| Accepted Posters |
| Category 'B'- Bioinformatics of Health and Disease' |
| Poster B01 |
| A Systematic Strategy for Large-Scale Analysis of Genotype-Phenotype Correlations |
| Paul Fisher- University of Manchester |
| Cornelia Hedeler (University of Manchester, Computer Science); Katherine Wolstencroft (University of Manchester, Computer Science); Helen Hulme (University of Manchester, Computer Science); Robert Stevens (University of Manchester, Computer Science); Andrew Brass (University of Manchester, Computer Science); Harry Noyes (University of Liverpool, Life Sciences); Stephen Kemp (University of Liverpool, Life Sciences); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster B02 |
| Molecular Dynamics study of Human Bradykinin - Bradykinin B2 Receptor Interactions |
| Artur Gieldon- Johann Wolfgang Goethe-Universitat |
| Jakob Lopez (Johann Wolfgang Goethe-Universitat, Institute for Biophysical Chemistry, Center for Biomolecular Magnetic Resonance (BMRZ)); Clemens Glaubitz (Johann Wolfgang Goethe-Universitat, 2Institute for Biophysical Chemistry, Center for Biomolecular Magnetic Resonance (BMRZ)); Harald Schwalbe (Johann Wolfgang Goethe-Universitat, Institute for Organic Chemistry and Chemical Biology); |
| Short Abstract: In the presented study, molecular modeling (MM) and molecular dynamics (MD) techniques were used to analyze the interaction of bradykinin (BK) with the bradykinin B2 receptor (B2R). We applied computational methods to investigate the putative ligand - receptor interface and discuss implications to the active structure of the bradykinin B2 receptor. |
| Long Abstract: Click Here |
| Poster B03 |
| Improving sequence variant descriptions in mutation databases and literature using the Mutalyzer sequence variation nomenclature checker. |
| Peter Taschner- LUMC |
| Martin Wildeman (LUMC, Human Genetics); Ernest van Ophuizen (Wageningen University, Laboratory of Bioinformatics); Johan den Dunnen (LUMC, Human Genetics); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster B04 |
| Integration and use of Schistosoma mansoni genomic data for the discovery of candidate therapeutic targets |
| Adhemar Zerlotini- FIOCRUZ - IRR |
| Mark Heiges (UGA, Center for Tropical and Emerging Global Diseases); Haiming Wang (UGA, Center for Tropical and Emerging Global Diseases); Jessica Kissinger (UGA, Genetics); Guilherme Oliveira (FIOCRUZ, Instituto Rene Rachou); |
| Short Abstract: Schistosomiasis, a disease caused by parasitic organisms of the genus Schistosoma, is responsible for more than 200 million infections in developing countries. Computational tools and databases were used to predict the metabolome of one of the species, aiming to narrow the list of gene candidates suitable as drug targets. |
| Long Abstract: Click Here |
| Poster B05 |
| A quantitative genotype algorithm reflecting H5N1 Avian influenza niches |
| Xiu-Feng (Henry) Wan- Centers for Disease Control and Prevention |
| Guorong Chen (Digene, Digene); Feng Luo (Clemson University, School of Computing); Michael Emch (University of North Carolina, Department of Geography); Ruben Donis (Centers for Disease Control and Prevention, Influenza Division); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster B06 |
| SIMS – Making structure analysis easy |
| Tjaart de Beer- University of Pretoria |
| Tjaart de Beer (University of Pretoria, Biochemistry); Fourie Joubert (University of Pretoria, Biochemistry); |
| Short Abstract: SIMS (Structural Information Management System) provides an intuitive web-interface for structural data and analysis based on the MSD datamodel and includes the ability to store and analyse data and results from various online analysis methods in a central, secure environment. Application to Foot and Mouth Disease Virus is shown. |
| Long Abstract: Click Here |
| Poster B07 |
| Selecting Functionally Informative Tag SNPs for Disease Association Studies |
| Hagit Shatkay- Queen's University, School of Computing |
| No additional authors |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster B08 |
| GlycoBase and autoGU: tools for HPLC-based glycan analysis |
| Matthew Campbell- National Institute for Bioprocessing, Research and Training |
| Louise Royle (Ludger Ltd, Ludger Ltd); Catherine Radcliffe (Lonza, Lonza); Jodie Abrahams (National Institute for Bioprocessing, Research and Training, Glycobiology); Raymond Dwek (Glycobiology Institute, University of Oxford, Department of Biochemistry); Pauline Rudd (National Institute for Bioprocessing, Research and Training, Glycobiology); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster B09 |
| Integrative analysis of DNA copy number aberrations and gene expresssion changes in cancer |
