Science); Amarda Shehu (George Mason University, Computer Science); |
| Short Abstract: We propose a method to compute symmetric homo-oligomeric protein structures assembled from a monomer of known semi-rigid structure. Geometric considerations rapidly extract candidatestructures from a protein complex database. Functional interfaces andphysico-chemical considerations further narrow predictions. The methodpresents a first step toward the design of large protein complexes. |
| Long Abstract: Click Here |
| Poster W013 |
| New Local Structure Properties for Creating Local Structure Alphabets |
| Grant Thiltgen- University of California, Santa Cruz |
| Kevin Karplus (University of California, Santa Cruz, Biomolecular Engineering); |
| Short Abstract: Combining local structure alphabets with sequence information has been shown to improve template searches. Our lab explores new structural features in order to create new alphabets. One feature is r_rot, and combining this feature with torsion angles and hydrogen bonds shows improvements over using these features alone. |
| Long Abstract: Click Here |
| Poster W014 |
| FREAD revisited: database search loop prediction |
| Yoonjoo Choi- Oxford University |
| No additional authors |
| Short Abstract: Over recent years, database search methods have been ignored. In light of the continued rapid expansion in the number of known protein structures we have re-evaluated FREAD, a database search method. In a direct comparison to MODELLER and other ab initio methods, FREAD is found to perform significantly better for an identifiable subset of loops. |
| Long Abstract: Click Here |
| Poster W015 |
| Structural rearrangement in the TCRpMHC formation in reaction to agonistic and antagonistic peptides |
| Bernhard Knapp- Medical University of Vienna |
| Wolfgang Schreiner (Medical University of Vienna, Biomedical Computersimulation and Bioinformatics); |
| Short Abstract: We present series of molecular dynamics simulations of two different TCRpMHC complexes. The first complex contains an agonistic peptide, the second an antagonistic one. The structural rearrangement in the CDRs of the TCRs in reaction to the different peptides is characterized. |
| Long Abstract: Click Here |
| Poster W016 |
| Comparison of proteins flexibilities by self-organizing maps: the test case of SH3 and its mutants |
| Domenico Fraccalvieri- Università degli Studi di Milano - Bicocca |
| Alessandro Pandini (National Institute for Medical Research, Division of Mathematical Biology); Fabio Stella (Università degli Studi di Milano - Bicocca, Dipartimento di Informatica Sistemistica e Comunicazione); Laura Bonati (Università degli Studi di Milano - Bicocca, Dipartimento di Scienze dell'Ambiente e del Territorio); |
| Short Abstract: A use of self-organizing maps in the analysis of molecular dynamics data is presented. The method was tested on a group of mutants of the SH3 domain and allowed to easily recover information about differences in the domain flexibilities that affect the biological function. |
| Long Abstract: Click Here |
| Poster W017 |
| Cryo-EM study and 3-D Structure determination of pore forming toxin |
| Somnath Dutta- National Institute of Cholera nad Enteric Diseases |
| No additional authors |
| Short Abstract: Mature Pore Forming Toxin (PFT) is 100-times more effective than truncated PFT. 3D structure of both types of PFTS is determined using cryo-EM and single particle analysis technique. Docking was also performed and 3D structure was observed using CHIMERA. Good structural differences explain the less pore formation activity and also explain pore formation mechanism. |
| Long Abstract: Click Here |
| Poster W018 |
| Modeling protein motions and ordering NMR models with the help of mass transportation theory |
| Sergey Nikolenko- Steklov Mathematical Institute |
| Eugene Stepanov (St. Petersburg State University of Information Technology, Mechanics & Optics, IT); Monica Zoppè (Institute of Clinical Physiology, National Research Council, Pisa, Italy, Laboratory of Molecular Biology); Yury Porozov (Institute of Clinical Physiology, National Research Council, Pisa, Italy, Laboratory of Molecular Biology); |
| Short Abstract: Knowledge about motion is crucial for understanding the proteins' functions. It is possible to reconstruct a sequence of conformations defining a motion on the basis of NMR data. To solve the problem of ordering different conformations we use a mathematical model based on evaluation of cost of mass transfer during conformational transition. |
| Long Abstract: Click Here |
| Poster W019 |
| Annotating Functional Residues of the Melanocortin-4 Receptor |
| Yana Bromberg- Columbia University |
| Burkhard Rost (Columbia University, Biochemistry and Molecular Biophysics); |
| Short Abstract: Using the example of the human melanocortin-4 receptor, we present a novel approach to prediction of functionally important residues from sequence. We computationally quantify functional consequences of all possible substitutions at each sequence position and compile per-residue importance scores. Our predictions correlate well with known functional sites. |
| Long Abstract: Click Here |
| Poster W020 |
| A density based approach to define structural alphabets |
| Alessandro Pandini- National Institute for Medical Research |
| Jens Kleinjung (National Institute for Medical Research, Division of Mathematical Biology); |
| Short Abstract: We present a new approach to extract representative fragments that are attractors in protein structure space. Highly populated attractors are also expected to be the most energetically stable conformations.The density based structural alphabets are both optimal to reconstruct known proteins and informative to describe the most favourable conformations. |
| Long Abstract: Click Here |
| Poster W021 |
| Visualization and modeling of protein motion. Autodesk Maya as a reliable and fast instrument for macromolecular dynamic representation. |
| Yuri Porozov- Insitute of Clinical Physiology. CNR |
| Raluca Andrei (Scuola Normale Superiore, Lab of Molecular Biology); Monica Zoppe' (Scientific Visualization Unit, Inst. of Clinical Physiology CNR); |
| Short Abstract: An approach for dynamic modeling of protein behavior based on 3D animation software and artificial implementation of forces influencing protein motion is presented. Evaluation of the method using NMR models of Calcium-free Calmodulin shows that it is possible to use it as powerful tool for protein visualization and motion prediction. |
| Long Abstract: Click Here |
| Poster W022 |
| SitesIdentify: Prediction of functional sites on the surface of proteins |
| Tracey Bray- The University of Manchester |
| Pedro Chan (The University of Manchester, Faculty of Life Sciences); Richard Greaves (The University of Manchester, Faculty of Life Sciences); Salim Bougouffa (The University of Manchester, Faculty of Life Sciences); Andrew Doig (The University of Manchester, Manchester Interdisciplinary Biocentre); Jim Warwicker (The University of Manchester, Faculty of Life Sciences); |
| Short Abstract: We present a functional site prediction tool, SitesIdentify, which predicts the location of a functional site on the surface of a protein. We have compared our results to other publicly available tools and have provided our method via a web server at www.manchester.ac.uk/bioinformatics/sitesidentify |
| Long Abstract: Click Here |
| Poster W023 |
| The Extended RNAMute and its Applications |
| Alexander Churkin- Ben Gurion University of the Negev |
| Danny Barash (Ben Gurion University of the Negev, Department of Computer Science); |
| Short Abstract: RNAMute is a bioinformatics application that aims to solve the RNA mutation predictionproblem. Given an RNA sequence, the goal is to compute the minimal number of mutations required to disrupt important secondary structure motifs. The extended RNAMute offers an advanced way to perform efficient and reliable mutation predictions. |
| Long Abstract: Click Here |
| Poster W024 |
| Using multi-data hidden Markov models trained on local neigh-borhoods of protein structure to predict residue-residue contacts |
| Patrik Björkholm- Stockholm Bioinformatics Center |
| No additional authors |
| Short Abstract: We propose a novel hidden Markov model based method for predicting residue-residue contacts from protein sequences using as training data homologous sequences, predicted secondary structure and a library of local neighborhoods (local descriptors of protein structure). The library consists of recurring structural entities in-corporating short-, medium- and long-range interactions. |
| Long Abstract: Click Here |
| Poster W025 |
| A Quantitative Pan-Receptor Predictive Method for Peptide Recognized by the SH2 Domain Family |
| Hao Zhang- Technical University of Denmark |
| No additional authors |
| Short Abstract: Src-homology 2 (SH2) domain is the largest class of known phosphotyrosine recognition structures. Characterization of the binding specificity is of pivotal importance. The challenge for both experimental and computational approaches is its large genetic diversity. We present a neural network method that leverages information from neighbouring receptors to unknowns. |
| Long Abstract: Click Here |
| Poster W026 |
| The Restricted Protein Redesign Problem: Efficient Search via Restricted Dead-End Elimination |
| Maria Safi- University of Toronto |
| No additional authors |
| Short Abstract: Dead-End Elimination (DEE) has emerged as a powerful conformational search technique enabling structure-based, computational protein redesign. We present rDEE as the solution of choice, when the desired number of mutations k is less than the number of mutable residues n. |
| Long Abstract: Click Here |
| Poster W027 |
| Protein folding -- from start to finish |
| Jonathan Ellis- Macquarie university |
| Fabian Huard (Macquarie university, Statistics); Charlotte Deane (Oxford university, Statistics); Graham Wood (Macquarie university, Statistics); |
| Short Abstract: Cotranslational folding may confer benefits to protein folding; such ashelping the peptide avoid kinetic traps. These benefits areinvestigated on proteins displaying both signs of cotranslationalfolding and post-translational folding. At times, sequential foldingperforms better than non-sequential. This suggests incorporation ofsequential folding may lead to better predictions. |
| Long Abstract: Click Here |
| Poster W028 |
| MOLECULAR DYNAMIC SIMULATION TO MONILIPHOTHORA PERNICIOSA CHITINASE, THE AGENT OF WITCHES’ BROOM DISEASE ON THEOBROMA CACAO |
| Rafaela Galante- University of Feira de Santana. |
| Catiane Souza (State University of Feira de Santana, Biological Science); Bruno Andrade (State University of Feira de Santana, Biological Science); Sandra Assis (State University of Feira de Santana, Health Science); Julio Carcardo (State University of Santa Cruz, Biological Science); Aristóteles Góes-Neto (State University of Feira de Santana, Biological Science); Alex Taranto (State University of Feira de Santana, Health Science); |
| Short Abstract: Chitinases are released by M. perniciosa promoting hydrolysis of chitin, which is important to the development of the pathogen in Theobroma cacao. We constructed and refined the 3D structure of the chitinase of M. perniciosa. The quality of resultant model was evaluated by PROCHECK 3.0 and ANOLEA. |
| Long Abstract: Click Here |
| Poster W029 |
| GOdot in 2009 |
| Ingolf Sommer- Max-Planck-Institue for Informatics |
| Frederik Gwinner (Max-Planck-Institute for Informatics, Computational Biology); Anne-Christin Hauschild (Max-Planck-Institute for Informatics, Computational Biology); Aaron Weimann (Max-Planck-Institute for Informatics, Computational Biology); Thomas Lengauer (Max-Planck-Institute for Informatics, Computational Biology); |
| Short Abstract: The previously published GOdot system allows for predicting molecular functions of query proteins with known structure. The system assesses structural similarities of reference proteins and relates those to molecular function. Here, we present an incorporated visualization of the structural and functional neighborhood of proteins. Additionally, we present an update now using current reference structures. |
| Long Abstract: Click Here |
| Poster W030 |
| A new method to predict 3D structure for protein loops |
| Christelle Reynes- Université Paris Diderot |
| Anne-Claude Camproux (Université Paris Diderot, UFR SdV - Unité MTi); Robert Sabatier (Faculté de Pharmacie de Montpellier, Laboratoire de Physique Industrielle et Traitement de l'Information); Leslie Regad (University of Helsinky, Faculty of Pharmacy, Centre for Drug Research, Computational Drug Discovery group P.O.); |
| Short Abstract: Predicting 3D protein structures from amino acid sequences and especially in loops is addressed. After prior encoding of structure via structural letters, the proposed method firstly predicts single letters from amino-acids via genetic programming, then prediction is refined by a hidden Markov-model considering links between letters (transitions and confusions). |
| Long Abstract: Click Here |
| Poster W031 |
| Improving 3D model selection of membrane proteins |
| Arjun Ray- Center for Biomembrane Research |
| Bjorn Wallner (Center for Biomembrane Research, Dept. Biochemistry Bjorn); |
| Short Abstract: The huge gap between the number of membrane proteins in the genome (25%) and the membrane proteins in the structural database (less than 1%) makes it an ideal target for computational approaches. We have improved and extended ProQ, for model quality assessment of water soluble proteins, to membrane proteins. |
| Long Abstract: Click Here |
| Poster W032 |
| Changing the traditional picture of alpha-helical membrane proteins |
| Kristoffer Illergård- Stockholm University |
| Anni Kauko (Stockholm University, Department of Biochemistry and Biophysics); Arne Elofsson (Stockholm University, Department of Biochemistry and Biophysics); |
| Short Abstract: We have investigated unexpected regions such as coils, reentrant regions and polar residues in the middle of alpha-helical membrane proteins of known structures. The studies revealed interesting clues about the structure, function, folding and evolution of these proteins. |
| Long Abstract: Click Here |
| Poster W033 |
| Investigation and prediction of the severity of p53 mutants using parameters from structural calculations |
| Jonas Carlsson- Linköping University |
| Thierry Soussi (Karolinska Institutet, Oncology-Pathology, Cancer Center Karolinska (CCK)); Bengt Persson (Linköping University, IFM Bioinformatics); |
| Short Abstract: A method has been developed to predict effects of mutations in the p53 cancer suppressor gene, combining novel and previously established parameters. Each mutant is classified as deleterious or non-deleterious based on a severity score. The method has a prediction accuracy of 77%, which is better than earlier methods. |
| Long Abstract: Click Here |
| Poster W034 |
| Importance of local model quality for Molecular Replacement |
| Marcin Pawlowski- International Institute of Molecular and Cell Biology in Warsaw |
| No additional authors |
| Short Abstract: Computational models of protein structure have been shown to be useful as search models in Molecular Replacement. Our study shows that theoretical modeling in combination with accurate prediction of quality of models by MQAP can provide useful search models for crystallographic structure solution by MR. |
| Long Abstract: Click Here |
| Poster W035 |
| Prediction of causative effects of disease-related mutations at the molecular level by integrated bioinformatic analyses. |
| Jan Kosinski- International Institute of Molecular and Cell Biology |
| Bujnicki Janusz (International Institute of Molecular and Cell Biology, Laboratory of Bioinformatics and Protein Engineering); |
| Short Abstract: We present an integrated approach to predict the effects of missense mutations by mapping the functional sites using a broad spectrum of bioinformatic methods, such as sequence and structural analyses, modeling and docking. Our approach can be easily applied by biologists and serve as a guide for selecting appropriate tools. |
| Long Abstract: Click Here |
| Poster W036 |
| Fold recognition insights into function of two myeloid specific regulators of apoptosis - HAX1 and MLF1/MLF2 |
| Katarzyna Kokoszynska- Sklodowska-Curie Memorial Cancer Center and Institute of Oncology |
| No additional authors |
| Short Abstract: Here we present the results of fold recognition and identification of distant homology of two myeloid regulators of apoptosis – HAX1 and myeloid leukemia factors (MLF). We summarized the involvement of HAX1 proteins in calcium homeostasis and the current state of the knowledge on the function of HAX1/MFL families. |
| Long Abstract: Click Here |
| Poster W037 |
| Classification of the SDR Superfamily of Short-Chain Dehydrogenases/Reductases Using Hidden Markov Models |
| Yvonne Kallberg- Linköping Univ. & Karolinska Inst. |
| Fredrik Lysholm (Linkoping University, IFM Bioinformatics); Udo Oppermann (University of Oxford, 3Structural Genomics Consortium, The Botnar Research Centre, ); Bengt Persson (Linkoping University, IFM Bioinformatics); |
| Short Abstract: The largest dehydrogenase superfamily is SDR of short-chain dehydrogenases/reductases with presently ~47.000 members. It shows considerable divergence and there is a great need for sub-classification. We have now developed a family classification system and an accompanying nomenclature scheme that provide a systematic overview and allows for functional conclusions. |
| Long Abstract: Click Here |
| Poster W038 |
| Solvent in protein-protein interactions and its impact on protein contacts prediction |
| Sergey Samsonov- Biotec TU Dresden |
| Joan Teyra (BIOTEC TU Dresden, Structural Bioinformatics); Gerd Anders (BIOTEC TU Dresden, Structural Bioinformatics); M. Teresa Pisabarro (BIOTEC TU Dresden, Structural Bioinformatics); |
| Short Abstract: Although solvent is important in protein interfaces, its impact on protein-protein interactions in computational studies is often ignored. We analyze water-mediated interactions in protein interfaces by a MD approach and, in addition, demonstrate that introduction of solvent into the correlated mutations concept improves to a certain extent protein contacts predictions. |
| Long Abstract: Click Here |
| Poster W039 |
| Characterisation of novel proteins involved in mitosis by structure-based computational methods |
| Sontheimer Jana- BIOTEC TU Dresden |
| Mirko Theis (Max Planck Institute of Cell Biology and Genetics, Dresden); Frank Buchholz (Max Planck Institute of Cell Biology and Genetics, Dresden ); Maria Teresa Pisabarro (BIOTEC TU Dresden, Structural Bioinformatics); |
| Short Abstract: With full sequenced genomes, computational methods are gaining importance in characterisation of novel proteins. We have developed a framework for automatic structure-based function annotation and used it for analysing phenotypic data from genome-wide RNAi screenings, which has resulted in characterisation of a novel mitotic protein regarding its structure and function. |
| Long Abstract: Click Here |
| Poster W040 |
| Discovery of novel chemokines with automated structure-based functional protein annotation methods |
| Aurelie Tomczak- BIOTEC - Technical University Dresden |
| Maria Teresa Pisabarro (BIOTEC - Technical University Dresden, Structural Bioinformatics); |
| Short Abstract: We developed an automatic framework for structure-based annotation of proteins and use it to identify novel chemokines, which are proteins essential for guiding immune cell migration. We integrate publicly available sequence and structure information and feature prediction tools with fold recognition and identified promising candidates that are currently experimentally validated. |
| Long Abstract: Click Here |
| Poster W041 |
| Fast structural alignment of RNA using n-grams |
| Kristian Rother- International Institute of Molecular and Cell Biology in Warsaw |
| Raphael Bauer (Charite Medical University, Arnimallee 22, 14195 Berlin, Structural Bioinformatics Group); Marcus Schroeder (Charite Medical University, Arnimallee 22, 14195 Berlin, Structural Bioinformatics Group); Robert Preissner (Charite Medical University, Arnimallee 22, 14195 Berlin, Structural Bioinformatics Group); Janusz M. Bujnicki (International Institute of Molecular and Cell Biology in Warsaw, Bioinformatics and Protein Engineering Lab); |
