| Accepted Posters |
| Category 'A'- Bioinformatics of Health and Disease' |
| 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 |
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