| Hyunju Lee- Gwangju Institute of Science and Technology |
| Peter Park (Harvard-Partners Center for Genetics and Genomics, Medicine); Sek Won Kong (Children’s Hospital, Boston, MA,, Department of Cardiology,); |
| Short Abstract: None On File |
| Long Abstract: Click Here |
| Poster B10 |
| Solutions for database interoperability: a report from the CASIMIR consortium |
| Damian Smedley- European Informatics Institute |
| Morris Swertz (University of Groningen, Groningen Bioinformatics Centre); Katy Wolstencroft (University of Manchester, The School of Computer Science); Michael Zouberakis (BSRC Fleming, Institute of Immunology); Ewan Birney (European Bioinformatics Institute, PANDA nucleotides); Glenn Proctor (European Bioinformatics Institute, PANDA nucleotides); Paul Schofield (University of Cambridge, Department of Anatomy); |
| Short Abstract: The CASIMIR consortium is focused on coordination of mouse informatics resources. A major goal is to assess the use of distributed architectures to overcome the database interoperability problems that affects most experimental analysis. Here we demonstrate a solution to a common use case using BioMart, Web Services, MOLGENIS and Taverna. |
| Long Abstract: Click Here |
| Poster B11 |
| Protein networks and microarray data analysis for drug target prediction in latent Mycobacterium tuberculosis |
| Christian SOLIS CALERO- Universidad Nacional Mayor de San Marcos |
| No additional authors |
| Short Abstract: A set of Mycobacteriun tuberculosis proteins with computationally predicted relationship to latent state was generated using publicly available protein networks and gene expression data. After that, this set was analysed considering essentiality, selectivity and druggability criteria. Our approach identified 19 genes that may be considered as potential drug targets. |
| Long Abstract: Click Here |
| Poster B12 |
| PLACENTAL MALARIA IN DIFFERENT HLA ALLELES |
| Bundi Karau- The University of Nairobi |
| No additional authors |
| Short Abstract: We use online benchmarking tools to show allelic variation to placental malaria susceptibilty. The criteria used is protein sequences from NCBI eluted, then subjected to HLA filtering and benchmarking to show their immunogenicity, and potential for infecting humans. |
| Long Abstract: Click Here |
| Poster B13 |
| Towards Data Analysis of Genome Wide Influenza RNAi Screen |
| Klaus-Peter Pleissner- Max Planck Institute for Infection Biology |
| Alexander Karlas (Max Planck Institute for Infection Biology, Molecular Biology); Nikolaus Machuy (Max Planck Institute for Infection Biology, Molecular Biology); David Manntz (Max Planck Institute for Infection Biology, Molecular Biology); Marina Drabkina (Max Planck Institute for Infection Biology, Molecular Biology); Elke MĂĽller (Max Planck Institute for Infection Biology, Molecular Biology); Thomas F. Meyer (Max Planck Institute for Infection Biology, Molecular Biology); |
| Short Abstract: A genome wide RNA interference screen has been applied to identify host cell factors involved in influenza virus infection. The data analysis, mainly based on open-source R-packages “cellHTS” and “biomaRt” from Bioconductor.org, integrates a variety of steps to obtain scored phenotype list and to map relevant genes into biological context. |
| Long Abstract: Click Here |
| Poster B14 |
| A meta-analysis of high-throughput approaches elucidating the attenuation of Mycobacterium tuberculosis H37Ra |
| Roland Krause- MPI For Molecular Genetics |
| No additional authors |
| Short Abstract: The interest in the role of the histidine kinase response regulator PhoP in Mycobacteria has resulted in several independent high-throughput studies. Genome, transcriptome and metabolome of the Mycobacterium tuberculosis H37Ra strain can now be elucidated together and allow the comparison of the different high-throughput approaches. |
| Long Abstract: Click Here |
| Poster B15 |
| Life-giving caspases: revealing new roles in embryo pre-implantation development |
| Calixto Dominguez- Universidad Catolica de Chile |
| Dolores Busso (Pontificia Universidad CatĂłlica de Chile, Unit of Reproduction and Development ); Ricardo Moreno (Pontificia Universidad CatĂłlica de Chile, Unit of Reproduction and Development ); Tomas Perez-Acle (Pontificia Universidad CatĂłlica de Chile, Centre for Bioinformatics); |
| Short Abstract: Caspases are universally associated with cell death pathways. Recent studies indicate that caspase activation does not always lead to cell death and, instead, are important for cell differentiation and proliferation in many cell types. Hence, molecular and in silico data analysis have been combined to disclose its role in embryo. |