| Short Abstract: We have created LaJolla, a structural alignment method for RNA. It represents the RNA backbone as strings, and uses N-grams for searching. We have benchmarked the method against SARA, and show improvements in the assignment of RNA function. |
| Long Abstract: Click Here |
| Poster W042 |
| Blender for biology: Game Engine for molecular animation and special effects for chemical and physical behavior |
| Monica Zoppè- Scientific Visualization Unit - LTGM |
| Raluca Andrei (Scuola Normale Superiore, Lab of Molecular Biology); Marco Callieri (CNR , ISTI); Tiziana Loni (BigBang Solutions, Graphics development); Maria Francesca Zini (CNR, Inst. of Clinical Physiology); Monica Zoppe' (CNR, Inst. of Clinical Physiology); |
| Short Abstract: We present an animation system based on the 3D open-source software Blender applied to the transition between two conformations of Calmodulin. Results are compatible with experimental data, and are visualized using a technique that reveals chemical and physical features immediately. The instrument is useful in research and other settings. |
| Long Abstract: Click Here |
| Poster W043 |
| Co-evolution of blocks of residues and sectors in protein structures |
| Linda Dib- CNRS-UPMC |
| Alessandra Carbone (CNRS-UPMC, Informatique); |
| Short Abstract: Evolutionarily conserved networks of residues have been demonstrated to mediate allosteric communication in proteins involved in cellular signaling. We propose a method to detect co-evolved blocks of residues, numerically rank them depending on their level of co-evolution, and clusterize them to obtain networks of co-evolved blocks. |
| Long Abstract: Click Here |
| Poster W044 |
| ModeRNA: A New Software Tool For Comparative Modeling of RNA 3D-Structures |
| Janusz Bujnicki- Intl. Institute of Molecular and Cell Biology (IIMCB) |
| Magdalena Musielak (Adam Mickiewicz University, PL-61-614 Poznan, Poland, Bioinformatics Laboratory, Institute of Molecular Biology and Biotechnology); Tomasz Puton (Adam Mickiewicz University, PL-61-614 Poznan, Poland, Bioinformatics Laboratory, Institute of Molecular Biology and Biotechnology); Kristian Rother (Intl. Institute of Molecular and Cell Biology (IIMCB), 02-109 Warsaw, Poland, Laboratory of Bioinformatics and Protein Engineering); |
| Short Abstract: We are developing ModeRNA, a computer program for comparative RNA modeling. With this tool a user can obtain a 3D model of a target RNA molecule based on a homologous template structure from the PDB, and a target-template alignment of RNA sequences, by introducing nucleoside substitutions and insertions/deletions. |
| Long Abstract: Click Here |
| Poster W045 |
| A comparative study for definition and search of protein motifs |
| Annika Kreuchwig- Free University Berlin |
| Ina Koch ([1] TFH Berlin FB VI, Seestr. 64, 13347 Berlin / [2] Max Planck Institute for Molecular Genetics, Ihnestr. 73, 14195 Berlin, [1] Bioinformatics / [2] Computational Molecular Biology); Patrick May (Max Planck Institute for Molecular Plant Physiology Am Muehlenberg 1, 14476 Potsdam-Golm, Bioinformatics Group / GoFORSYS); |
| Short Abstract: Protein Topology Graph Library provides graph-theoretical descriptions of proteins. We define functional protein domains of protein topology graphs and introduce a new method to browse the database for topological protein structure motifs by pre-defined search patterns of structural motifs. We perform a comparative analysis with CATH, SCOP and TOPS. |
| Long Abstract: Click Here |
| Poster W046 |
| InterProScan New and Planned Developments |
| Manjula Thimma- European Bioinformatics Institute |
| Sarah Hunter (EBI, InterPro Team); Antony Quinn (EBI, Interpro Team); Phil Jones (EBI, InterProTeam); |
| Short Abstract: The InterPro database integrates multiple protein signature databases and provides a portal for protein functional and structural annotation. InterProScan is a software package which wraps the search algorithms for these signature databases into a single tool. This poster will present significant new developments in InterProScan. |
| Long Abstract: Click Here |
| Poster W047 |
| A geometric knowledge-based coarse-grained scoring potential for structure prediction evaluation |
| Sebastien LORIOT- INRIA |
| Frédéric Cazals (INRIA, ABS); Michael Levitt (Stanford University, Structural Biology); Julie Bernauer (INRIA, ABS); |
| Short Abstract: We present a method to derive multi-body contact potentials,based on the arrangement of circles on sphere.Using this geometric construction on coarse-grained protein models, we show thatwe can build various knowledge-based potentials, encoding up to 5-body contacts,able to distinguish native structures from decoys. |
| Long Abstract: Click Here |
| Poster W048 |
| firestar -predicting functional residues, new developements |
| Gonzalo Lopez- Cnio |
| Michael Tress (CNIO, Structural and Computational Biology Programm); Alfonso Valencia (CNIO, Structural and Computational Biology Programm); |
| Short Abstract: The prediction of functional residues with firestar is now wholly automated and has been made available as a web service. As part of the automatization of firestar we have linked functional residue predictions with GO molecular function terms and all binding sites are now filtered for biological relevance. |
| Long Abstract: Click Here |
| Poster W049 |
| PET(co)fold: Unification of evolutionary and thermodynamic information for RNA folding |
| Stefan Seemann- IBHV, University Of Copenhagen |
| Andreas S Richter (Inst. of Computer Science, Albert-Ludwigs-Univ. Freiburg, Chair for Bioinformatics); Rolf Backofen (Inst. of Computer Science, Albert-Ludwigs-Univ. Freiburg, Chair for Bioinformatics); Jan Gorodkin (IBHV, University Of Copenhagen, Genetics And Bioinformatics); |
| Short Abstract: PETfold has shown that the prediction of RNA structure in multiple aligned sequences can benefit from the unification of probabilistic evolutionary and thermodynamic model into a single optimization problem. In PETcofold, we extend the concept to search for RNA duplexes considering covariance and pseudoknots between intra- and intermolecular base pairs. |
| Long Abstract: Click Here |
| Poster W050 |
| Allostery Hotspot Prediction Using Support-vector Machines |
| Omar Demerdash- University of Wisconsin-Madison |
| Julie Mitchell (University of Wisconsin-Madison, Biochemistry and Mathematics); Michael Daily (University of Wisconsin-Madison, Chemistry); |
| Short Abstract: Allostery is the process whereby a ligand or protein-binding event at one site changes the activity at a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed a family of knowledge-based models using support vector machines for accurate prediction of allosteric “hot spots.” |
| Long Abstract: Click Here |
| Poster W051 |
| Predicting Protein Interface Residues from Functional Specificity |
| K. Anton Feenstra- Free University Amsterdam |
| Bas Dutilh (Radboud University Nijmegen, CMBI); Vera van Noort (Radboud University Nijmegen, CMBI); Martijn Huynen (Radboud University Nijmegen, CMBI); Giacomo Bastianelli (Institut Pasteur, Paris); Jaap Heringa (Free University Amsterdam, IBIVU/Computer Science); |
| Short Abstract: Functional specialization within protein families implies differences in protein-protein interactions. We select sub-type specific sites by comparing interacting orthologs with non-interacting paralogs using Sequence Harmony [NAR 35:W495; NAR 34:6540]. Selections are highly enriched in surface residues, and enriched in interface residues from known (PDB) complex structures. |
| Long Abstract: Click Here |
| Poster W052 |
| Evolutionarily driven algorithm for the quantification of protein patterns' similarity |
| Konstantinos Exarchos- Unit of Medical Technology & Intelligent Information Systems |
| George Rigas (Unit of Medical Technology & Intelligent Information Systems, Dept of Computer Science, University of Ioannina); Dimitrios Fotiadis (Unit of Medical Technology & Intelligent Information Systems, Dept of Computer Science, University of Ioannina); |
| Short Abstract: We propose an evolutionarily-driven algorithm which quantifies the statistical similarity between two patterns. The algorithm computes the Kullback-Leibler divergence, employing the residues’ substitution probabilities and their prior distribution. Thus, we determine whether a pattern is novel and consequently identify its functional propensity, by comparing it against the PROSITE database. http://sites.google.com/site/patterncomparer/. |
| Long Abstract: Click Here |
| Poster W053 |
| Model-structure, mutagenesis and functional characteristics of the NHA2 transporter |
| Maya Schushan- Tel-aviv university |
| Nir Ben-Tal (Prof. , Biochemistry); Minghui Xiang (Dr., Physiology); Rajini Rao (Dr., Physiology); Etana Padan (Prof., Molecular Microbial Ecology); |
| Short Abstract: We generated a model-structure of a novel human cation/proton transmembrane antiporter, NHA2, via a composite homology modeling approach. The model-structure is supported by evolutionary conservation analysis and guided mutagenesis experiments. Additionally, the model of NHA2 reveals some unique functional features, distinct from those of other family members. |
| Long Abstract: Click Here |
| Poster W054 |
| TESE: Generating specific protein structure test set ensembles |
| Silvio Tosatto- University of Padova |
| Francesco Sirocco (University of Padova, Dept. of Biology); |
| Short Abstract: TESE is a web server for the generation of test sets of protein sequences and structures fulfilling a number of different criteria. Structure classification is used to control structural/sequence redundancy and to interactively select protein subsets with specific characteristics. The TESE server is available for non-commercial use at URL: http://protein.bio.unipd.it/tese/. |
| Long Abstract: Click Here |
| Poster W055 |
| Comparative modeling of the SmSERCA protein of Schistosoma mansoni |
| Nelson Gichora- ILRI |
| Anna Tramontano (University of Rome "La Sapienza", Biochemical Sciences); |
| Short Abstract: We present our results having modeled the structure of Schistosoma mansoni SERCA (SmSERCA) protein by homology and compared using Modeller. The results will be used in the design of a specific drug that targets the artemisone binding site of the SmSERCA protein in the platyhelminth. |
| Long Abstract: Click Here |
| Poster W056 |
| GOPHER - An automatic server for function prediction evaluation |
| Jose Maria Fernandez- Spanish National Cancer Research Center (CNIO) |
| Angela del Pozo (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Gonzalo Lopez (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Michael Tress (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Alfonso Valencia (Spanish National Cancer Research Center (CNIO), Structural and Computational Biology Programme); Mark Wass (Imperial College London, Structural Bioinformatics Group); Michael Sternberg (Imperial College London, Structural Bioinformatics Group); |
| Short Abstract: We have developed a server, GOPHER, to assess protein function prediction in a continuous fashion. Predictors assign GO terms to weekly PDB updates and are assessed using a range of methods. The server is now functioning and we would like to invite developers to take part in this rolling assessment. |
| Long Abstract: Click Here |
| Poster W057 |
| WRAPPA: a Web-based Residue Analysis Program for Phobicity Assessment |
| Christopher Fraser- Institute for Mathematics and its Applications (IMA) |
| Thuong Van Du Tran (l’ ́Ecole Polytechnique `a Palaiseau, Laboratoire d’Informatique); Ariel Fernandez (Rice University, Bioengineering); L. Ridgway Scott (University of Chicago, Computer Science); |
| Short Abstract: Defectively packed hydrogen bonds, or “dehydrons”, play a significant role in protein-ligand interactions through the thermodynamically favorable exclusion of water. We introduce and validate a new bioinformatics application that screens for dehydrons within protein structures: a Web-Based Residue Analysis Program for Phobicity Assessment (WRAPPA). |
| Long Abstract: Click Here |
| Poster W058 |
| GOmotif: A web server for investigating the biological role of protein sequence patterns |
| Franklin Bristow- Public Health Agency of Canada |
| Runtao He (Public Health Agency of Canada, National Microbiology Laboratory); Gary Van Domselaar (Public Health Agency of Canada, National Microbiology Laboratory, Bioinformatics Core Facility); |
| Short Abstract: Biologically relevant sequence patterns (motifs) are commonly found in proteins. Experimentally ascertaining the biological relevance of novel motifs can be an expensive and time consuming process. GOmotif is a web based tool that searches Gene Ontology annotated protein databases to assist scientists in assigning biological roles to a novel motif. |
| Long Abstract: Click Here |
| Poster W059 |
| Prediction of Protein Binding Regions in Disordered Proteins |
| Balint Meszaros- Institute of Enzymology |
| Istvan Simon (Institute of Enzymology, Protein structure); Zsuzsanna Dosztanyi (Institute of Enzymology, Protein structure); |
| Short Abstract: Intrinsically unstructured/disordered proteins (IUPs/IDPs) do notadopt a stable structure in isolation but exist as highly flexibleconformational ensembles. Many IDPs function via binding to astructured partner and undergo a disorder-to-order transition. In thiswork we report a prediction method for such disordered bindingregions. |
| Long Abstract: Click Here |
| Poster W060 |
| Fragment-based replica-exchange method with adaptive parameter tuning |
| Masaaki Suzuki- The University of Tokyo |
| Hiroshi Okuda (The University of Tokyo, Research into Artifacts, Center for Engineering (RACE)); |
| Short Abstract: Fragment-based replica-exchange method (REM) with automatic parameter tuning has been developed. In the parameter tuning scheme, fragment length is optimized adaptively. Performing peptide folding simulations, we have found that the proposed REM successfully provides appropriate fragment length, and thus, good conformational sampling performance. |
| Long Abstract: Click Here |
| Poster W061 |
| Guidelines for fragment selection in protein structure prediction |
| Sheenal Srivastava- Macquarie University |
| Graham Wood (Macquarie University, Statistics); Jonathan Ellis (Macquarie University, Statistics); Charlotte Deane (Oxford University, Statistics); |
| Short Abstract: Fragment-based assembly methods are commonly employed to predict protein structure. We present a study of Rosetta fragment libraries and a first principles approach to better select fragments, based on a locational bias of the target protein sequence. |
| Long Abstract: Click Here |
| Poster W062 |
| Assessing conformational diversity in proteins using evolutionary information |
| Nicolas Palopoli- Universidad Nacional de Quilmes |
| Ezequiel Juritz (Universidad Nacional de Quilmes, Centro de Estudios e Investigaciones); Sebastian Fernandez Alberti (Universidad Nacional de Quilmes, Centro de Estudios e Investigaciones); Gustavo Parisi (Universidad Nacional de Quilmes, Centro de Estudios e Investigaciones); |
| Short Abstract: We have previously presented a method for 3D protein models discrimination based on evolutionary information. Here we show that our method is able to describe the conformational diversity of a protein, allowing us to select native-like models representing the conformational ensemble that characterizes the native state of the protein. |
| Long Abstract: Click Here |
| Poster W063 |
| How good can Template-based Modelling be? |
| Braddon Lance- Macquarie University |
| Graham Wood (Macquarie University, Department of Statistics); Charlotte Deane (Oxford University, Statistics); |
| Short Abstract: To predict the structure of a protein, the amino-acid sequence may be aligned with a related structure, and the prediction built from the corresponding fragments. We show how this prediction would be improved if the structure fragments were optimally positioned, and model this improvement as a function of protein properties. |
| Long Abstract: Click Here |
| Poster W064 |
| Automated scaffold selection in enzyme design |
| Christoph Malisi- Max Planck Institute for developmental biology |
| Birte Höcker (Max Planck Institute for developmental biology, Junior Research Group); Oliver Kohlbacher (Eberhard Karls University Tübingen, Computer Science); |
| Short Abstract: We present ScaffoldSelection, an algorithm for identifying attachment sites for catalytic motifs in protein structures. It identifies pairs of geometrically suitable backbone positions, and combines these with a graph clique search to complete attachment sites. ScaffoldSelection performed well in a benchmark involving the identification and geometric recapitulation of catalytic motifs in a large structure database. |
| Long Abstract: Click Here |
| Poster W065 |
| Compensatory patterns of tRNA recognition regions are preserved between bacterial and mitochondrial amino-acyl tRNA synthetases |
| Milana Morgenstern- Weizmann Institute of Science |
| Liron Klipcan (Weizmann Institute of Science, Structural Biology); Dmitry Tworowski (Weizmann Institute of Science, Structural Biology); Mark Safro (Weizmann Institute of Science, Structural Biology); |
| Short Abstract: We studied aminoacyl-tRNA synthetases (aaRSs), and their adaptation using correlated mutations. For eight bacterial aaRS-tRNA complexes and two mitochondrial aaRS, we found the 1.75-fold increase of mutations frequency in tRNA recognition regions. The compensatory patterns are preserved for tRNA recognition regions between corresponding bacterial and mitochondrial aaRSs. |
| Long Abstract: Click Here |
| Poster W066 |
| Data Mining of Enzymes using Specific Peptides |
| David Horn- Tel Aviv University |
| Uri Weingart (Tel Aviv University, Physics); Yair Lavi (Tel Aviv University, Physics); |
| Short Abstract: Employing Specific Peptides (SPs, Kunik et al 2007), motifs specific to branches of the EC classification hierarchy, we classify proteins into enzyme categories. Very good results are obtained both on positive and negative data. The method is applied to several metagenomic datasets, whose enzymatic profiles are predicted. |
| Long Abstract: Click Here |
| Poster W067 |
| FiberDock: Modeling Restricted Backbone Flexibility in Docking |
| Efrat Mashiach- Tel-Aviv University |
| Ruth Nussinov (National Cancer Institute, Center for Cancer Research Nanobiology Program); Haim J. Wolfson (Tel Aviv University, School of Computer Science); |
| Short Abstract: FiberDock is a novel docking refinement method that models backbone and side-chain flexibility. The method minimizes backbone conformations along the most relevant normal modes, which correlate with chemical forces. It uses both low and high frequency modes and therefore is able to model global and local conformational changes. |
| Long Abstract: Click Here |
| Poster W068 |
| IPASS: Error Tolerant NMR Backbone Resonance Assignment by Linear Programming |
| Xin Gao- University of Waterloo |
| Babak Alipanahi (University of Waterloo, David R. Cheriton School of Computer Science); |
| Short Abstract: This paper proposed a novel Integer Linear Programming (ILP) based NMR backbone resonance assignment method, IPASS, which guarantees to find the global optimalsolution under our problem setup. IPASS significantly outperforms the state-of-the-art assignment methods on both synthetic peak lists and real peak lists generated by automatic peak picking method. |
| Long Abstract: Click Here |
| Poster W070 |
| Improving Human Disease Gene Ranking by Cross-Species Function Prediction |
| Samira Jaeger- Humboldt-Universitaet zu Berlin |
| Stefan Kröger (Deutsches Rheuma-Forschungszentrum Berlin, Signal Transduction); Ulf Leser (Humboldt-Universitaet zu Berlin, Department of Computer Science); |
| Short Abstract: We propose a framework for disease gene ranking based on human interaction data and protein function to prioritize genes. The integration of predicted functions for uncharacterized proteins improves our ranking. We identify highly-ranked disease-related proteins that are weakly or not annotated and therefore cannot be captured by other methods. |
| Long Abstract: Click Here |
| Poster W071 |
| From the detection of functional regions towards function annotation in proteins |
| Guy Nimrod- Department of Biochemistry |
| Nir Ben-Tal (Tel Aviv University, Department of Biochemistry); Maya Schushan (Tel Aviv University, Department of Biochemistry); Christina Leslie (Memorial Sloan-Kettering Cancer Center, Computational Biology Program); András Szilágyi (Hungarian Academy of Sciences, Institute of Enzymology); |
| Short Abstract: We present a new method, and a web-server, for the identification of DNA binding proteins from 3D-structure. The method is based on various characteristics of the protein and the functional region predicted by the PatchFinder algorithm. We used it to predict DNA-binding proteins in the N-Func database of 'hypothetical proteins'. |
| Long Abstract: Click Here |
| Poster W072 |
| HOMOLOGY MODELLING AND MOLECULAR DYNAMIC SIMULATION TO MONILIOPHTHORA PERNICIOSA BETA-1,3-GLUCAN SYNTHASE |
| Catiane Souza- State University of Feira de Santana |
| Braz Hora-junior (State University of Santa Cruz, Biological Science); Bruno Andrade (State University of Feira de Santana., Biological Science); Maiza Lopes (State University of Santa Cruz, Biological Science); Cristiano Dias (State University of Santa Cruz, Biological Science); Carlos Pirovani (State University of Santa Cruz, Biological Science); Julio Cascardo (State University of Santa Cruz, Biological Science); Arist�teles G�es-Neto (State University of Feira de Santana, Biological Science); Alex Taranto (State University of Feira de Santana, Biological Science); |
| Short Abstract: The fungal cell wall, a complex structure composed by polysaccharides such as glucan synthase and chitin. The glucan synthase is targets to search for inhibitors in fungal pathogens. A model was constructed and refined. Its quality was evaluated by PROCHECK. The Ramachandran plot showed that the model was acceptible. |
| Long Abstract: Click Here |
| Poster W073 |
| Uncovering the Structure and Function of the Core Transcriptional Network That Maintains Pluripotency in Embryonic Stem Cells |
| Jaden Hastings- University of Oxford |
| No additional authors |
| Short Abstract: Pluripotency is known to be regulated by a particular set of transcription factors, including Nanog, Sox2 and Oct4 (POU5F1). Using both comparative modelling as well as ab initio molecular modelling methods, we generated the 3D structures of their human orthologs then applied docking methods to predict their interactions. |
| Long Abstract: Click Here |
| Poster W074 |
| Estimating the genome-wide preference of interaction between disordered proteins in a human protein-protein interaction network |
| Kana Shimizu- National Institute of Advanced Industrial Science and Technology (AIST) |
| Kazuhiko Fukui (National Institute of Advanced Industrial Science and Technology (AIST), Computational Biology Research Center (CBRC)); Hiroyuki Toh (Kyushu University, Medical Institute of Bioregulation); |
| Short Abstract: Intrinsic disorder is considered to play an important role in protein-protein interactions (PPIs). Although rigid structures have been expected to become identifiers for recognition on binding, this study revealed that the occurrence of interactions between disordered proteins is significantly frequent, by comparing an existing human PPI network with randomized networks. |
| Long Abstract: Click Here |
| Poster W075 |
| Bioinformatic Analysis of Sigma C Protein of Avian Reovirus Israeli Isolates Towards Novel Vaccine Production |
| Adva Yeheskel- Bioinformatics unit, The Faculty of Life Science, Tel Aviv University |
| Metsada Pasmanik-Chor (The Faculty of Life Science, Tel-Aviv University, Bioinformatics Unit); Dana Goldenberg (MIGAL-Galilee Technology Center, Department of Virology and Immunology); Jacob Pitcovski (MIGAL-Galilee Technology Center, of Virology and Immunology); |
| Short Abstract: Chicken reoviruses cause severe losses in avian industry. The present vaccines are inefficient. Sigma C protein from 28 Israeli viral isolates were sequenced. The aim of this study is to apply bioinformatic tools in order to better predict novel epitopes that would serve as better vaccination options. |
| Long Abstract: Click Here |
| Poster W076 |
| Prediction of super-secondary structure in α-helical and β-barrel transmembrane proteins |
| Van Du Tran- Laboratoire d'Informatique de l'Ecole Polytechnique |
| Jean-Marc Steyaert (Laboratoire d'Informatique de l'Ecole Polytechnique, Computer Science); Philippe Chassignet (Laboratoire d'Informatique de l'Ecole Polytechnique, Computer Science); |
| Short Abstract: We modeled the protein folding problem into finding the longest closed path in a graph with respect to some given permutation to predict the super-secondary structure in alpha-helical and beta-barrel proteins which may contain Greek key motifs. The algorithm is implemented and tested for the class of beta-barrel transmembrane proteins. |
| Long Abstract: Click Here |
| Poster W077 |
| Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods |
| Stefano Lise- University College London |
| Cedric Archambeau (University College London, Department of Computer Science); Massimiliano Pontil (University College London, Department of Computer Science); David Jones (University College London, Department of Computer Science); |
| Short Abstract: Protein-protein interactions are critically dependent on just a fewresidues (hot spots), which if mutated can disrupt complex formation.We present a novel computational approach to identify hot spot residues,given the structure of a complex. The approach combines the strengths ofmachine learning and energy-based methods. |
| Long Abstract: Click Here |
| Poster W078 |
| A novel index to evaluate the appropriateness of a set of homologous sequences for functional region prediction |
| Wataru Nemoto- Advanced Industrial Science and Technology |
| Wataru Nemoto (Advanced Industrial Science and Technology, Computational Biology Research Center); Hiroyuki Toh (Kyushu University, Medical Institute for Bioregulation); |
| Short Abstract: We developed a novel method to predict functional regions of a protein by using sequence and structure. Advantage of this method is that we can collect sequences for multiple sequence alignment automatically and objectively. We will discuss the benefits and the pitfalls of our method. |
| Long Abstract: Click Here |
| Poster W079 |
| Protein Sequence and Structure Optimisation in One Probabilistic Framework |
| Gundolf Schenk- University of Hamburg |
| Andrew Torda (University of Hamburg, ZBH - Centre for Bioinformatics); |
| Short Abstract: Protein structure prediction and sequence optimisation are two challenges which routinely appear to scare PhD students. We have used a fragment-based approach which turns both into a classic self-consistent field problem within a framework of descriptive statistics. |
| Long Abstract: Click Here |
| Poster W080 |
| Analysis of functional divergency in the EFG I and EFG II |
| Tõnu Margus- Tartu University |
| Maido Remm (Tartu University, Bioinformatics); Tanel Tenson (Institute of Technology at Tartu University, Antibiotics); |
| Short Abstract: EFG duplications in bacteria form four subfamilies: EFG-I, EFG-II, spdEFG1 and spdEFG2. We have first characterized an EFG subfamily (the EFG-II) which differs from the EFG-I (canonical EFG) by its high divergency in primary sequence. We highlight five differentially conserved positions which are related with altered functionality of the EFG-II |
| Long Abstract: Click Here |
| Poster W081 |
| PAUL: Protein structural alignment using integer linear programming and Lagrangian relaxation |
| Inken Wohlers- Centrum Wiskunde & Informatica |
| Lars Petzold (Freie Universität Berlin, Mathematics in Life Sciences Group); Francisco Domingues (Max-Planck-Institut für Informatik, Computational Biology and Applied Algorithmics Group); Gunnar Klau (Centrum Wiskunde & Informatica, Life Sciences Group); |
| Short Abstract: We present PAUL, a method for protein structural alignment that is based on aligning sparse protein distance matrices using integer linear programming and Lagrangian relaxation. PAUL is a novel, non-heuristic and mathematically sound approach that is competitive to or even outperforms other state-of-the-art structural alignment algorithms. |
| Long Abstract: Click Here |
| Poster W082 |
| Simulation of induced structural transitions in an isolated Kv1.2/2.1 voltage-sensor important for the gating mechanism |
| Christine Schwaiger- Center for Biomembrane Research |
| Pär Bjelkmar (Center for Biomembrane Research, Department of Biophysics and Biochemistry); Erik Lindahl (Center for Biomembrane Research, Department of Biophysics and Biochemistry); |
| Short Abstract: The Kv1.2/2.1 voltage-sensor movement is studied through an AFM-like technique. The voltage-sensor is pulled in two conformations (alpha/310), over the hydrophobic core proposed to be the gating free energy barrier, and the work distribution difference is compared. Additionally, residues responsible for the barrier are determined by utilizing core region mutations. |
| Long Abstract: Click Here |
| Poster W083 |
| Predicting helix-helix interactions from residue contacts in membrane proteins |
| Allan Lo- Academia Sinica |
| Yi-Yuan Chiu (Academia Sinica, Bioinformatics Lab., Institute of Information Science); Einar Andreas Rødland4 (University of Oslo, Centre for Cancer Biomedicine); Ping-Chiang Lyu (National Tsing Hua University, Institute of Bioinformatics and Structural Biology, Department of Life Sciences); Ting-Yi Sung (Academia Sinica, Bioinformatics Lab., Institute of Information Science); Wen-Lian Hsu (Academia Sinica, Bioinformatics Lab., Institute of Information Science); |
| Short Abstract: We present a novel two-level framework to predict residue contacts and helix-helix interactions in membrane proteins. Compared to the conventional direct method, this approach reduces both false positives and computational cost. This method can be used to guide helix-packing simulations and facilitate protein design for interaction with target transmembrane helices. |
| Long Abstract: Click Here |
| Poster W084 |
| Active Site Classification |
| Marc Roettig- Eberhard-Karls-University Tuebingen |
| Oliver Kohlbacher (Eberhard-Karls-University Tuebingen, Center for Bioinformatics); |
| Short Abstract: Active Site Classification (ASC) is a method to predict the specificity within an enzyme family usingsequence and structural information about the active site. We applied ASC to two enzyme families and could achieve improvements in classification accuracy and also interpretability of the models. |
| Long Abstract: Click Here |
| Poster W085 |
| Identification and comprehensive classification of Saccharomyces cerevisiae methyltransferome |
| Tomasz Wlodarski- University of Warsaw |
| Krzysztof Ginalski (University of Warsaw, Interdisciplinary Center for Mathematical and Computational Modelling); |
| Short Abstract: We have conducted comprehensive bioinformatics survey of all known and putative methyltransferases in S. cerevisiae genome and classified them into functional and structural classes. We identify several new methyltransferases and novel domains contexts and provide complete picture of methylation in S. cerevisiae. |
| Long Abstract: Click Here |
| Poster W086 |
| beta-strand segments prediction based on protein sequence and predicted neighboring structural information |
| Kanaka Durga Kedarisetti- University of Alberta |
| Marcin Mizianty (University of alberta, Electrical and Computer Engineering); Scott Dick (University of alberta, Electrical and Computer Engineering); Lukasz Kurgan (University of alberta, Electrical and Computer Engineering); |
| Short Abstract: Accurate prediction of beta-strands is an important step towards prediction of beta-sheets. We developed a novel sequence-based beta-strand predictor that exploits an ensemble of predicted local/global structural information. Our method improves SOVe and misses fewer strand segments when compared with current secondary structure predictors on two test sets including CASP8. |
| Long Abstract: Click Here |
| Poster W087 |
| Splitting statistical potentials to improve scoring of docking conformations |
| Elisenda Feliu Trijueque- Universitat de Barcelona |
| Baldomero Oliva (Pompeu Fabra University, Ciències experimentals i de la salut); Patrick Aloy (Institute for Research in Biomedicine, Structural and computational biology); |
| Short Abstract: We propose a new scoring function for rigid-body docking derived by splitting the usual residue-pair statistical potential as a sum of energy terms build upon local properties of the interacting aminoacids (exposure, secondary structure and hydrophobicity). The resulting scores are then combined into a final score. |
| Long Abstract: Click Here |
| Poster W088 |
| ModLink+: improving fold recognition by using protein-protein interactions |
| Oriol Fornes- GRIB-IMIM/UPF |
| Ramon Aragues (GRIB-IMIM/UPF, Structural Bioinformatics Lab); Jordi Espadaler (GRIB-IMIM/UPF, Structural Bioinformatics Lab); Marc A. Marti-Renom (GRIB-IMIM/UPF, Structural Bioinformatics Lab); Andrej Sali (UCSF, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry and California Institute for Quantitative Biosciences); |
| Short Abstract: The fold of a protein sequence can be predicted using different strategies. Here, we show how protein-protein interaction information can improve the fold recognition capacity of state-of-the-art methodologies. In addition, we show that our method can be applied large-scale (e.g. in yeast). |
| Long Abstract: Click Here |
| Poster W089 |
| Computational Identification of Local and Global RNA Motifs |
| Steffen Heyne- University of Freiburg |
| Rolf Backofen (University of Freiburg, Computer Science); Sebastian Will (University of Freiburg, Computer Science); |
| Short Abstract: Non-protein coding regions of bacteria as well as eukaryotes often contain important functional RNA elements. Both sequence and structure properties are important features of such RNAs. We present a new approach for the identification and motif-based comparison of such RNA elements. |
| Long Abstract: Click Here |
| Poster W090 |
| Predicting docking interactions between a plant defence protein and its ligands |
| Judit Kumuthini- CPGR |
| Melané Vivier (Stellenbosch University, IWBT); Abre de Beer (Stellenbosch University, IWBT); Albert Joubert (Stellenbosch University, IWBT); Reinhard Hiller (CPGR, CPGR); |
| Short Abstract: Protein-Protein interactions are useful in identifying the mechanism(s) involved in plant defence. This approach was to predict the interactions between a plant defence-protein and a plant pathogen. The binding-conformations of interaction complex of Endopolygalacturonases from B. cinerea and the polygalacturonase-inhibiting protein from grapevine were predicted using the crystalline-structure of the bean-PGIP as a model. |
| Long Abstract: Click Here |
| Poster W091 |
| New insights into coiled coil formation by means of support vector machines |
| Ingrid Abfalter- Johannes Kepler University Linz |
| Carsten Mahrenholz (Charite Berlin, Insititute for Medical Immunology); Ulrich Bodenhofer (Johannes Kepler University, Institute of Bioinformatics); Sepp Hochreiter (Johannes Kepler University, Institute of Bioinformatics); |
| Short Abstract: We use support vector machines and statistical methods to extract important amino acid sequence patterns that determine the olgimerization state of coiled coil proteins. These patterns are an important prerequisite for the rational design of drugs targeting coiled coil membrane fusion proteins from viruses like HIV and Avian Influenza. |
| Long Abstract: Click Here |
| Poster W092 |
| Identifying Functional Sites Common to the GCN5 Related N-Acetyltransferases (GNAT Super Family) Through Computational Methods |
| Domonique Bulls- North Carolina Agricultural & Technical State University |
| No additional authors |
| Short Abstract: This research focuses on the complexity of proteins and their active/functional sites. The GCN5-Related N-Acetyltransferases (GNAT Family) is a super family of proteins. The main goal is to identify functional sites and other structural motifs with assistance of computational methods. |
| Long Abstract: Click Here |
| Poster W093 |
| 3D Modeling of ribosomal RNA based on cryo-EM maps |
| Alexander Jarasch- Ludwig-Maximilians-Universität München |
| Roland Beckmann (Ludwig-Maximilians-Universität München, Gene Center); Fabrice Jossinet (Université Strasbourg, Institut de biologie moleculaire et cellulaire du CNRS); Elisabeth Villa (Max-Planck Institute for Biochemistry, Molecular Structural Biology); |
| Short Abstract: Modelling of RNA tertiary structure is still a difficult task. Here we present a workflow for RNA homology and de novo modelling followed by flexible fitting of the generated models into high-resolution cryo-EM maps using Molecular Dynamics Flexible Fitting (MDFF). |
| Long Abstract: Click Here |
| Poster W094 |
| Counting RNA pseudoknotted structures |
| Cédric Saule- Université Paris-Sud 11 and CNRS |
| Alain Denise (Université Paris-Sud 11 and CNRS, LRI & IGM); |
| Short Abstract: In 2004, Condon and coauthors classified RNA structure prediction algorithms allowing pseudoknots, according to the generality of the structure classes that they handle. We give formulas for the cardinality of several of these classes. This allows to better evaluate the tradeoff between computational complexity and expressive power of the algorithms. |
| Long Abstract: Click Here |
| Poster W095 |
| PhyloFacts: New Methods and Webservers |
| Ruchira Datta- UC Berkeley |
| Kimmen Sjölander (UC Berkeley, QB3 Institute); |
| Short Abstract: We present two new algorithms hosted within the PhyloFacts Phylogenomic Encyclopedias: http://phylofacts.berkeley.edu. INTREPID is a webserver for predicting functional sites which we have shown to produce higher accuracy on benchmark datasets. PHOG is a webserver for phylogenetic identification of orthologs that can be tuned to specific taxonomic distances. |
| Long Abstract: Click Here |
| Poster W096 |
| Combining Kernels for SVM-based Classification of protein structral sequences |
| Quan Le- University College Dublin |
| Patrice Koehl (University of California, Davis, Department of Computer Science and Genome Center); Gianluca Pollastri (University College Dublin, School of Computer Science and Informatics); |
| Short Abstract: An appealing approach to classify protein structures is to map each structure to a sequence of letters representing structural motifs, thenclassify these sequences using sequence based classifiers. Adopting an informative sequence representation, we show that the SVM with a kerned combined from different spectrum kernels significantly outperforms a SVM using spectrum kernel. |
| Long Abstract: Click Here |
| Poster W098 |
| Protein secondary structure prediction evaluation using a new tool - SSPE |
| Bogumil Konopka- Wroclaw University of Technology |
| Witold Dyrka (Wroclaw University of Technology, Faculty of Fundamental Problems of Technology); Jean-Christophe Nebel (Kingston University London, Faculty of Computing, Information Systems and Mathematics); Malgorzata Kotulska (Wroclaw University of Technology, The Faculty of Fundamental Problems of Technology); |
| Short Abstract: Secondary structure prediction is a significant stage in protein three-dimensional structure prediction. We have developed software for evaluating the efficiency of secondary structure predictors using segment overlap and standard per residue evaluation parameters. A standard evaluation procedure was proposed to validate prediction of four secondary structure predictors. |
| Long Abstract: Click Here |
| Poster W099 |
| An efficient on-line software for automatic prediction of non-coding RNA secondary structures |
| Fariza Tahi- CNRS/University of Evry/Genopole |
| No additional authors |
| Short Abstract: We propose an efficient algorithm and system called Tfold (http://tfold.ibisc.univ-evry.fr/TFold), for predicting non-coding RNA secondary structures. Tfold combines conservation, covariation and thermodynamic criteria for searching for stems including all kinds of pseudo-knots. Tfold is very competitive in terms of results quality and of time complexity comparing to existing software. |