| Long Abstract: Click Here |
| Poster B16 |
| GOGrapher: A Python library for GO network graph analysis |
| Brian Muller- Medical University of South Carolina |
| Adam Richards (Medical University of South Carolina, Department of Biostatistics, Bioinformatics, and Epidemiology); Lam Tsoi (Medical University of South Carolina, Department of Biostatistics, Bioinformatics, and Epidemiology); Bo Jin (Medical University of South Carolina, Department of Biostatistics, Bioinformatics, and Epidemiology); Xinghua Lu (Medical University of South Carolina, Department of Biostatistics, Bioinformatics, and Epidemiology); |
| Short Abstract: Network graphs based on the Gene Ontology database are now widely used in projects that analyze biological concepts. GOGrapher is a Python library that can be used as the basis for any future research involving the analysis, visualization, or manipulate these graphs. |
| Long Abstract: Click Here |
| Poster B17 |
| Gene profiling and pathway analysis reveal novel cellular signaling networks in Royale College of Surgeon's Rat Model |
| Jin Lu- Centocor |
| Susan Munga (Stem Cell Internal Venture, Cell Biology); Ben Amegadzie (Centocor RIan, Harris); Ben Amegadzie (Centocor Research, Molecular discovery technologies); Ian Harris (Stem Cell Internal Venture, Cell Biology); Xiaozhen Wang (Stem Cell Internal Venture, Cell Biology); |
| Short Abstract: A powerful statistics analysis of gene profiling of rat eyes and pathway study revealed several distinct biological pathways in the cells treated by hUTC. Both network prediction and experiment results suggested protection of photoreceptors in the eyes contributed to the vision protection in this Rat model |
| Long Abstract: Click Here |
| Poster B18 |
| Ranking single nucleotide polymorphisms by potential deleterious effects |
| Phil Hyoun Lee- Queen's University |
| Shatkay Hagit (Queen's University, School of Computing); |
| Short Abstract: We propose a new integrative scoring system for prioritizing SNPs based on their possible deleterious effects to human health in a probabilistic framework. We also provide the evaluation result of our system on the OMIM database, which is one of the most widely-used databases of human genes and genetic disorders. |
| Long Abstract: Click Here |
| Poster B19 |
| Protein phosphorylation sites prediction server integrating sequence dependent features and potential energy |
| Xishu Wang- University o illinois at Chicago |
| Guijun Zhao (UIC, Bioengineering); Robert Langlois (UIC, Bioengineering); Hui Lu (UIC, Bioengineering); |
| Short Abstract: We have developed a kinase-specific phosphorylation prediction server at (http://proteomics.bioengr.uic.edu/) that uses machine learning to accurately characterize residue phosphorylation potential. Our goal was to develop a server that can identify key factors that characterized phosphorylation. These features include sequence dependent features and potential energy in the predicted kinase-peptide complexes. |
| Long Abstract: Click Here |
| Poster B20 |
| A Bayesian network framework for integrating high throughput/high dimensional data to model the regulatory networks behind cancer outcomes |
| Olivier Gevaert- Katholieke Universiteit Leuven |
| 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 B21 |
| Translational Medicine through Comparative Genomics and data integration |
| Wilco Fleuren- Radboud University Nijmegen Medical Centre |
| Raoul Frijters (Radboud University Nijmegen Medical Centre, CMBI); Tim Hulsen (Radboud University Nijmegen Medical Centre, CMBI); Peter Groenen (Organon part of Schering-Plough Corporation, MDI); Jacob de Vlieg (Organon part of Schering-Plough Corporation, MDI); Wynand Alkema (Organon part of Schering-Plough Corporation, MDI); |
| Short Abstract: In order to choose the most appropriate animal model to test new drugs in, and to translate the findings to an effect in human, we have developed a method which retrieves, analyses and displays gene pathway conservation for a pharmaceutical target or drug of interest, by integrating different types of data. |
| Long Abstract: Click Here |
| Poster B22 |
| Genetic Patterns of considering BMI risk factors based on community cohort |
| Ji-young Lee- Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention |
| Ju-young Lee (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Functional Genomics); Jong-young Lee (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Functional Genomics); Jee-yeon Heo (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Bio-Medical Informatics); Mi-sun Park (Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Division of Bio-Medical Informatics); |
| Short Abstract: The genetic and environmental influences of risk factor are characteristic of, but not unique, persons with obesity or non-obesity. So we select BMI as representation of obesity risk factor, then we analyze genetic patterns of considering BMI criteria using two types of data from the epidemiological and genetical. |
| Long Abstract: Click Here |
| Poster B23 |
| EHCO 2.0 (Encyclopedia of Hepatocellular Carcinoma genes Online 2.0) |
| Chia-Hung Liu- National Taiwan University |
| Kuan-Ting Lin (Academia Sinica, Institute of Information Science); Chi-Ying F. Huang (Institute of Clinical Medicine, National Yang-Ming University); Chun-Nan Hsu (Academia Sinica, Institute of Information Science); |
| Short Abstract: We extend the numbers of HCC-related genes from 2,906 in previous version to 3,963 by continuously collecting and computational prediction. For deciphering the hepatocarcinogenesis at the transcriptome level, we annotated and identified their expression of alternative splicing variants. The results can be accessed through EHCO 2.0 (http://bioagent.iis.sinica.edu.tw/EHCO2/). |
| Long Abstract: Click Here |
| Poster B24 |
| In-silico Drug Design |
| Rosangela Hickson- Santa Casa de Misericordia de Belo Horizonte |
| Guilherme Oliveira (Fiocruz - MG, Laboratorio de Parasitologia Celular e Molecular); |
| Short Abstract: Schistosomiasis is endemic in 74 countries. We have produced by homology modeling 169 structures in addition to 11 experimentally determined structures. For each sequence a druggability index (DI –druggability index) is calculated and automatic docking of all the molecules of database will be performed. |
| Long Abstract: Click Here |
| Poster B25 |
| Identification of candidate disease genes from conserved coexpression |
| Paolo Provero- University of Turin |
| Ugo Ala (University of Turin, Genetics, Biology and Biochemistry); Rosario Michael Piro (University of Turin, Genetics, Biology and Biochemistry); Elena Grassi (University of Turin, Genetics, Biology and Biochemistry); Christian Damasco (University of Turin, Genetics, Biology and Biochemistry); Lorenzo Silengo (University of Turin, Genetics, Biology and Biochemistry); Martin Oti (University Medical Centre Nijmegen, Human Genetics); Ferdinando Di Cunto (University of Turin, Genetics, Biology and Biochemistry); |
| Short Abstract: We present a method for the identification of candidate disease genes based on the analysis of gene expression data. The method is based on the construction of a human-mouse conserved coexpression network and produces high-probability candidates for 81 genetic diseases of unknown molecular basis. |
| Long Abstract: Click Here |
| Poster B26 |
| Inferring Pathway Differences from Gene Expression Data |
| Jarred McCaffrey- University of Massachusetts Lowell |
| Gary Livingston (University of Massachusetts Lowell, Computer Science); Patrick Shaughnessy (University of Massachusetts Lowell, Computer Science); |
| Short Abstract: We have developed a computational method that uses known pathways and Fisher's r-to-z transform for correlations to infer significant differences in gene interactions between subsets of a gene-expression microarray dataset. A preliminary analysis of this method shows that it is able to rediscover known differences between two subtypes of lymphoma. |
| Long Abstract: Click Here |
| Poster B27 |
| Pooling breast cancer datasets has a synergetic effect on classification performance and improves signature stability |
| Martin Van Vliet- Delft, University Of Technology |
| F Reyal (Institut Curie, Department of Surgery); Hugo Horlings (Netherlands Cancer Institute, Department of Experimental Therapy); Marc van de Vijver (Netherlands Cancer Institute, Department of Experimental Therapy); Marcel Reinders (Delft University of Technology, ICT Group); Lodewyk Wessels (Netherlands Cancer Institute, Bioinformatics and Statistics Group); |
| Short Abstract: Pooling breast cancer datasets has a synergetic effect on prediction accuracy in 73% of the cases. We also observe a significant positive correlation between the number of datasets that is pooled and the validation performance. Moreover, limited overlap of current signature genes can be attributed to small sample size. |
| Long Abstract: Click Here |
| Poster B28 |
| The Interplay between Mutations and Epigenetic Alterations during Oncogenesis |
| Leander Van Neste- Ghent University |