| Long Abstract: Click Here |
| Poster W100 |
| Transmembrane protein structure determination guided by sparse experimental restrains. |
| Dominik Gront- University of Warsaw |
| David Baker (University of Washington, Department of Biochemistry); |
| Short Abstract: We combined Rosetta protein structure prediction methodology with chemical shifts measured by solid-state NMR experiments to build structures of transmembrane proteins. We used anisotropic chemical shifts and couplings to guide model building. Our primary results show the great potential in anisotropic NMR data; the structure of test proteins can be calculated at the great level of accuracy. |
| Long Abstract: Click Here |
| Poster W101 |
| Structural insight into the binding mode between the targeting domain of ALE-1 (92AA) and pentaglycine of peptidoglycan |
| Hideki Hirakawa- Kazusa DNA Research Institute |
| Hidenori Akita (Kyushu University, Graduate School of Genetic Resource Technology); Tamaki Fujiwara (Hiroshima University, Department of Bacteriology); Motoyuki Sugai (Hiroshima University, Department of Bacteriology); Satoru Kuhara (Kyushu University, Graduate School of Genetic Resource Technology); |
| Short Abstract: ALE-1 is a glycylglycine endopeptidase that selectively lyses the pentaglycine of peptidoglycan of Staphylococcus aureus, which is expected to be a next generation antibacterial agent.We proposed a mode of binding between 92AA (binding domain of ALE-1) and the pentaglycine of peptidoglycan by a binding simulation. |
| Long Abstract: Click Here |
| Poster X001 |
| Describing Simulation Experiments using the SED-ML |
| Dagmar Köhn- Universität Rostock |
| Richard Adams (The University of Edinburgh , Centre for Systems Biology); Igor Goryanin (The University of Edinburgh , Informatics Life-Sciences Institute); Frank Bergmann (Keck Graduate Institute, Applied Sciences); Fedor Kolpakov (Design Technological Institute of Digital Techniques, Institute of Systems Biology ); Michael Hucka ( Phone (626) 395-8128 Office Beckman Institute 272 California Institute of Technology, Control and Dynamical Systems); Ion Moraru (University of Connecticut, Center for Cell Analysis and Modeling); Nicolas Le Novère (European Bioinformatics Institute, Computational Neurobiology); Sven Sahle (Universität Heidelberg, Bioquant); Henning Schmidt (-, -); |
| Short Abstract: The proper use of computational models of biochemical processes requires the details of the simulation processes to run. We present the XML-based formatSED-ML for the encoding of simulation experiments. It holds information about the simulation, the models and model perturbations, the experiment setups, and the output. |
| Long Abstract: Click Here |
| Poster X002 |
| Stochastic modelling in biology |
| Yang Luo- Cambridge University |
| No additional authors |
| Short Abstract: Stochastic heterogeneity in a cell culture derived from the same environmental exposure and identical histories is a key to understanding the phenotypic variability in these cell populations. To assess the effect of stochastic fluctuations, we perform stochastic simulations after adding stochastic effect on to deterministic models. |
| Long Abstract: Click Here |
| Poster X003 |
| Computational evidence for the relationship between protein phosphorylation and protein complex formation |
| Nozomu Yachie- Keio University |
| Rintaro Saito (Keio University, Institute for Advanced Biosciences); Naoyuki Sugiyama (Keio University, Institute for Advanced Biosciences); Masaru Tomita (Keio University, Institute for Advanced Biosciences); Yasushi Ishihama (Keio University, Institute for Advanced Biosciences); |
| Short Abstract: Ｗe identified 3,774 novel phosphosites and 898 phosphoproteins in yeast cells by liquid chromatography-tandem mass spectrometry. We then integrated yeast phosphoproteome and protein interactome data to computationally demonstrate general relationship between protein phosphorylation and protein complex formation. |
| Long Abstract: Click Here |
| Poster X004 |
| Identifying and Investigating Protein Clusters in the HIV-Human Protein Interaction Network |
| Jamie MacPherson- University of Manchester |
| John Pinney (Imperial College London, Division of Molecular Biosciences); David Robertson (University of Manchester, Faculty of Life Sciences); |
| Short Abstract: Using biclustering analysis, we investigate groups of human proteins that respond in similar ways during the course of HIV-1 infection. We identify 261 significant clusters and find that many of these consist of biologically related proteins. Our results highlight ways through which HIV-1 perturbs the host cell. |
| Long Abstract: Click Here |
| Poster X005 |
| Inferring the metabolic network of Plasmodium falciparum in the host |
| Segun Fatumo- Covenant University |
| Ezekiel Adebiyi (Covenant University, Nigeria, Department of Computer and Information Sciences); Rainer König (German Cancer Research Center, Heidelberg, Theoretical Bioinformatics); |
| Short Abstract: A critical comparison disclosed that the automatic reconstruction of pathways generates manifold paths that need an expert manual verification. In this work, we support the hypothesis that the gaps in PlasmoCyc could be filled by an elaborated comparison to the human metabolic network as the parasite may take advantage of human enzymes. |
| Long Abstract: Click Here |
| Poster X006 |
| On multiple regulatory mechanisms in the tryptophan operon system in Escherichia coli: in silico study of perturbation dynamics |
| Lan Nguyen- Lincoln University |
| No additional authors |
| Short Abstract: Using mathematical models and intensive computational simulations, we show that the multiple control mechanisms that govern the tryptophan operon system in Escherichia coli, are not redundant but possess distinctive functional characteristics. Enzyme inhibition directly controls the disturbance level from perturbations. Attenuation speeds up system recovery whereas Repression lengthens recovery time. |
| Long Abstract: Click Here |
| Poster X007 |
| Reactome: a database of curated pathways |
| David Croft- European Bioinformatics Institute |
| No additional authors |
| Short Abstract: Reactome is a curated database of cellular processes in human biology. It is authored by biological researchers and maintained by the Reactome editorial staff All entries are supported by literature references. Inferred orthologous pathways in 22 other species, including mouse, worm, fly, yeast and E.coli are also available. |
| Long Abstract: Click Here |
| Poster X008 |
| Systems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related functional genomics data |
| Natasa Przulj- UC Irvine |
| Tijana Milenkovic (University of California, Irvine, Computer Science); Vesna Memisevic (University of California, Irvine, Computer Science); Anand Ganesan (University of California, Irvine, Dermatology and Biological Chemistry); |
| Short Abstract: We use a sensitive graph-theoretic method for comparing local structures of node neighborhoods to demonstrate that in human protein interaction network, topology around cancer genes is different from topology around non-cancer genes. From this observation, we identify novel cancer gene candidates, validating our predictions both biologically and in the literature. |
| Long Abstract: Click Here |
| Poster X009 |
| Functional Module Identification in Protein Interaction Networks |
| Waqar Ali- Oxford University |
| Charlotte Deane (Oxford University, Statistics); |
| Short Abstract: Current functional module detection studies based on network alignment invariably use sequence information. We investigated the use of protein function for alignment and achieved significantly better results. We went on to develop a combined method that improves the coverage of alignment results. |
| Long Abstract: Click Here |
| Poster X010 |
| Integrated analysis of multidimensional RNAi screens |
| Angela Simeone- TU Dresden |
| Claudio Collinet (Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Institute of Molecular Cell Biology and Genetics); Yannis Kalaidzidis (Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Institute of Molecular Cell Biology and Genetics); Marino Zerial (Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Institute of Molecular Cell Biology and Genetics); Andreas Beyer (TU Dresden, BIOTEC); |
| Short Abstract: Despite the technological progress genome-wide RNAi screens still cope with significant problems (off-target effects, inaccurate phenotype detection). We propose two methods that integrate high-dimensional RNAi screens with independent interaction data. These methods improve the hit detection and provide rich insights for the biological interpretation of the screen. |
| Long Abstract: Click Here |
| Poster X011 |
| Condition-dependent complex regulation in Escherichia coli |
| Karen Lemmens- KU Leuven |
| Tijl De Bie (University of Bristol, Department of Engineering Mathematics); Thomas Dhollander (KU Leuven, Department of Electrical engineering); Bart De Moor (KU Leuven, Department of Electrical engineering); Sigrid De Keersmaecker (KU Leuven, Department of Microbial and Molecular Systems (M2S)); Inge Thijs (KU Leuven, Department of Microbial and Molecular Systems (M2S)); Kristof Engelen (KU Leuven, Department of Microbial and Molecular Systems (M2S)); Kathleen Marchal (KU Leuven, Department of Microbial and Molecular Systems (M2S)); Julio Collado-Vides (Universidad Nacional Autónoma de México, Centro de Ciencias Genómicas); |
| Short Abstract: DISTILLER is a data integration framework for the inference of transcriptional modules. Experimental validation of predicted targets showed the effectiveness of our approach in Escherichia coli. In addition, the condition dependency and modularity of the inferred network was studied. Surprisingly, complex regulatory programs decreased the degree of modularity |
| Long Abstract: Click Here |
| Poster X012 |
| Identify co-conserved regulatory-metabolic network by multi-level pathway alignment |
| Yunlei Li- Delft University of Technology |
| Dick de Ridder (Delft University of Technology, Mediamatics); Marcel Reinders (Delft University of Technology, Mediamatics); |
| Short Abstract: We systematically compare the metabolic networks and transcriptional regulations of two species in the same time, with the goal of finding conserved units of evolution at both regulatory and metabolic levels. Then we generate hypotheses at one level using the information of another level, and reveal the differences between them. |
| Long Abstract: Click Here |
| Poster X013 |
| Immunology Atlas (I-ATLAS) A pathway based approach to dissect the hyerarchy of signal transduction in the dendritic cell |
| Enrica Calura- University of Firenze |
| Luca Beltrame (University of Firenze, Pharmacology); Raffaele Paola (University of Firenze, Pharmacology); Lisa Rizzetto (University of Firenze, Pharmacology); Razvan Popovic (Wayne State University, Computer Science); Sorin Draghici (Wayne State University, Computer Science); Duccio Cavalieri (University of Firenze, Pharmacology); Damariz Rivero-Guedez (University of Firenze, Pharmacology); |
| Short Abstract: Here we present a study focused on the advantages of the use cell type-specific pathways, employed by re-contructing the pathway signatures of public expression datasets on macrophage and dendritic cell in response to different stimuli, to decipher the biological complexity of the immune response depending on organism and cell-type. |
| Long Abstract: Click Here |
| Poster X014 |
| Searching for functional gene modules with interaction component models |
| Juuso Parkkinen- Helsinki University of Technology |
| Samuel Kaski (Helsinki University of Technology, Department of Information and Computer Science); |
| Short Abstract: We introduce a new probabilistic modeling framework to integrate protein-protein interactions with gene expression measurements. Our combined approach outperforms alternatives in the task of of finding functional gene modules. |
| Long Abstract: Click Here |
| Poster X015 |
| Computational Study on Signaling Pathway Networks of Fission Yeast |
| JIAN-QIN LIU- NICT-KARC |
| HIRAOKA YASUSHI (NICT-KARC/Osaka University, Biological ICT Group (Cell Biology Project)/Laboratory of Cellular Structure and Function); |
| Short Abstract: With a signaling pathway network model designed based on information theoretic measurement and methodology of systems biology, complex dynamics mechanisms of signal transduction in the fission yeast Schizosaccharomyces pombe is quantitatively analyzed, from which the transmission rate of the Byr2-Byr1-Spk1 pathway is determined for verifying the feedback function on meiosis. |
| Long Abstract: Click Here |
| Poster X016 |
| Deciphering chemotaxis pathways |
| Rebecca Hamer- University of Oxford |
| Pao-Yang Chen (University of Oxford, Statistics); Judith Armitage (University of Oxford, Oxford Centre for Integrated Systems Biology); Charlotte Deane (University of Oxford, Statistics); Gesine Reinert (University of Oxford, Statistics); |
| Short Abstract: Chemotaxis is the process whereby motile bacteria sense their environment and move towards more favourable conditions. Escherichia coli utilises a single pathway but other bacteria have more complex systems with little known about the pathways involved. We aim to predict chemotaxis pathways and determine common features across bacterial species. |
| Long Abstract: Click Here |
| Poster X017 |
| SysMO-DB: Sharing and Exchanging Systems Biology Data and Models |
| Katy Wolstencroft- University of Manchester |
| Olga Krebs (EML Research, gGmbH); Wolfgang Mueller (EML Research, gGmbH); Isabel Rojas (EML Research, gGmbH); Stuart Owen (University of Manchester, School of Computer Science); Sergejs Aleksejevs (University of Manchester, School of Computer Science); Carole Goble (University of Manchester, School of Computer Science); Jacky Snoep (University of Manchester, Manchester Centre for Integrative Systems Biology); |
| Short Abstract: SysMO-DB is a web-based data exchange environment for scientists to share Systems Biology data and models. It provides an integrated platform for the dissemination of results and methodologies from the SysMO consortium (Systems Biology of Microorganisms), demonstrating an approach for managing the interoperation between models and experimental data. |
| Long Abstract: Click Here |
| Poster X018 |
| EFFICIENT QUERY-DRIVEN AND GLOBAL BICLUSTERING OF GENE EXPRESSION DTA USING PROBABILISTIC RALATIONAL MODELS |
| hui zhao- K.U.Leuven |
| Tim Van den Bulcke (KULeuven, ESAT); Lore Cloots (KULeuven, CMPG); Kristof Engelen (KULeuven, CMPG); Tom Michoel (VIB, PSB); Bart De Moor (KULeuven, ESAT); Kathleen Marchal (KULeuven, CMPG); |
| Short Abstract: ProBic is an efficient biclustering algorithm that simultaneously identifies a set of overlapping biclusters in a gene expression dataset. It can be used in both a query-based and a global mode. Experiments on synthetic data showed that biclusters are successfully identified under various settings, both in query-driven and global setting. |
| Long Abstract: Click Here |
| Poster X019 |
| Functional Class Scoring for Metabolomics |
| Henning Redestig- Riken Plant Science Center |
| Miyako Kusano (Riken Plant Science Center, Metabolomics Research Group); Fumio Matsuda (Riken Plant Science Center, Metabolomics Research Group); Akira Oikawa (Riken Plant Science Center, Metabolomics Research Group); Hiroshi Ezura (Tsukuba University, Gene Research Center); Masanori Arita (Plant Science Center, Metabolomics Research Group); Kazuki Saito (Plant Science Center, Metabolomics Research Group); |
| Short Abstract: The use of gene class testing has become routine analysis fortranscriptomics data. Improvements in profiling techniques has made itpossible to analyze the metabolome in a similar manner. Here wedescribe an implementation and application of metabolite class testingto data from a substantial equivalence study of transformed tomato. |
| Long Abstract: Click Here |
| Poster X020 |
| Identification and quantification of Granger causality between gene sets. |
| Andre Fujita- University of Tokyo / Institute of Medical Science |
| Joao Sato (Universidade Federal do ABC, Mathematics, Computation and Cognition Center); Kaname Kojima (University of Tokyo, Human Genome Center); Luciana Gomes (University of Sao Paulo, Biochemistry); Mari Sogayar (University of Sao Paulo, Biochemistry); Satoru Miyano (University of Tokyo, Human Genome Center); |
| Short Abstract: Granger has introduced the concept of Granger causality between two variables. We generalize this concept in order to identify Granger causalities between sets of gene expressions. An identification method with a bootstrap test is proposed. This method is applied in simulated and also in actual biological gene expression data. |
| Long Abstract: Click Here |
| Poster X021 |
| Comparative Analysis of Co-expressed Protein Interaction Networks Reveals Heart Failure Related Modules |
| Chen-Ching Lin- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University |
| No additional authors |
| Short Abstract: Heart failure stems from complicate causes and is one of the main causes of death in the world. We presented a novel computational network-based approach for integration of transcriptomic and proteomic data to identify heart failure related modules which may be potential disease markers and provide new directions for heart failure therapy. |
| Long Abstract: Click Here |
| Poster X022 |
| HOW PERFECT CAN PROTEIN INTERACTOMES BE? LESSONS FROM PHOSPHOPROTEOMES |
| Emmanuel Levy- Universite de Montreal |
| Christian Landry (Universite de Montreal, Biochemistry Department); Stephen Michnick (Universite de Montreal, Biochemistry Department); |
| Short Abstract: Phosphorylation sites (phosphosites) characterized by phosphoproteomics methods are not globally conserved compared to random serines and threonines, and are as likely to be polymorphic. However, among dataset of manually curated phosphosites, those of known function are significantly more conserved, suggesting that the rapid evolution of phosphoproteomes results from a fraction non-functional phosphosites. |
| Long Abstract: Click Here |
| Poster X023 |
| Automatic layout tool for large-scale metabolic pathway models based on KEGG Atlas and SBML/SBGN |
| Nobuhiro Kido- Institute for Advanced Biosciences, Keio University |
| Nobuaki Kono (Institute for Advanced Biosciences, Keio University, Bioinformatics); Kazuharu Arakawa (Institute for Advanced Biosciences, Keio University, Bioinformatics); Masaru Tomita (Institute for Advanced Biosciences, Keio University, Bioinformatics); |
| Short Abstract: We present a software tool that lays out large-scale metabolic pathway models in SBML format according to the coordinates of KEGG Atlas using SBGN, so that users can intuitively edit the model on CellDesigner. This tool is available at http://g-language.org/metal/. |
| Long Abstract: Click Here |
| Poster X024 |
| Validation of ChIP-chip targets by query-driven biclustering |
| Riet De Smet- KULeuven |
| Thomas Dhollander (KULeuven, ESAT); Inge Thijs (KULeuven, CMPG); Kristof Engelen (KULeuven, CMPG); Kathleen Marchal (KULeuven, CMPG); |
| Short Abstract: Due to problems with non-functional binding and experiment noise ChIP-chip experiments often yield a lot of false positive results. Here we illustrate how an improved query-driven biclustering method together with a microarray compendium can be used to verify and extend the knowledge on the regulatory network obtained by ChIP-chip. |
| Long Abstract: Click Here |
| Poster X025 |
| Executable Modeling of the EGFR Signalling Pathway. |
| Dennis Wang- University of Cambridge |
| Jasmin Fisher (Microsoft Research, Computational Biology); Luca Cardelli (Microsoft Research, Programming Principles and Tools); Nir Piterman (Imperial College London, Computing); Andrew Phillips (Microsoft Research, Computational Biology); |
| Short Abstract: Using stochastic pi-calculus we developed a model for describing the dynamics of the EGFR signaling pathway. Perturbation of the model allows us to characterize key control mechanisms in the signaling pathway. Partitioning the model into signaling modules summarizes the control mechanisms and facilitates the abstraction of the model. |