| Kornel Schuebel (Johns Hopkins, Cancer Biology Division); Nita Ahuja (Johns Hopkins, Cancer Biology Division); James Herman (Johns Hopkins, Cancer Biology Division); Stephen Baylin (Johns Hopkins, Cancer Biology Division); Leslie Cope (Johns Hopkins, Biometry and Clinical Trials Division); Timothy Chan (Memorial Sloan Kettering, Human Oncology and Pathogenesis Program); Wim Van Criekinge (Ghent University, Molecular Biotechnology); |
| Short Abstract: The silencing frequencies of DNA-hypermethylated genes, found through a computational, microarray based, method is compared to their mutation frequencies. The genes identified by this large scale screening procedure are not only useful to gain insight into oncogenesis and the underlying pathways, but can also be crucial early-detection or staging biomarkers. |
| Long Abstract: Click Here |
| Poster B29 |
| IDENTIFICATION OF TWO FUNCTIONAL GENE CLUSTERS DRIVING CHRONIC INFLAMMATION: TRANSCRIPTOME ANALYSIS OF MOUSE ARTHRITIS MODELS |
| Anton Glueck- Novartis Institutes for BioMedical Research |
| Nozomi Takahashi (Radboud University Medical Centre Nijmegen, NCMLS, Rheumatology Research and Advanced Therapeutics, Dept. Rheumatology); Victor de Jager (Netherlands Bioinformatics Centre, BioAssist); Nicole Hartmann (Novartis Pharma AG, GeneChip Lab group); Martin Letzkus (Novartis Pharma AG, Genomics Factory); Frank Staedtler (Novartis Institutes for BioMedical Research, Sampling/RNA extraction group); Wim van den Berg (Radboud University Medical Centre Nijmegen, NCMLS, Rheumatology Research and Advanced Therapeutics, Dept. Rheumatology); Leo Joosten (Radboud University Medical Centre Nijmegen, NCMLS, Rheumatology Research and Advanced Therapeutics, Dept. Rheumatology); |
| Short Abstract: Rheumatoid arthritis (RA) is a chronic autoimmune disease with unknown etiology. We analyzed the transcriptome of two mouse models of RA by using oligonucleotide genome arrays. Principal component analysis (PCA) identified 1) partially common molecular mechanisms between the two models and 2) Two functional classes of genes driving chronic inflammation. |
| Long Abstract: Click Here |
| Poster B30 |
| Classification of novel malaria drug targets for efficient possible drug combination |
| Chinwe Ekenna- Covenant University |
| Segun Fatumo (Covenant University, Department of Computer and Information Sciences); Ezekiel Adebiyi (Covenant University, Department of Computer and Information Sciences); Gunnar Schramm (DKFZ, Theoretical Bioinformatic); Rainer Konig (University of Heidelberg, IPMB); |
| Short Abstract: Plasmodium falciparum-the parasite responsible for the deadly malaria disease has become resistant to monoteraphic drugs like chloroquine.We identified the pathways for the newly proposed drug targets(Fatumo et al 2008)and proffer possible combinable targets to produce an efficient malaria drug |
| Long Abstract: Click Here |
| Poster B31 |
| Discovery of noise-tolerant cancer specific biomarkers |
| Luc Dehaspe- OncoMethylome BVBA |
| Valérie Deregowski (Oncomethylome BVBA, ); Josef Straub (Oncomethylome BVBA, ); Geert Trooskens (Oncomethylome BVBA, ); Wim Van Criekinge (Oncomethylome BVBA, ); |
| Short Abstract: We present a novel biomarker scoring strategy based on a weighted combination of a marker’s discriminating power and its robustness. The strategy is applied to the discovery of genes that are differentially methylated in cancer samples. |
| Long Abstract: Click Here |
| Poster B32 |
| dA systems biology perspective on CCC development. Focus on MAPK-Singnaling and |
| Andreas Teufel- Johannes Gutenberg Univ |
| No additional authors |
| Short Abstract: We demonstrated the liver microenvironment to potentially hold essential functions and structutres key to CCC. In addition, we identified the MAPK signaling pathway consistanly to be enriched in all pathway analyses, warranting an evaluation of MAPK kinase inhibitors such as sorafenib in treatment of CCC. |
| Long Abstract: Click Here |
| Poster B33 |
| Genetic pathway analysis may point to additional applications in of known |
| Markus Krupp- Johannes Gutenberg Univ |
| No additional authors |
| Short Abstract: When death is aggregated by age, cancer has surpassed heart disease as the leading cause of death for those younger than age 85 since 1999. Thus our work was focused on cancer to improve existing therapies as well as revealing new therapeutic targets. |
| Long Abstract: Click Here |
| Poster B34 |
| InnateDB - a manually-curated interactome database and analysis platform for systems level analysis of the mammalian immune response. |
| Nicolas Richard- Simon Fraser University |