| Long Abstract: Click Here |
| Poster X026 |
| Probabilistic Network Clustering in Euclidean Space |
| Robert Gevers- Purdue University |
| Olga Vitek (Purdue University, Statistics); |
| Short Abstract: We propose an approach to clustering protein interaction networks that is based on embedding the network into Eucledian space. Advantages include a natural mechanism for incorporating additional, context-specific experimental measurements associated with the proteins, inference on the number of clusters, and probabilistic representations of cluster membership. |
| Long Abstract: Click Here |
| Poster X027 |
| Exploring type-2 Diabetes Protein Interactions Network by modeling their complex structures |
| Aggeliki Kosmopoulou- UPF |
| No additional authors |
| Short Abstract: The exact causes of type-2 diabetes mellitus (T2DM), a metabolic disorder that is primarily characterized by insulin resistance, relative insulin deficiency and hyperglycemia, are not completely understood. Here, we apply a method for delineating the interacting motifs of hub proteins to discover their roles in type-2 Diabetes Protein Interaction Network. |
| Long Abstract: Click Here |
| Poster X028 |
| IDENTIFICATION OF PROTEIN-PROTEIN INTERACTION DOMAINS |
| SALIHA OZBABACAN- KOC UNIVERSITY |
| ATILLA GURSOY (KOC UNIVERSITY, CENTER FOR COMPUTATIONAL BIOLOGY AND BIOINFORMATICS AND COLLEGE OF ENGINEERING); OZLEM KESKIN (KOC UNIVERSITY, CENTER FOR COMPUTATIONAL BIOLOGY AND BIOINFORMATICS AND COLLEGE OF ENGINEERING); |
| Short Abstract: This project focuses on interaction domains, which play a crucial role in the regulation of different cellular processes, through two aspects: by classifying interaction domains in order to differentiate them from other domains via machine learning tool and by structurally comparing them with the nonredundant template interfaces obtained from PDB. |
| Long Abstract: Click Here |
| Poster X029 |
| Atacking Interface & Interaction Networks |
| Billur Engin- Koc University |
| Ekin Tuzun (Koc University, Center for Computational Biology and Bioinformatics and College of Engineering); Atilla Gursoy (Koc University, Center for Computational Biology and Bioinformatics and College of Engineering); Ozlem Keskin (Koc University, Center for Computational Biology and Bioinformatics and College of Engineering); |
| Short Abstract: Here, networks resulting from integration of binding site information of the proteins into PPI networks (Interface & Interaction Networks) are presented. Various attack strategies with several network parameters are performed on these networks and we analyzed the robustness of these networks. |
| Long Abstract: Click Here |
| Poster X030 |
| Human Protein-Protein Interaction Network: a Structural Perspective |
| Gozde Kar- Koc University |
| Attila Gursoy (Koc University, Center for Computational Biology and Bioinformatics); Ozlem Keskin (Koc University, Center for Computational Biology and Bioinformatics); |
| Short Abstract: We provide a detailed analysis of human protein-protein interaction network which contains cancer-related interactions and characterize the interactions using three-dimensional protein structures. The results reveal distinctive characteristics of cancer-related interactions; they have smaller, more planar and more hydrophilic binding sites which may indicate low affinity and high specificity of them. |
| Long Abstract: Click Here |
| Poster X031 |
| Pathway Projector: Web-based Zoomable Pathway Browser using KEGG Atlas and Google Maps API |
| Nobuaki Kono- Institute for Advanced Biosciences, Keio University |
| Kazuharu Arakawa (Institute for Advanced Biosciences, Keio University, Media & Governance); Nobuhiro Kido (Institute for Advanced Biosciences, Keio University, Environment & Info.); Ryu Ogawa (Institute for Advanced Biosciences, Keio University, Media & Governance); Kazuki Oshita (Institute for Advanced Biosciences, Keio University, Environment & Info.); Keita Ikegami (Institute for Advanced Biosciences, Keio University, Environment & Info.); Satoshi Tamaki (Institute for Advanced Biosciences, Keio University, Environment & Info.); Masaru Tomita (Institute for Advanced Biosciences, Keio University, Environment & Info.); |
| Short Abstract: Pathway Projector is a web application for browsing global pathway map based on KEGG Atlas, with zoomable user interface implemented using Google Maps API. This application allows numerous interactive queries, as well as data mapping from -omics experiments. Pathway Projector is available at: http://www.g-language.org/PathwayProjector/. |
| Long Abstract: Click Here |
| Poster X032 |
| Stochastic Simulation of T-Cell Activation |
| Wolfgang Schreiner- Medical University Vienna |
| Bernhard Knapp (Medical University Vienna, Medical statistics and Informatics); rudolf Karch (Medical University Vienna, Medical statistics and Informatics); Michael Cibena (Medical University Vienna, Medical statistics and Informatics); |
| Short Abstract: We present an agent based simulation of epitope detection by MHC-peptide-TCR – complexes. Cooperative phenomena are modelled to investigate the mechanism that gives rise to a realistic discrimination between self and pathogen peptides. |
| Long Abstract: Click Here |
| Poster X033 |
| Analysing perturbational effects at systems level by data-integration. |
| Anagha Joshi- VIB/ Gent university |
| Tom Michoel (VIB/ Gent university, Plants systems biology); Yves van de Peer (VIB/ Gent university, Plants systems biology); Thomas van Parys (VIB/ Gent university, Plants systems biology); |
| Short Abstract: when transcription factor is perturbed, we observed that only 2% ofdifferentially expressed targets were direct transcriptional. We used a compendium of overexpression and deletion experiments in S. cerevisiae and examinedregulatory paths which combine transcriptional, protein-protein and phosphorylation interactions. We found 8 overrepresented paths which explain 10% of differentially expressed targets. |
| Long Abstract: Click Here |
| Poster X034 |
| Exploring Transcription Factor Target Gene Relationships by Condition-dependent Module Networks |
| Hasan Ogul- Helsinki University of Technology |
| Jarkko Salojarvi (Helsinki University of Technology, Department of Information and Computer Science); Pinja Jaspers (University of Helsinki, Department of Biological and Environmental Sciences); Antti Ajanki (Helsinki University of Technology, Department of Information and Computer Science); Mikael Brosché (University of Helsinki, Department of Biological and Environmental Sciences); Jaakko Kangasjärvi (University of Helsinki, Department of Biological and Environmental Sciences); Samuel Kaski (Helsinki University of Technology, Department of Information and Computer Science); |
| Short Abstract: We present a probabilistic model for inferring local regulatory networks and transcription factor target gene relationships based on condition-dependent Bayesian module networks and promoter motif analysis. |
| Long Abstract: Click Here |
| Poster X035 |
| From the zebrafish embryo toxicity test to systems toxicology: The development of a multifactorial knowledge base and bioinformatics tools to optimise data interpretation |
| Marion Reuter- Fraunhofer Gesellschaft |
| Martina Fenske (Fraunhofer Gesellschaft, IME); Torben Söker (Fraunhofer Gesellschaft, IME); Christoph Schäfers (Fraunhofer Gesellschaft, IME); Viktoria Schiller (Fraunhofer Gesellschaft, IME); Arne Wichmann (Fraunhofer Gesellschaft, IME); |
| Short Abstract: UNIFISH uses phenotypic and systemic changes in zebrafish embryos to assess chemical toxicity and to screen bioactive compounds. Experimental data together with public database information are compiled and managed in a multifactorial knowledge base. The knowledge base provides the fundamental basis for the development of customised automated high-throughput testing systems. |
| Long Abstract: Click Here |
| Poster X036 |
| Integrative Analysis of Type 2 Diabetes Protein Interaction Network and OMIM Database Reveals Associations between Complex Disorders |
| Binnaz Coskunkan- Yeditepe University |
| Deniz Rende (Yeditepe University and Bogazici University, Department of Chemical Engineering); Nihat Baysal (Yeditepe University, Department of Chemical Engineering); Betul Kirdar (Bogazici University, Department of Chemical Engineering); |
| Short Abstract: This study aims to investigate the associations between type 2 diabetes and other complex diseases. Disease related protein interaction network was constructed, transformed to a line graph and clustered into functional modules. The integration of pathway, localization and disease terms with functional modules indicates strong coherence of complex diseases. |
| Long Abstract: Click Here |
| Poster X037 |
| Human gene coexpression network built with a robust reverse engineering method: deciphering functional, transcriptional and topological information |
| Carlos Prieto- Cancer Research Center (CIC-IMBCC, CSIC/USAL) |
| Carlos Prieto (Cancer Research Center (CIC-IMBCC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); Alberto Risueño (Cancer Research Center (CIC-IMBCC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); Celia Fontanillo (Cancer Research Center (CIC-IMBCC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); Javier De Las Rivas (Cancer Research Center (CIC-IMBCC, CSIC/USAL), Bioinformatics and Functional Genomics Research Group); |
| Short Abstract: Human genome-wide expression data from normal-healthy tissues is used to built a confident human gene coexpression network with a new robust method. Further functional and topology analysis of the network defines critical nodes and shows functional coherent biological modules that share common transcription factors. |
| Long Abstract: Click Here |
| Poster X038 |
| Finding new drug candidates against Mycobacterium tuberculosis using protein-protein interaction networks |
| Gabor Ivan- PhD Student |
| Dániel Bánky (Eotvos Lorand University, Department of Computer Science); Vince Grolmusz (Eotvos Lorand University, Department of Computer Science); |
| Short Abstract: We created the metabolic (including the MTB-specific mycolic acid pathway) and physical protein-protein interaction (PPI) networks of Mycobacterium tuberculosis (MTB). We then merged the two types of networks to a single one which is currently being used for estimating new protein targets for drug candidates against MTB. |
| Long Abstract: Click Here |
| Poster X039 |
| A method for atherosclerotic plaque growth based on a markup representation of blood flow simulation |
| Stefanos Konstantinos Petsios- Unit of Medical Technology & Intelligent Information Systems University of Ioannina |
| Antonis Sakellarios (Unit of Medical Technology & Intelligent Information Systems University of Ioannina, Computer Science); Dimitrios I. Fotiadis (Unit of Medical Technology & Intelligent Information Systems University of Ioannina, Computer Science); |
| Short Abstract: We propose a formal XML like representation of blood flow simulation (BFS) results. It contains the required data for preprocessing, the produced results and the metadata related with the BFS. We use these results to construct a mathematical model of the early plaque formation in the artery and blood flow. |
| Long Abstract: Click Here |
| Poster X040 |
| Using monochromatic purity to select gene sets |
| Magali Michaut- University of Toronto |
| Gary Bader (University of Toronto, Terrence Donnelly CCBR); |
| Short Abstract: We aim to automatically select gene sets from GO at an appropriate level of the hierarchy to best annotate a given genomic data set. We analyze quantitative positive and negative genetic interactions and select gene sets by monochromatic purity (the ratio of positive to negative interactions). |
| Long Abstract: Click Here |
| Poster X041 |
| Deciphering the regulation of cell cycle progression by cell adhesion using an integrated network of gene interactions |
| Marcio Acencio- Sao Paulo State University - Institute of Biosciences of Botucatu |
| No additional authors |
| Short Abstract: To better understand the regulation of cell cycle progression by celladhesion, we constructed a human integrated network of geneinteractions likely involved with this phenotype and then calculatednetwork centrality measures and performed functional analysis toreveal important pathways and genes involved with the regulation of cell cycle progression bycell adhesion. |
| Long Abstract: Click Here |
| Poster X042 |
| Beyond linearity in the relationship between DNA copy number alterations and mRNA expression in Breast Cancer |
| Hiroko Solvang- Norwegian Radium Hospital University Hospital, University of Oslo |
| Ole Christian Lingjærde (University of Oslo, Department of Informatics); Arnoldo Frigessi (University of Oslo, Institute of Basic Medical Research); Vessela Kristensen (Norwegian Radiumhospital, University of Oslo, Department of Genetics, Medical Faculty); Anne-Lise Børresen-Dale (Norwegian Radium Hospital, University of Oslo, Department of Genetics); |
| Short Abstract: For the investigation related to the variation in gene expression attributable to variation in gene copy number among breast tumors, we propose a statistical analysis including comparison with the linear and nonlinear relationship to identify the regulatory mechanisms of abnormal mRNA expression. |
| Long Abstract: Click Here |
| Poster X043 |
| Dissecting disease progression of Chronic Lymphocytic Leukemia using an integrated quantitative proteomic and genomic analysis |
| Han-Yu Chuang- Univ. Of California San Diego |
| Zhouxin Shen (UCSD, Biology); Laura Ressenti (UCSD, Medicine); Steve Briggs (UCSD, Biology); Thomas Kipps (UCSD, Medicine); Trey Ideker (UCSD, Bioengineering); |
| Short Abstract: We developed a shotgun method to quantify protein expression correlated with progression of chronic lymphocytic leukemia. Our protein markers are more functionally related, consistent with gene expression and robust across patient cohorts. We found that protein differential expression is coherent with their interaction, enabling prediction of expression for unmeasured proteins. |
| Long Abstract: Click Here |
| Poster X044 |
| A WEB-BASED APPLICATION FOR EVALUATING PARAMETER IDENTIFIABILITY OF BIOCHEMICAL MODELS IN POLYNOMIAL FORM |
| Marcos Simoes- INESC-ID Lisbon |
| Susana Vinga (INESC-ID Lisbon, kdbio Group); |
| Short Abstract: State-space models are often used for the quantitative modelling of biochemical systems. Alongside parameter estimation, a necessary (and early) step in the building of such models is the assessment of structural identifiability properties. We present a web-based application that computes these properties for polynomial models in a completely automated manner. |
| Long Abstract: Click Here |
| Poster X045 |
| Core stemness mechanisms revealed through homology |
| Martina Koeva- University of California, Santa Cruz |
| Josh Stuart (University of California, Santa Cruz, Department of Biomolecular Engineering); Camilla Forsberg (University of California, Santa Cruz, Department of Biomolecular Engineering); |
| Short Abstract: Few stemness genes required for core stem cell function across many stem cell types have been identified through transcriptional profiling. We developed a computational approach to test for stemness groups, which show frequent upregulation in many stem cell types and utilize paralogous genes for functionally similar or equivalent purposes. |
| Long Abstract: Click Here |
| Poster X046 |
| Modeling the Dynamics of SIRT1 Regulation |
| Augustin Luna- Boston University/National Cancer Institute |
| Kurt Kohn (National Cancer Institute, Laboratory of Molecular Pharmacology); Geoffrey McFadden (National Institute of Standards and Technology, Mathematical Modeling Group); Mirit Aladjem (National Cancer Institute, Laboratory of Molecular Pharmacology); |
| Short Abstract: We propose a mathematical model describing the dynamics of control loops involved in the regulation of SIRT1, a histone deacetylase implicated in aging. The model is the basis for simulation studies aimed at determining how SIRT1 levels affect elements critical to the DNA damage response induced by ionizing radiation. |
| Long Abstract: Click Here |
| Poster X047 |
| Inferring gene networks from short time-series microarray datasets under different biological conditions |
| Teppei Shimamura- University of Tokyo |
| Teppei Shimamura (University of Tokyo, Human Genome Center, Institute of Medical Science); Seiya Imoto (University of Tokyo, Human Genome Center, Institute of Medical Science); Rui Yamaguchi (University of Tokyo, Human Genome Center, Institute of Medical Science); Masao Nagasaki (University of Tokyo, Human Genome Center, Institute of Medical Science); Yoshinori Tamada (University of Tokyo, Human Genome Center, Institute of Medical Science); Satoru Miyano (University of Tokyo, Human Genome Center, Institute of Medical Science); |
| Short Abstract: We develop a new approach for incorporating multiple time-series datasets measuring the expressions of the same set of genes under different experimental conditions in inferring gene network from short time-series data. We apply this methodology to structure learning of dynamic Bayesian networks from multiple short time-series datasets. |
| Long Abstract: Click Here |
| Poster X048 |
| Neutral Network models for Biochemical Systems |
| Marco Vilela- ITQB/UNL |
| Susana Vinga (INESC, Bioinformatics); Marco Grivet Mattoso Maia (PUC, Centro de Estudo em Telecomunicações); Eberhard Voit (Georgia Institute of Technology and Emory University, Integrative BioSystems Institute and Dept. Biomedical Engineering); Jonas Almeida (University of Texas M.D. Anderson Cancer Center, Dept. Bioinformatics and Computational Biology); |
| Short Abstract: The major difficulty in modeling biological systems from time series is the identification of parameter sets that gives the model a desired behavior. This work shows that different parameter sets with different model’s structure can give rise to similar dynamical behavior, relating it to the system’s robustness and evolvability |
| Long Abstract: Click Here |
| Poster X049 |
| From Use Case to User Base: Developing a 3R Implementation for Community Use. |
| Hannah Tipney- University of Colorado Denver |
| William Baumgartner Jr (University of Colorado Denver, Center for Computational Pharmacology, School of Medicine); Ronald Schuyler (University of Colorado Denver, Center for Computational Pharmacology, School of Medicine); Lawrence Hunter (University of Colorado Denver, Center for Computational Pharmacology, School of Medicine); |
| Short Abstract: Although hugely useful as investigative tools, networks and associated software are often viewed as impenetrable by biologists, the very users they are supposed to support. We present several barriers to network use and illustrate how we addressed them, moving the Hanalyzer from its interesting use case to wider user base. |
| Long Abstract: Click Here |
| Poster X050 |
| An atlas of combinatorial transcriptional regulation in mouse and man |
| Carlo Cannistraci- Polytechnic of Turin |
| Vladimir B. Bajic (University of the Western Cape, South African National Bioinformatics Institute); Kai Tan (University of California San Diego, Department of Bioengineering, Jacobs School of Engineering); Shintaro Katayama (RIKEN Yokohama Institute, RIKEN Omics Science Center); Alistair R. R. Forrest (Griffith University, The Eskitis Institute for Cell and Molecular Therapies); Nicolas Bertin (RIKEN Yokohama Institute , RIKEN Omics Science Center); Piero Carnici (RIKEN Yokohama Institute , RIKEN Omics Science Center); Jesper Tegnér ( Karolinska University Hospital Solna SE, Computational Medicine Group, Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet); Sarah A. Teichmann (Cambridge CB2 0QH , MRC Laboratory of Molecular Biology); Harukazu Suzuki (RIKEN Yokohama Institute , RIKEN Omics Science Center); Yoshihide Hayashizaki (RIKEN Yokohama Institute , RIKEN Omics Science Center); Trey Ideker (University of California San Diego , Department of Bioengineering, Jacobs School of Engineering); Timothy Ravasi (University of California San Diego , Department of Bioengineering, Jacobs School of Engineering); |
| Short Abstract: We present a systems approach to study mammalian transcription regulatory networks (TRNs). By integration of genome-wide measurements of several cellular components across tissues and time, we identified two distinct classes of TRN hubs displaying specific topological and functional properties. Furthermore we mapped tissues&time-specific combinatorial regulatory sub-networks. |
| Long Abstract: Click Here |
| Poster X051 |
| Introduction and application of CellExpress, a new database for studying human tissue-specific gene expression |
| Larisa Kiseleva- AIST |
| Raymond Wan (AIST, CBRC); Paul Horton (AIST, CBRC); |
| Short Abstract: We introduce the CellExpress database, the storing gene expression data from (currently) 10,000 samples classified in a tissue specific manner. The data gathered has been used for visualizing human cell/tissue type relationships and identifying tissue-specific transcription factors. |
| Long Abstract: Click Here |
| Poster X052 |
| Asymmetric relationships between proteins shape genome evolution |
| Bas Dutilh- Radboud University Nijmegen Medical Centre |
| Richard A. Notebaart (Radboud University Nijmegen Medical Centre, CMBI); Philip R. Kensche (Radboud University Nijmegen Medical Centre, CMBI); Martijn A. Huynen (Radboud University Nijmegen Medical Centre, CMBI); |
| Short Abstract: Relationships between enzymes are often asymmetric: protein A requires protein B to function, but B can function without A (A->B). This asymmetry predictably biases genomic variables like presence of orthologs, gene expression and the effect of knockouts. This bias is strongest for proteins whose asymmetric relationship is evolutionarily conserved. |
| Long Abstract: Click Here |
| Poster X053 |
| Predicting pathways in yeast using genome-wide phenotype data. |
| Brian Peyser- USAMRIID |
| No additional authors |
| Short Abstract: I developed a score connecting yeast deletion mutants by adapting Resnik's application of shared information content. Translation of the shared information technique to distributions of phenotypes generated similarity scores which connect genes with related functions. This does not require similar phenotype data distributions and scores are easily updated. |
| Long Abstract: Click Here |
| Poster X054 |
| HEFalMp: Integrating 30,000 experimental conditions to predict systems-level relationships in H. sapiens |
| Curtis Huttenhower- Princeton University |
| Erin Haley (Princeton University, Molecular Biology); Hilary Coller (Princeton University, Molecular Biology); Olga Troyanskaya (Princeton University, Computer Science); |
| Short Abstract: The HEFalMp system is a data integration technique that produces functional maps, each summarizing the results most relevant to a particular gene, pathway, or disease of interest. These comprise over 200 areas of human cellular biology, include information from ~30,000 genome-scale experiments, and provide a focus on the molecular mechanisms of genetic disorders. |
| Long Abstract: Click Here |
| Poster X056 |
| Systems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related functional genomics data |
| Tijana Milenkovic- University of California, Irvine |
| Natasa Przulj (University of California, Irvine, Computer Science); Vesna Memisevic (University of California, Irvine, Computer Science); Anand Ganesan (University of California, Dermatology and Biological Chemistry); |
| Short Abstract: We use a sensitive graph-theoretic method for comparing local structures of node neighborhoods to demonstrate that in human protein interaction network, topology around cancer genes is different from topology around non-cancer genes. From this observation, we identify novel cancer gene candidates, validating our predictions both biologically and in the literature. |
| Long Abstract: Click Here |
| Poster X057 |
| Biological convergence of cancer signatures |
| Xavier Solé- Catalan Institute of Oncology - IDIBELL |
| Núria Bonifaci (Catalan Institute of Oncology, IDIBELL, Bioinformatics and Biostatistics Unit); Núria López-Bigas (Barcelona Biomedical Research Park, Research Unit on Biomedical Informatics of IMIM/UPF); Antoni Berenguer (Catalan Institute of Oncology, IDIBELL, Bioinformatics and Biostatistics Unit); Pilar Hernández (Catalan Institute of Oncology, IDIBELL, Translational Research Laboratory); Oscar Reina (Catalan Institute of Oncology, IDIBELL, Unit of Infections and Cancer, CIBERESP, Epidemiology Research of Cancer Program); Christopher A. Maxwell (Catalan Institute of Oncology, IDIBELL, Translational Research Laboratory); Helena Aguilar (Catalan Institute of Oncology, IDIBELL, Translational Research Laboratory); Ander Urruticoechea (Catalan Institute of Oncology, IDIBELL, Translational Research Laboratory); Silvia de Sanjosé (Catalan Institute of Oncology, IDIBELL, Unit of Infections and Cancer, CIBERESP, Epidemiology Research of Cancer Program); Francesc Comellas (Technical University of Catalonia, Department of Applied Mathematics IV); Gabriel Capellá (Catalan Institute of Oncology, IDIBELL, Translational Research Laboratory); Víctor Moreno (Catalan Institute of Oncology, IDIBELL, Bioinformatics and Biostatistics Unit); Miguel Angel Pujana (Catalan Institute of Oncology, IDIBELL, Bioinformatics and Biostatistics Unit); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster X058 |
| Transcriptional gene regulatory network analysis with CoryneRegNet |
| Jan Baumbach- International Computer Science Institute |
| No additional authors |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster X059 |
| Co-Expression among Constituents of a Motif in the Protein-Protein Interaction Network |
| Nitin Bhardwaj- Yale University |
| No additional authors |
| Short Abstract: We show that the robustness of protein interaction system emerges from a proportionate synchronicity among the constituents of motifs via co-expression and this co-expression correlates strongly with the motif complexity. We further show that such biological coherence among component proteins can be reinforced by integrating conservation data in the analysis. |
| Long Abstract: Click Here |
| Poster X060 |
| Analysis of Gene Sets Based on the Underlying Regulatory Network |
| Ali Shojaie- Student/University of Michigan |
| George Michailidis (University of Michigan, Statistics); |
| Short Abstract: We consider simultaneous analysis of changes in expression levels and interactions among genes. We propose a latent variable model that can directly incorporate network information. Exploiting the flexibility of mixed linear models, we propose an efficient inference procedure for analysis of pathways which isolates the effect of each subnetwork. |
| Long Abstract: Click Here |
| Poster X061 |
| Benchmarking examples for pathway analysis tools |
| Luis de Figueiredo- Friedrich-Schiller-Universität Jena |
| Stefan Schuster (Friedrich-Schiller-Universität Jena, Lehrstuhl Bioinformatik); Christoph Kaleta (Friedrich-Schiller-Universität Jena, Lehrstuhl Bioinformatik); David A. Fell (Oxford Brookes University, School of Life Sciences); |
| Short Abstract: The concept of elementary flux modes has been used for prediction of metabolic pathways. Alternative approaches have been proposed, which are based on graph theory and neglect the mass balance of co-substrates and by-products. Here, we present benchmark examples by which pathway analysis tools can be compared. |
| Long Abstract: Click Here |
| Poster X062 |
| Robust simplifications of multiscale biochemical networks with application to NFkB modeling |
| Andrei Zinovyev- Institut Curie |
| Ovidiu Radulescu (University of Rennes, Mathematics); Alexander Gorban (University of Leicester, Mathematics); Alain Liliennbaum (CNRS, UMR 7000); |
| Short Abstract: We develop a limitation-based theory of model reduction both for linear and nonlinear networks. We demonstrate how our methods can be applied for simplifying a complex model of NFkB signalling. Our approach generates a hierarchy of simplified models, levels of which can be compared with existing models of NFkB signalling. |
| Long Abstract: Click Here |
| Poster X063 |
| On the use and misuse of GO biological process annotations |
| Monica Chagoyen- Centro Nacional de Biotecnologia - CSIC |
| Florencio Pazos (Centro Nacional de Biotecnologia - CSIC , de); |
| Short Abstract: We analyze the biological cohesiveness of the processes in the Gene Ontology (GO) using data from STRING functional network. We also evaluate the direct and indirect relationships established in GO, and discuss its implications for the analysis of system-wide data. |
| Long Abstract: Click Here |
| Poster X064 |
| Generalized Nested Effects Models for Reconstructing Protein Signaling Networks from Multiple Interventions |
| Christian Bender- German Cancer Research Center |
| Holger Fröhlich (Cellzome AG, Bioinformatics); Özgur Sahin (German Cancer Research Center, Molecular Genome Analysis); Dorit Arlt (German Cancer Research Center, Molecular Genome Analysis); Tim Beissbarth (University of Goettingen, Medical Statistics); |
| Short Abstract: In this work we propose an approach to analyse protein expression data after siRNA-mediated knockdowns called 'Generalized Nested Effects Models'. We monitor the intervention effects in few timepoint-measurements. Reconstruction of signaling networks happens by combining incoming signals at each node via boolean functions and propagating effects accordingly through the network. |
| Long Abstract: Click Here |
| Poster X065 |
| InnateDB and Cerebral Facilitate the Systems-Level Analysis of Large Datasets: Case Studies |
| Jennifer Gardy- University Of British Columbia |
| David Lynn (Simon Fraser University, Department of Molecular Biology & Biochemistry); Robert Hancock (University Of British Columbia, Centre For Microbial Diseases & Immunity Research); Fiona Brinkman (Simon Fraser University, Department of Molecular Biology & Biochemistry); |
| Short Abstract: InnateDB (www.innatedb.ca) is a comprehensive interaction/pathway database and systems biology analysis environment designed to facilitate analysis and visualization (through Cytoscape/Cerebral) of complex quantitative datasets from human and mouse. We describe a workflow taking an InnateDB user from spreadsheet to network, and apply this workflow to complex host response expression profiles. |
| Long Abstract: Click Here |
| Poster X066 |
| Learning the role of the transcriptional co-regulator NC2 in early mesoderm development |
| Mikhail Spivakov- European Molecular Biology Laboratory |
| Hitoshi Aihara (Cornell University, Weill Medical College); Ya-Hsin Liu (European Molecular Biology Laboratory, Gene Expression Unit); Robert Zinzen (European Molecular Biology Laboratory, Gene Expression Unit); Charles Girardot (European Molecular Biology Laboratory, Gene Expression Unit); Martina Braun (European Molecular Biology Laboratory, Gene Expression Unit); Yutaka Nibu (Cornell University, Weill Medical College); Ewan Birney (European Molecular Biology Laboratory, EMBL-EBI); Eileen Furlong (European Molecular Biology Laboratory, Gene Expression Unit); |
| Short Abstract: We analysed the binding of transcriptional regulator NC2 in Drosophila mesoderm and integrated the data with our previous analyses of mesodermal transcriptional networks. The application of statistical learning approaches suggests a co-operative effect of NC2 and Twist in the 'priming' of mesodermal CRMs for future binding of lineage-specific transcription factors. |
| Long Abstract: Click Here |
| Poster X067 |
| A Method for Inference of Gene Regulatory Networks based on Bayesian Network with Clustering of Time-Series Subsequences |
| Yuya Shuto- Graduate School of Information Science and Technology, Osaka University |
| Shigeto Seno (Graduate School of Information Science and Technology, Osaka University, Bioinfomatic Engineering); Yoichi Takenaka (Graduate School of Information Science and Technology, Osaka University, Bioinfomatic Engineering); Hideo Matsuda (Graduate School of Information Science and Technology, Osaka University, Bioinfomatic Engineering); |
| Short Abstract: We propose a method for the inference of gene regulatory networks based on Bayesian network with subsequences of time-series gene expression profiles. Proposed method is effective for analysis of time-series expression data and infers more accurate networks than the other existing methods. |
| Long Abstract: Click Here |
| Poster X068 |
| Mathematical modelling of cell-fate decision in response to death receptor engagement |
| Laurent Tournier- Institut Curie |
| Laurence Calzone (Institut Curie, U900 INSERM - Curie - Ecole des Mines ParisTech); Simon Fourquet (Institut Curie, U900 INSERM - Curie - Ecole des Mines ParisTech); Emmanuel Barillot (Institut Curie, U900 INSERM - Curie - Ecole des Mines ParisTech); Andrei Zinovyev (Institut Curie, U900 INSERM - Curie - Ecole des Mines ParisTech); Denis Thieffry (Technologies Avancées pour le Génome et la Clinique, Département de Biologie); |
| Short Abstract: We present a model of cell decision between three cellular fates: survival, apoptosis and non-apoptotic cell death, in response to death receptor engagement. A qualitative dynamical model is constructed, and analysed using discrete systems techniques. The obtained qualitative results are then used to validate the network structure. |
| Long Abstract: Click Here |
| Poster X069 |
| Semantic signature: comparative concept lattice analysis for gene expression microarray data on a semantic space |
| Jihun Kim- Seoul National University Biomedical Informatics (SNUBI) |
| Keewon Kim (Seoul National University Biomedical Informatics, Department of medicine); SangJay Bien (Seoul National University Biomedical Informatics, Department of medicine); Juhan Kim (Seoul National University Biomedical Informatics, Department of medicine); |
| Short Abstract: In this study, the semantic space was constructed as absolute universal platform for the comparative microarray analysis. Comparing different geographies of concept lattices from different categories of microarray experiments revealed the semantic signatures. |
| Long Abstract: Click Here |
| Poster X070 |
| Discovering cancer pathways through logic network inference |
| Jeroen de Ridder- Delft University of Technology |
| Jan Bot (Delft University of Technology, Bioinformatics Group); Jaap Kool (Netherlands Cancer Institute, Division of Molecular Genetics); Anthony Uren (Netherlands Cancer Institute, Division of Molecular Genetics); Marcel Reinders (Delft University of Technology, Bioinformatics Group); Lodewyk Wessels (Netherlands Cancer Institute, Bioinformatics and Statistics Group); |
| Short Abstract: In this study we have expression profiled 43 tumors that were induced by retroviral insertional mutagenesis. From these data we infer combinatorial association logic networks - using a novel method - that are capable of capturing complex associations between the initiating events (the viral integration sites) and the consequent downstream expression profiles. |
| Long Abstract: Click Here |
| Poster X071 |
| Ondex data integration applied to the annotation of durum wheat time-series microarray data |
| Matthew Hindle- Rothamsted Research |
| Marcela Baudo (Rothamsted Research, Plant Science); Micheal Defoin-Platel (Rothamsted Research, Biomathematics and Bioinformatics); Stephen Powers (Rothamsted Research, Biomathematics and Bioinformatics); Charlie Hodgman (University of Nottingham, Multidisciplinary Centre for Integrative Biology); Christopher Rawlings (Rothamsted Research, Biomathematics and Bioinformatics); Mansoor Saqi (Rothamsted Research, Bioinformatics and Biomathmatics); Dimah Habash (Rothamsted Research, Plant Science); |
| Short Abstract: A common challenge in microarray analysis is the compiling of up-to-date annotations from multiple biological domains. This situation is compounded in partially sequenced organisms like durum wheat. This study demonstrates how data integration techniques can be used to extract the latest data from multiple databases that span disparate biological domains. |
| Long Abstract: Click Here |
| Poster X072 |
| Characterizing microRNA regulatory modules that govern combinatorial regulation using matched microRNA-mRNA expression profile data |
| Young-Ji Na- Seoul National University Biomedical Informatics (SNUBI) |
| Ju Han Kim (Seoul National University Biomedical Informatics (SNUBI) , Biomedical science); |
| Short Abstract: There are attempts to identify miRNA regulatory modules by research groups. The novelty of our approach is characterizing miRNA regulatory modules that govern combinatorial regulation. We report that the distinct regulatory roles of the miRNAs using matched microRNA-mRNA expression profile data. |
| Long Abstract: Click Here |
| Poster X073 |
| Enrichment Map: a network-based method for gene-set enrichment visualization and interpretation |
| Daniele Merico- University of Toronto |
| Ruth Isserlin (University of Toronto, Banting & Best Dept. of Medical Research - Donnelly CCBR); Oliver Stueker (University of Toronto, Banting & Best Dept. of Medical Research - Donnelly CCBR); Andrew Emili (University of Toronto, Banting & Best Dept. of Medical Research - Donnelly CCBR); Gary Bader (University of Toronto, Banting & Best Dept. of Medical Research - Donnelly CCBR); |
| Short Abstract: High-throughput genomic experiments typically lead to the identification of large gene-lists. Gene-set enrichment analysis has been successfully applied to functionally summarize such data. However, the number and mutual overlap of gene-sets constitutes a critical barrier. To address this problem, we propose a network visualization of enrichment results, called Enrichment Map. |
| Long Abstract: Click Here |
| Poster X074 |
| A framework for identifying cross patterns in systems biology: application to chemogenomics |
| Tara Gianoulis- Yale University |
| Ashish Agarwal (Yale University, Molecular Biophysics and Biochemistry); Michael Snyder (Yale University, Molecular, Cellular, and Developmental Biology); Mark Gerstein (Yale University, Computational Biology & Bioinformatics, Molecular Biophysics & Biochemistry, Computer Science); |
| Short Abstract: Straightforward integration, as currently done in genomics, does not provide enough flexibilitywhen datasets can no longer be indexed on a single class of variable. We developed a formalism to identify “cross patterns” between differently indexed metadata and applied this concept to reveal novel and non-obvious connections in chemogenomics data. |
| Long Abstract: Click Here |
| Poster X075 |
| Metabolite and reaction inference based on enzyme specificities |
| Dick de Ridder- Delft University Of Technology |
| Marco J.L. de Groot (Delft University of Technology, Bioinformatics Lab, Faculty Of Electrical Engineering, Mathematics And Computer Science); Rogier J.P. van Berlo (Delft University of Technology, Bioinformatics Lab, Faculty Of Electrical Engineering, Mathematics And Computer Science); Wouter A. van Winden (Delft University of Technology, Bioprocess Technology Group, Dept. of Biotechnology); Peter J.T. Verheijen (Delft University of Technology, Bioprocess Technology Group, Dept. of Biotechnology); Sef J. Heijnen (Delft University of Technology, Bioprocess Technology Group, Dept. of Biotechnology); Marcel J.T. Reinders (Delft University of Technology, Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science); |
| Short Abstract: Many enzymes are aspecific: they can catalyze transformations of more compounds than the traditional ones listed in e.g. KEGG. We model this aspecificity by predicting whether a certain input substrate is likely to be transformed by an enzyme. To train this predictor, we use the BRENDA enzyme activity database. |
| Long Abstract: Click Here |
| Poster X076 |
| Integrated Weighted Gene Co-expression Module Analyses with an Application to Sheep Gastrointestinal Nematode Infection |
| Haja Kadarmideen- Commonwealth Scientific and Industrial Research Organisation (CSIRO) |
| Nick Andronicos (Commonwealth Scientific and Industrial Research Organisation (CSIRO), Livestock Industries); Nathan Watson-Haigh (Commonwealth Scientific and Industrial Research Organisation (CSIRO), Livestock Industries); |
| Short Abstract: Microarray gene expression data, from sheep gastrointestinal nematode infection experiments, were used to detect/annotate differentially expressed genes across parasites, tissues and length of infection. We constructed four weighted gene co-expression networks and detected several important gene modules. Biologically relevant candidate genes/biomarkers were then identified using systems biology approach. |
| Long Abstract: Click Here |
| Poster X077 |
| Learning gene regulatory networks from gene expression measurements using non-parametric molecular kinetics |
| Tarmo Äijö- Tampere University of Technology |
| Harri Lähdesmäki (Tampere University of Technology, Department of Signal Processing); |
| Short Abstract: We propose a novel method for modeling transcriptional level regulation which is built on the use of Bayesian analysis with ordinary differential equations and nonparametric Gaussian process modeling. Evaluation of the proposed structure and dynamics inference method using a recently published in vivo data set demonstrates improved performance. |
| Long Abstract: Click Here |
| Poster X078 |
| Logical Modeling of Gene Regulatory Networks |
| Guy Karlebach- Tel-Aviv University |
| Ron Shamir (Tel-Aviv University, The Blavatnik school of computer science); |
| Short Abstract: Understanding gene regulatory networks is a challenge. We present an algorithm that determines the smallest perturbation sets for manipulating the dynamics of a network and implement it using Petri nets. By modifying McMillan’s unfolding algorithm, we handle partial knowledge and reduce computation cost. The methodology is demonstrated on a glioma network |
| Long Abstract: Click Here |
| Poster X079 |
| Scoring disease relevance of proteins through network topology mediated information dissemination |
| Emre Guney- Pompeu Fabra University |
| Oriol Fornes (Pompeu Fabra University, Health and Experimental Sciences); Baldo Oliva (Pompeu Fabra University, Health and Experimental Sciences); |
| Short Abstract: Based on the intuition that crucial proteins involved in a specific biological pathway might be identified by inspecting their kinship with other proteins in an interaction network, we present NetZcore, a novel algorithm to score pathway relevance of proteins involved in a particular pathology. |
| Long Abstract: Click Here |
| Poster X080 |
| Refinement of Calvin cycle models with allosteric regulations inferred from metabolomic data |
| Zoran Nikoloski- University of Potsdam |
| Sergio Grimbs (University of Potsdam, Institute of Biochemistry and Biology); Joachim Selbig (Max-Planck Institute of Molecular Plant Physiology, Bioinformatics); |
| Short Abstract: A first step towards practical solutions for increasing photosynthesis is developing a precise model of the Calvin cycle that includes different regulatory mechanisms. We propose an approach for determining putative allosteric regulations, based on a hierarchy of higher-order partial correlation matrices and apply it to Arabidopsis metabolomic high-throughput data. |
| Long Abstract: Click Here |
| Poster X081 |
| Functional characterisation of Mediator subcomplexes: Application of Nested Effects Models in a genetical genomics approach |
| Theresa Niederberger- Ludwig-Maximilians-University Munich |
| Dietmar Martin (Ludwig-Maximilians-University Munich, Gene Center); Michael Lidschreiber (Ludwig-Maximilians-University Munich, Gene Center); Achim Tresch (Ludwig-Maximilians-University Munich, Gene Center); |
| Short Abstract: The Mediator multiprotein complex is a transcriptional coregulator that acts via physical interactions with transcription factors. Several genome-wide gene expression data sets of yeast knockout strains are analysed with Nested Effects Models in order to predict these interactions. This combines classical epistasis analysis with network reconstruction approaches. |
| Long Abstract: Click Here |
| Poster X082 |
| Prioritizing functional modules mediating genetic perturbations and their phenotypic effects: a global strategy |
| Li Wang- University of Southern California |
| Ting Chen (University of Southern California, Molecular and Computational Biology); Fengzhu Sun (University of Southern California, Molecular and Computational Biology); |
| Short Abstract: We have developed a global strategy based on the Bayesian network framework to prioritize the functional modules mediating genetic perturbations and their phenotypic effects among a set of overlapping candidate modules. We take lethality in S. cerevisiae and human cancer as two examples to show effectiveness of this approach. |
| Long Abstract: Click Here |
| Poster X083 |
| Inferring Cancer-associated Signaling Networks Based on Significance Analysis of microRNA-mRNA Targeting |
| Xiaobo Zhou- The Methodist Hospital Research Institute |
| Di Huang (The Methodist Hospital Research Institute, Radiology); Stephen T. C. Wong (The Methodist Hospital Research Institute, Radiology); |
| Short Abstract: To infer signal networks, we develop a method in which mRNA expression data and microRNA information are integrated. By this mean, two major factors impacting gene expression, mRNA abundance and microRNA effect, are considered. To evaluate the effect of microRNA, we explore the expression data as well as sequence data. |
| Long Abstract: Click Here |
| Poster X084 |
| Integrative analysis of complex disease network underlying epistatic loci cross multiple tissues |
| Zhidong Tu- Rosetta/Merck |
| Chunsheng Zhang (Rosetta/Merck, Informatics); I-Ming Wang (Rosetta/Merck, Genetics); Hongyue Dai (Rosetta/Merck, Informatics); Pek Lum (Rosetta/Merck, Genetics); Mark Keller (UW-Madison, Genetics); Alan Attie (UW-Madison, Genetics); Jun Zhu (Rosetta/Merck, Genetics); Eric Schadt (Rosetta/Merck, Genetics); |
| Short Abstract: By constructing an F2 mouse cross and performing molecular profiling, we demonstrate how multiple genetic factors interact with each other to cause the underlying molecular network perturbation in a tissue specific manner. A network based prioritization approach identified candidate genes whose perturbations lead to changes in particular phenotypes as predicted. |
| Long Abstract: Click Here |
| Poster X085 |
| Dynamic modeling of FGF-2 signaling pathway in human embryonic stem cells |
| Geoffrey Koh- Bioprocessing Technology Institute, Agency for Science and Technology Research |
| Dong-Yup Lee (Bioprocessing Technology Institute, Agency for Science and Technology Research, Bioinformatics); Vanessa Ding (Bioprocessing Technology Institute, Agency for Science and Technology Research, Stem Cell); Andre Choo (Bioprocessing Technology Institute, Agency for Science and Technology Research, Stem Cell); |
| Short Abstract: We present a mathematical model of the FGF-2 signaling pathway in human embryonic stem cells. Our study focuses on the activity of the four members in the FGF receptor family. Through combinatorial knockdown simulations, we show that receptors FGFR1 and FGFR4 are crucial for activating the downstream ERK1/2 signaling pathway. |
| Long Abstract: Click Here |
| Poster X086 |
| Visualizing properties of protein interaction networks in functional space. |
| John Pinney- Imperial College London |
| William Kelly (Imperial College London, Centre for Bioinformatics); |
| Short Abstract: Using GLASS (Gene Layout by Semantic Similarity), a recently developed methodology for the visualization of genome-scale data, we demonstrate the striking differences between network data sets in terms of their biases towards different cellular components, and the knock-on effects of these biases for derived network statistics. |
| Long Abstract: Click Here |
| Poster X087 |
| Exploration of Arabidopsis regulome using data integration and network analysis approaches |
| Artem Lysenko- Rothamsted Research |
| Chris Rawlings (Rothamsted Research, Centre for Mathematical and Computational Biology); Charlie Hodgman (University of Nottingham, Multidisciplinary Centre for Integrative Biology); Tony Miller (Rothamsted Research, Plant Pathology and Microbiology ); |
| Short Abstract: We have constructed a network of predicted and experimentally proven protein-protein interactions, gene regulatory relationships and gene coexpression. This integrated network was analysed to identify modular structures and linked to the metabolic pathways and Gene Ontology. Centrality and betweenness analyses were then used to identify important regulatory modules. |
| Long Abstract: Click Here |
| Poster X088 |
| An automated approach for identification of parameter relations resulting in a switch-like behavior of pathway activation |
| Yvonne Koch- German Cancer Research Center |
| Hannah Schmidt-Glenewinkel (German Cancer Research Center, Theoretical Bioinformatics); Roland Eils (German Cancer Research Center, Theoretical Bioinformatics); Benedikt Brors (German Cancer Research Center, Theoretical Bioinformatics); |
| Short Abstract: An automated approach for scanning parameter space for models of differential equations combined with a decision tree algorithm was developed to find component relations responsible for pathway activation. Applied to EGF receptor internalization the method shows to be a useful tool in identifying parameter relations evoking a switch-like pathway response. |
| Long Abstract: Click Here |
| Poster X089 |
| A SREBP Centered Transcriptional Networks Controlling Lung Lipids And Surfactant Homeostasis |
| Yan Xu- Cincinnati Children's Hospital Medical Center |
| Minlu Zhang (University of Cincinnati, Computer Science); Yanhua Wang (CCHMC, Pulmonary Biology); Vrushank Dave (CCHMC, Pulmonary Biology); Jason Lu (CCHMC, Biomedical Informatics); Jeffrey Whitsett (CCHMC, Pulmonary Biology); |
| Short Abstract: We integrated microarray data with array independent data to enable the elucidation of genetic networks regulating the lipids related biological processes in lung. Using this strategy, we identified the critical components in lung transcriptional network directing lipogenesis, lipid sensing or trafficking, controlling surfactant homeostasis in the mouse lung. |
| Long Abstract: Click Here |
| Poster X090 |
| BIANA: A Cytoscape Plugin for Compiling Biological Interactions and for Network Analysis |
| Javier Garcia- Research Unit on Biomedical Informatics of IMIM/UPF |
| Emre Güney (UPF, Structural Bioinformatics Lab); JOAN PLANAS-IGLESIAS (UPF, Structural Bioinformatics Lab (GRIB)); BALDO OLIVA (UPF, Structural Bioinformatics Lab); RAMON ARAGUES (UPF, Structural Bioinformatics Lab); |
| Short Abstract: BIANA, a Python framework that can be used as a Cytoscape Plugin, is a tool for biological information integration and network management. It achieves the goal of integrating, managing and inferring latent biomolecular relationships from multiple sources of biological information. |
| Long Abstract: Click Here |
| Poster X091 |
| Predicting interacting motifs from protein-protein interaction networks |
| Jaume Bonet- GRIG-IMIM/UPF |
| Baldo Oliva (GRIB-IMIM/UPF, SBI); Ramon Aragues (GRIB-IMIM/UPF, SBI); Pascal Braun (DFCI-Harvard, CCSB); Marc Vidal (DFCI-Harvard, CCSB); |
| Short Abstract: Here we present a method to identify protein-protein interacting regions by using only sequence and topological information of the protein-protein interaction network (ppin). The method is based on the concept that proteins sharing common interactors might perform those same interactions through the same region. |
| Long Abstract: Click Here |
| Poster X092 |
| Novel Approach for Reconstructing the Metabolic Network |
| David Alarcon- GRIB |
| No additional authors |
| Short Abstract: We propose a novel method for reconstructing the metabolic network that avoids arbitrarily removing frequent chemical compounds (water, ATP) to prevent spureous relationships between enzymes. Our approach does not assume any a priori topoloy for the network. The method is focussed on accurately predicting enzyme relationships driven by these compounds. |
| Long Abstract: Click Here |
| Poster X093 |
| Dynamic modeling of E. coli central carbon metabolism combining different kinetic rate laws |
| Rafael Costa- University of Minho |
| Daniel Machado (University of Minho, Centre of Biological Engineering); Isabel Rocha (University of Minho, Centre of Biological Engineering); Eugenio Ferreira (University of Minho, Centre of Biological Engineering); |
| Short Abstract: In this work, we analyze four alternative hybrid modeling strategies to the reference large scale mechanistic E. coli central carbon metabolic network model based on mechanistic Michaelis-Menten equation for the bimolecular reactions and the other reactions with different formats of approximative rate kinetics (Generalized Mass-Action, convenience equation, Lin-Log and Power-Law). |
| Long Abstract: Click Here |
| Poster X095 |
| Multi-criterion approaches for the in silico optimization of mutant microorganisms |
| Isabel Rocha- University of Minho |
| Paulo Maia (University of Minho, IBB - Institute for Biotechnology and Bioengineering); Eugenio Ferreira (University of Minho, IBB - Institute for Biotechnology and Bioengineering); Miguel Rocha (University of Minho, CCTC); |
| Short Abstract: In Metabolic Engineering, Evolutionary Computation (EC) techniques to find optimal mutants (sets of gene knockouts) for the production of valuable compounds have been recently presented with good results. In this work, we view the problem as a multi-criterion optimization task, proposing adequate EC techniques, validated with some real world case-studies. |
| Long Abstract: Click Here |
| Poster X096 |
| The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles |
| Dirk Walther- MPI Molecular Plant Physiology |
| No additional authors |
| Short Abstract: We investigated the relationships between metabolic pathways and protein interaction networks. Our results reveal topological equivalences between the protein interaction network and the metabolic pathway network. Evolved protein interactions may contribute significantly towards increasing the efficiency of metabolic processes by permitting higher metabolic fluxes. |
| Long Abstract: Click Here |
| Poster X097 |
| Inferring cluster-based networks from differently stimulated multiple time-course gene expression data |
| Yuichi Shiraishi- RIKEN Advanced Science Institute |
| Shuhei Kimura (Tottori University, Department of Information and Knowledge Engineering); Mariko Hatakeyama (RIKEN Advanced Science Institute , Advanced Computational Sciences Department); |
| Short Abstract: In this paper,we propose a new statistical method based on state space models for estimating cluster-based gene networks.First, our model can treat several temporal profiles stimulated via different ligands.Second, our model performs clustering and estimation of relationships between clusters and outside stimuli via a unified criterion. |
| Long Abstract: Click Here |
| Poster X098 |
| Data integration for systems biology - The Ondex SABR Project |
| Chris Rawlings- The Ondex SABR Consortium |
| No additional authors |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster X099 |
| Investitating the Mechanisms of Transcriptional Timing in S. cerevisiae |
| Nathan Lewis- University of California, San Diego |
| Bernhard Palsson (University of California, San Diego, Bioengineering); Eran Segal (Weizmann Institute of Science, Department of Computer Science And Applied Mathematics); |
| Short Abstract: Various timing motifs for gene expression in linear metabolic pathways have been witnessed in yeast. Here various methods are applied to identify the mechanisms which contribute to transcriptional timing motifs in metabolic networks. |
| Long Abstract: Click Here |
| Poster X100 |
| Prediction of cardiac transcription networks based on molecular data and complex clinical phenotypes |
| Markus Schueler- Max Planck Institute for Molecular Genetics |
| Martje Tönjes (Max Planck Institute for Molecular Genetics, Vertebrate Genomics); Stefanie Hammer (Max Planck Institute for Molecular Genetics, Vertebrate Genomics); Utz J. Pape (Max Planck Institute for Molecular Genetics, Computational Molecular Biology); Felix Berger (Department of Pediatric Cardiology, German Heart Center); Martin Vingron (Max Planck Institute for Molecular Genetics, Computational Molecular Biology); Silke Sperling (Max Planck Institute for Molecular Genetics, Vertebrate Genomics); |
| Short Abstract: We analyzed transcription levels in biopsies derived from hearts of 190 patients. After defining informative meta-phenotypes from a detailed phenotype ontology we could identify specific disease associated transcription profiles by applying linear models. We predicted regulatory networks for genes showing highly correlated expression patterns using ChIP-optimized TFBS predictions. |
| Long Abstract: Click Here |
| Poster X101 |
| Leveraging the context-specific coordination of transcript and metabolite concentrations to discover gene-metabolite interactions. |
| Patrick Bradley- Princeton University |
| Matthew Brauer (Princeton University, Molecular Biology); Joshua Rabinowitz (Princeton University, Chemistry); Olga Troyanskaya (Princeton University, Computer Science); |
| Short Abstract: Understanding the mutual regulation between metabolites and gene products could benefit areas as diverse as medicine and bioengineering. We measure metabolite and transcript concentrations in yeast, and provide new quantitative evidence that these concentrations are coordinated. We then develop a Bayesian approach that effectively finds gene-metabolite functional relationships from this experimental data. |
| Long Abstract: Click Here |
| Poster Y01 |
| Interaction Networks for Proteins Coded by Alternatively Spliced Human Genes |
| Bahar Taneri- Eastern Mediterranean University |
| Senay Kafkas (Eastern Mediterranean University, Computer Engineering); Ekrem Varoglu (Eastern Mediterranean University, Computer Engineering); |
| Short Abstract: A key process affecting interactomes is alternative splicing. We introduce a new approach for investigating how alternative splicing shapes the human interactome, by building an interaction network for proteins coded by alternatively spliced genes. Using text mining and machine learning techniques, we analyze 16,826 genes and obtain 88,345 interacting pairs. |
| Long Abstract: Click Here |
| Poster Y02 |
| Identifying Associated Genes Specific to a Particular Disease Using Biomedical Literatures |
| Yeondae Kwon- National Institute of Genetics |
| Hideaki Sugawara (National Institute of Genetics, Center for Information Biology and DNA Data Bank of Japan); |
| Short Abstract: In this paper, we propose an algorithm that extracts a group of associated genes with a given disease from literatures and prioritizes them in terms of their specificity to the disease. This enables the identification of associated genes that do not have side-effects, which contributes to efficient drug developments. |
| Long Abstract: Click Here |
| Poster Y03 |
| Towards Semantic Network of Bioinformatics Resources |
| Goran Nenadic- University of Manchester |
| Hammad Afzal (University of Manchester, School of Computer Science); Robert Stevens (University of Manchester, School of Computer Science); |
| Short Abstract: Bioinformatics has witnessed a huge number of tools, services and resources, but many of them are not accessible as their names and functionalities are unknown. We present a resource discovery approach based on bioinformatics literature. Almost 10,000 candidate resources were identified, terminologically profiled and organised in a searchable semantic network. |
| Long Abstract: Click Here |
| Poster Y04 |
| Victoria: navigating to a new style of searching for web-services and workflows |
| Johan Karlsson- Malaga University |
| Javier Ríos (Malaga University, Department of Computer Architecture); Oswaldo Trelles (Malaga University, Department of Computer Architecture); |
| Short Abstract: The number of web-services in bioinformatics is rapidly increasing. However, lack of effective discovery tools for said applications is a barrier to wiring different services together as workflows. Victoria is a versatile Java library for dynamic service discovery and automatic service composition using public service metadata repositories. |
| Long Abstract: Click Here |
| Poster Y05 |
| Text-mining of PubMed abstracts by natural language processing to create a free database on molecular mechanisms of bacterial pathogens – a year of use, feedback and development. |
| David Pot- SRA International |
| Sam Zaremba (SRA International, Health & Civil Services); Mila Ramos-Santacruz (SRA International, Health & Civil Services); Panna Shetty (SRA International, Health & Civil Services); Sri Iyer (SRA International, Health & Civil Services); Joel Fedorko (SRA International, Health & Civil Services); Jon Whitmore (SRA International, Health & Civil Services); Matthew Shaker (SRA International, Health & Civil Services); Nicole Perna (University of Wisconsin - Madison, Genome Center); Jeremy Glasner (University of Wisconsin - Madison, Genome Center); Guy Plunkett III (University of Wisconsin - Madison, Laboratory of Genetics); John Greene (SRA International, Health & Civil Services); |
| Short Abstract: The Enteropathogen Resource Integration Center (ERIC) text mining application has been released for a year+. The system extracts Gene - Roles; Mutation - Phenotypes; and Organism – Pathogenesis relationships from PubMed abstracts. We report progress of the system in the past year based on feedback from the user community. |
| Long Abstract: Click Here |
| Poster Y06 |
| PubMedScan: an automatic paper recommendation system for newly published PubMed articles |
| Katsuhiko Murakami- Japan Biological Informatics Consortium |
| Fusano Todokoro (National Institute of Advanced Industrial Science and Technology, Biomedicinal Information Research Center); Yoshiharu Sato (National Institute of Advanced Industrial Science and Technology, Biomedicinal Information Research Center); Takashi Gojobori (National Institute of Advanced Industrial Science and Technology, Biomedicinal Information Research Center); Tadashi Imanishi (National Institute of Advanced Industrial Science and Technology, Biomedicinal Information Research Center); |
| Short Abstract: We introduce a paper-recommendation system in which a user specifies the search condition by multiple papers of the users’ interest. As recent improvements, we launched a new web sever of PubMedScan for anonymous users, and developed software to obtain PMIDs from PDF files of papers to input the users’ interest. |
| Long Abstract: Click Here |
| Poster Y07 |
| CALBC – Collaborative Annotation of a Large Biomedical Corpus |
| Dietrich Rebholz-Schuhmann- European Bioinformatics Institute |
| Antonio Jimeno Yepes (European Bioinformatics Institute, Research Department); Erik van Mulligen (Erasmus Medical Center, Medical Informatics); Olivier Bodenreider (National Library of Medicine, Cognitive Science); David Milward (Linguamatics, Development); Udo Hahn (Friedrich Schiller Universitaet, Julie Laboratory); |
| Short Abstract: CALBC aims at creating a large annotated corpus (on the order of 150,000 documents) with about 5 to 10 different semantic types (genes, diseases) whose annotation is carried out automatically. The named entity annotations from the collaborators are fully integrated into a single corpus for future public annotation challenges. |
| Long Abstract: Click Here |
| Poster Y08 |
| Whatizit-IeXML: Suite of Web services for biomedical information extraction |
| Dietrich Rebholz-Schuhmann- European Bioinformatics Institute |
| Antonio Jimeno Yepes (European Bioinformatics Institute, Research Department); Anika Oellrich (European Bioinformatics Institute, Research Department); |
| Short Abstract: Whatizit is a SOAP Web service infrastructure at the EBI to extract different semantic types from scientific literature: genes, proteins, diseases and composite solutions. Recently, methods for MeSH terms and chemical entities have been added. Whatizit-IeXML delivers the same results in the standardized IeXML format. |
| Long Abstract: Click Here |
| Poster Y09 |
| Recognition of Synechocystis gene names in full papers |
| Hong-Woo Chun- Database Center for Life Science, Research Organization of Information and System, Japan |
| Shinobu Okamoto (Research Organization of Information and System, Database Center for Life Science); Yasunori Yamamoto (Research Organization of Information and System, Database Center for Life Science); Atsuko Yamaguchi (Research Organization of Information and System, Database Center for Life Science); Toshihisa Takagi (Research Organization of Information and System, Database Center for Life Science); |
| Short Abstract: The proposed approach aims to recognize Synechocystis gene names using features from not only the sentence but also the full paper. A rule-based and a dictionary-based candidate detection, and a machine learning-based classification were conducted. Experiments demonstrated that features from full papers have important roles in improving the performance. |
| Long Abstract: Click Here |
| Poster Y10 |
| Selecting an Ontology for Biomedical Text Mining |
| He Tan- Linköpings universitet |
| Patrick Lambrix (Linköpings universitet, Institutionen för datavete); |
| Short Abstract: Biomedical ontologies provide the domain knowledge required by text mining applications in the area. In this poster we propose a framework for selecting an appropriate ontology for a particular text mining application, and present an experiment based on the framework choosing an ontology for a gene normalization system. |
| Long Abstract: Click Here |
| Poster Z01 |
| Estimating genomic diversity of the cleavage site peptides among H5HA avian influenza ameliorates the synthesis of influenza vaccine |
| Sherry Dadgar- Rochester Institute of Technology |
| Sherry Dadgar (Rochester Institute of Technology, Bioinformatics); Michael Osier (Rochester Institute of Technology, Bioinformatics); Carol Marchetti (Rochester Institute of Technology, Statistics and Mathematics); Gary R. Skuse (Rochester Institute of Technology, Bioinformatics); |
| Short Abstract: We employed, in silico analysis of hemagglutinin to predict cleavage sites of strains employing SigCleave and SignalP 3.0. Then we employed information theory methods, mutual information and Pearson Chi-squared tests to identify possible phenotypic and genotypic characteristics between pathogenic and low/non-pathogenic HAH5 cleavage site in USA and improve vaccine development. |
| Long Abstract: Click Here |
| Poster Z02 |
| Bioinformatics: Caribbean Prospects In The Face of Emerging Technology |
| Alana Abdool- The University of Manchester, England |
| No additional authors |
| Short Abstract: The Caribbean has seen significant advancements in the use of biological technology. Both industry and academia utilize bioinformatics tools. The field of bioinformatics, although it has evolved into a full-fledged discipline over the last decade, has yet to have anything more than an ad-hoc treatment from its Caribbean users. |
| Long Abstract: Click Here |
| Poster Z03 |
| BioCatalogue: A Curated Web Service Registry for Life Science Community |
| Franck Tanoh- University of Manchester |
| Khalid Belhajjame (University of Manchester, School of computer science); Carole Goble (University of Manchester , School of Computer science); Jiten Bhagat (University of Manchester , School of Computer science); Katy Wolstencroft (University of Mancheste, School of Computer science); Robert Stevens (University of Manchester, School of Computer science); Rodrigo Lopez (EMBL European Bioinformatics Institute, EBI); Eric Nzuobontane (EMBL European Bioinformatics Institute, EBI); Thomas Laurent (EMBL European Bioinformatics Institute, EBI); Steve Pettifer (University of Manchester, School of Computer science); |
| Short Abstract: BioCatalogue provides a central registry of curated biological Web Services. A place where providers, users and curators can register, annotate and search for Web Services. BioCatalogue is a place where the community can meet the maintainers of these services. It is co-developed by the University of Manchester and the EMBL-EBI. |
| Long Abstract: Click Here |
| Poster Z04 |
| Real-Time Volume Ray Tracing For Bioinformatics Applications |
| Lukas Marsalek- Saarland University |
| Anna Dehof (Saarland University, Chair for Bioinformatics); Philipp Slusallek (DFKI Saarbruecken & Saarland University, Agents and Simulated Reality); Andreas Hildebrandt (Saarland University, Center for Bioinformatics); |
| Short Abstract: An important data source in structural bioinformatics are scalar three-dimensional data sets. The method of choice for visualizing such data sets is volume ray tracing, a technique traditionally associated with high computational demands. In this work, we present an interactive real-time volume ray tracer for use in the bioinformatics field. |
| Long Abstract: Click Here |
| Poster Z05 |
| Using Exon Microarrays to Predict Breast Cancer Occurrence |
| William Johnson- Brigham Young University |
| Ying Sun (University of Utah, Genetics); Andrea Bild (University of Utah, Genetcs); |
| Short Abstract: We present a complete and powerful method for analyzing Affymetrix exon arrays. We apply a novel normalization method that substantially increases the signal-to-noise ratio in the data. Also we employ a Bayesian Hierarchical model for the identification of differentially expressed genes and spliced exons. |
| Long Abstract: Click Here |
| Poster Z06 |
| The evolution of the repertoire of domain architectures in genomes |
| Julian Gough- University Of Bristol |
| Cyrus Chothia (MRC Laboratory of Molecular Biology, Structural Studies); |
| Short Abstract: Nature has achieved very little innovation since LUCA by creating new domains, has exploited duplication and divergence of existing domains to some degree, but the main way in which organisms adapt and evolve at the protein level is by recombination of domains in its existing repertoire to produce novel architectures. |
| Long Abstract: Click Here |
| Poster Z08 |
| A model structure of the human potassium channel Kv7.2 in complex with a potent selective opener |
| Yana Gofman- Tel-Aviv University |
| Asher Peretz (Tel-Aviv University, Department of Physiology & Pharmacology); Liat Pell (Tel-Aviv University, Department of Physiology & Pharmacology); Yoni Haitin (Tel-Aviv University, Department of Physiology & Pharmacology); Bernard Attali (Tel-Aviv University, Department of Physiology & Pharmacology); Nir Ben Tal (Tel-Aviv University, Biochemistry); |
| Short Abstract: We generated a model-structure of the Kv7.2 human voltage-gated potassium channel in complex with NH29, a compound stabilizing the open state. This potent and selective opener binds to the voltage sensing domain in the interface formed between three helices. The model guided the design of mutagenesis experiments. |
| Long Abstract: Click Here |
| Poster Z09 |
| A method for validation for clustering of phenotypic gene knockdown profiles using protein-protein interactions information |
| Nikolay Samusik- MPI-CBG |
| Yannis Kalaidzidis (MPI-CBG, -); Marino Zerial (MPI-CBG, -); |
| Short Abstract: We propose a method for cross-validation of the clustering of phenotypic siRNA screening data using protein-protein interaction (PPI) information. We established a measure of cluster quality with respect to PPI and showed that this measure allows discriminating between optimal and suboptimal segmentation and can be used to select clustering parameters. |
| Long Abstract: Click Here |
| Poster Z10 |
| The Bioinformatics Resource Manager & Gaggle: a platform for management, integration and analysis of systems biology data |
| Mudita Singhal- PNNL |
| Anuj Shah (PNNL, Scientific Data Management); Tara Gibson (PNNL, Scientific Data Management); Ian Gorton (PNNL, Applied Computer Science); Benson Kalahar (PNNL, Global Security Tech & Policy); Katrina Waters (PNNL, Computational Biol & Bioinfor); Dan Tenenbaum (ISB, Baliga Group); Christopher Bare (ISB, Baliga Group); Nitin Baliga (ISB, Baliga Group); |
| Short Abstract: This poster demonstrates the capabilities of the Bioinformatics Resource Manager (BRM, a general purpose data management and integration software that provides the user with data storage, annotation, and merging capabilities and utilizes the Gaggle communication model to broadcast data to the integrated application tools, such as Cytoscape and the Multi-Experiment Viewer. |
| Long Abstract: Click Here |
| Poster Z12 |
| fRMSDPred: A pairwise local structure similarity measure from sequence |
| Huzefa Rangwala- George Mason University |
| Huzefa Rangwala (George Mason University, Computer Science); George Karypis (University of Minnnesota, Computer Science); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster Z13 |
| Polymorphism at the apical membrane antigen 1 locus reflects the world population history of Plasmodium vivax |
| Priscila Grynberg- Federal University of Minas Gerais |
| No additional authors |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster Z14 |
| Fast database search for flexible similar structures using TOPS++FATCAT method |
| Mallika Veeramalai- Burnham Institute for Medical Research |
| Yuzhen Ye (Indiana University, School of Informatics); Adam Godzik (Burnham Institute for Medical Research, Joint Center for Molecular Modelling); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster Z15 |
| Computational Methods for Dissection of MicroRNA Function |
| Igor Ulitsky- Tel Aviv University |
| Louise Laurent (The Scripps Research Institute, Center for Regenerative Medicine); Franz-Josef Müller (The Scripps Research Institute, Center for Regenerative Medicine); Jeanne F. Loring (The Scripps Research Institute, Center for Regenerative Medicine); Ron Shamir (Tel Aviv University, Blavatnik School of Computer Science); |
| Short Abstract: We present two methods for improving discovery of miRNA function and their targets. The first detects enrichment of miRNA targets in sets of co-annotated or co-expressed genes. The second detects groups of miRNAs that jointly target a cellular pathway, utilizing information on protein interactions, putative miRNA targets and miRNA expression. |
| Long Abstract: Click Here |
| Poster Z16 |
| Engineering Bioinformatics automated analysis pipelines to run on Open Science Grid(OSG) Infrastructure |
| Abhishek Pratap- Institute for Genome Sciences |
| Abhishek Pratap (Institute for Genome Sciences/Institute for Systems Biology, GRC); Mats Rynge (The Renaissance Computing Institute, OSG); Eric Deutsch (Institute for Systems Biology, Aebersold Group); |
| Short Abstract: A generic methodology to engineer bioinformatics based analysis pipeline on Open Science Grid. The aim is to provide one button Grid access to end user to run data analysis from their local desktop. It gives a scale up both in the data processing capacity and efficiency of the pipeline. |
| Long Abstract: Click Here |
| Poster Z17 |
| The Prediction of Protein-Protein Interaction Networks in Rice Blast Fungus |
| FEI HE- CHINA AGRICULTRUAL UNIVERSITY |
| YAN ZHANG (China Agricultural University, State Key Laboratory for ArgoBiotechnology); YONG-ZI CHEN (China Agricultural University, State Key Laboratory for ArgoBiotechnology); ZIDING ZHANG (China Agricultural University, State Key Laboratory for ArgoBiotechnology); YOU-LIANG PENG (China Agricultural University, State Key Laboratory for ArgoBiotechnology); |
| Short Abstract: Large-scale PPI mapping projects have not been implemented for Magnaporthe grisea, which causes the most severe rice disease. We have predicted protein interaction network of the pathogen. This will provide new insights into the functional genomics of this fungus. |
| Long Abstract: Click Here |
| Poster Z18 |
| Bad habits about homology die hard. |
| Angelo Facchiano- Institute of Food Science, CNR |
| Anna Marabotti (Institute of Food Science, CNR, Lab. of Bioinformatics and Computational Biology); |
| Short Abstract: Despite decades of discussion, the term “homology†is still wrongly used instead of “similarityâ€.We made a survey in literature about this bad habit and we present our results to stimulatediscussion and to make conscious as much people as possible of the use and misuse of this term. |
| Long Abstract: Click Here |
| Poster Z19 |
| Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project |
| Chris Taylor- EMBL-EBI |
| Susanna-Assunta Sansone (EMBL-EBI, Microarray Group); Philippe Rocca-Serra (EMBL-EBI, Microarray Group); Dawn Field (Oxford Centre for Ecology and Hydrology, Molecular Evolution and Bioinformatics Group); |
| Short Abstract: Minimum information (MI) checklists specify the content to provide when reporting research; ontology-aware tools such as 'ISAcreator' (http://isatab.sourceforge.net/isacreator.html) help researchers create semantically rich checklist-compliant reports. MIBBI provides access to MI checklists, their developers and appropriate tools, and is driving the development of a new, modular, fully integrated checklist suite (http://mibbi.org/). |
| Long Abstract: Click Here |
| Poster Z20 |
| Imprints of evolution on protein structures |
| Sanne Abeln- University of Oxford |
| Charlotte Deane (University of Oxford, Department of Statistics); |
| Short Abstract: A protein superfamily may be traced back in evolution to determine its lineage specificity. Here we show that there are significant structural differences between superfamilies that are lineage specific, and those that occur across all species. The differences suggest that protein structures of surviving superfamilies are more stable. |
| Long Abstract: Click Here |
| Poster Z21 |
| In Silico analysis of Y chromosome proteins of Homo sapiens |
| Chinmay Dwibedi- VIT UNIVERSITY |
| Karthikeyan p.p (Guest lecturer, Bioinformatics); Rao Sethumadhavan (Senior Proffessor, Bioinformatics); P.T.V. Lakshmi (Lecturer, Bioinformatics); |
| Short Abstract: The present study involves the analysis of 107 proteins of Y chromosome of human beings and to compute the physico-chemical properties; to predict the 2D, 3D structural information with validation and to predict the functions for the same.The structures were obtained by template based homology modelling and Ab Initio modelling |
| Long Abstract: Click Here |
| Poster Z22 |
| Serum Paraoxonase's Structure and Its Interaction with VX |
| Matthew Peterson- The MITRE Corporation |
| Steven Fairchild (The MITRE Corporation, Emerging Technologies Office); Wenling Chang (The MITRE Corporation, Emerging Technologies Office); Chang-Guo Zhan (University of Kentucky College of Pharmacy, Department of Pharmaceutical Science); Adel Hamza (University of Kentucky College of Pharmacy, Depertment of Pharmaceutical Science); Douglas Cerasoli (US Army Medical Research Institute of Chemical Defense, Physiology and Immunology Branch); |
| Short Abstract: Human serum paraoxonase (HuPON1) is a potential bioscavenger for organophosphorus nerve agents such as VX. HuPON1's 3D structure and interaction mechanism with VX are unknown. This study computationally characterized HuPON1's 3D structure, and its binding mechanism for VX. Key active site residues and associated functions were determined from the results. |
| Long Abstract: Click Here |
| Poster Z23 |
| UCSC CSC Potency Prediction Pipeline |
| Marcos Woehrmann- UC Santa Cruz |
| Scott Lokey (UC Santa Cruz, Chemistry); Josh Stuart (UC Santa Cruz, Biomolecular Engineering); Nadine Gassner (UC Santa Cruz, Chemical Screening Center); Walter Bray (UC Santa Cruz, Chemical Screening Center); |
| Short Abstract: The University of California - Santa Cruz Chemical Screening Center Potency Prediction Pipeline is a soft agar hit analysis system used to identify compounds that show activity in a variety of organisms. |
| Long Abstract: Click Here |
| Poster Z24 |
| PSEUDO-RANDOM OLIGOMER MICROARRAY-BASED BIOSENSOR |
| Mojdeh Mohtashemi- MITRE/MIT |
| David Walburger (MITRE, CS); Haley Smith (MITRE, CS); Felicia Sutton (MITRE, CS); James Diggans (MITRE, CS); |
| Short Abstract: Conventional microarray-based biosensors can detect a limited number of organisms. They require physical reengineering when a novel pathogen emerges. The current work seeks to design a microarray-based sensor using pseudo-random oligomer probes paired with mathematical models for recognition and classification of a broader array of organisms. Initial results are promising. |
| Long Abstract: Click Here |
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