| David J. Lynn (Simon Fraser University, Department of Molecular Biology and Biochemistry); Geoffrey L. Winsor (Simon Fraser University, Department of Molecular Biology and Biochemistry); Matthew R. Laird (Simon Fraser University, Department of Molecular Biology and Biochemistry); Aaron Barsky (University of British Columbia, Department of Computer Science); Jennifer L. Gardy (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Fiona M. Roche (Simon Fraser University, Department of Molecular Biology and Biochemistry); Timothy H.W. Chan (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Calvin Chan (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Naisha Shah (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Raymond Lo (Simon Fraser University, Department of Molecular Biology and Biochemistry); Misbah Naseer (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Jaimmie Que (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Melissa Yau (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Michael Acab (Simon Fraser University, Department of Molecular Biology and Biochemistry); Dan Tulpan (Simon Fraser University, Department of Molecular Biology and Biochemistry); Matthew Whiteside (Simon Fraser University, Department of Molecular Biology and Biochemistry); Avinash Chikatamarla (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Tamara M. Munzner (University of British Columbia, Department of Computer Science); Karsten Hokamp (Trinity College Dublin, Smurfit Institute of Genetics); Bernadette Mah (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Robert E.W. Hancock (University of British Columbia, Centre for Microbial Diseases and Immunity Research); Fiona S.L. Brinkman (Simon Fraser University, Department of Molecular Biology and Biochemistry); |
| Short Abstract: InnateDB (www.innatedb.ca) is a publicly available manually-curated, integrative biology database of the human and mouse molecules, interactions and pathways involved in innate immunity along with centralized annotation on the broader human and mouse interactomes. Integrated bioinformatics and visualization tools facilitate systems-level investigations of the mammalian innate immune response and beyond. |
| Long Abstract: Click Here |
| Poster B35 |
| Narrowing the search for novel aging genes with systems biology |
| Kristen Fortney- University of Toronto |
| Igor Jurisica (University of Toronto, Dept. of Medical Biophysics); |
| Short Abstract: Many genes are differentially regulated in aging mice, but which of these changes actually affect the aging process? Here we use computational methods to characterize the few genes known to influence aging, and apply our results to find promising targets for study in the large set of age-regulated genes. |
| Long Abstract: Click Here |
| Poster B36 |
| An automatic fuzzy clustering method for omics data analysis |
| Nabil Belacel- National Research Council of Canada |
| Miroslava Cuperlovic-Culf (NRC, IIT); Qian Wang (NRC, IIT); |
| Short Abstract: A new strategy for automatic clustering of different omics data was developed. Our approach is based on fuzzy logic to uncover information about the relative likelihood of each feature belonging to each predefined number of clusters, thus providing information regarding different omics (gene, protein, metabolite,...) multifunctionality.the Clustering will be performed on real data. |
| Long Abstract: Click Here |
| Poster B37 |
| The PathOlogist: An Automated Tool for Pathway-Centric Analysis |
| Sharon Greenblum- National Institutes of Health |
| Sol Efroni (National Institutes of Health, National Cancer Institute); Carl Schaefer (National Institutes of Health, National Cancer Institute); Ken Buetow (National Institutes of Health, National Cancer Institute); |
| Short Abstract: The PathOlogist is a new resource designed to analyze sets of experimental data within the context of pathways. This stand-alone tool uses gene abundance values to calculate activity and consistency metrics for pathways in a set of canonical pathways while generating a visual representation of pathway scores and alterations. |
| Long Abstract: Click Here |
| Poster B38 |
| A Systematic Strategy for the Discovery of Candidate Genes Responsible for Phenotypic Variation |
| Paul Fisher- University of Manchester |
| Robert Stevens (University of Manchester, Computer Science); Andrew Brass (University of Manchester, Life Sciences); Paul Fisher (University of Manchester, Computer Science); |
| Short Abstract: The combination of Quantitative Trait Loci, Microarray data, and text can be used to search for candidate genes and pathways responsible for phenotypic variation. Workflows provide a means for systematically processing these large datasets and represent a framework for the re-use and the explicit declaration of experimental methods. |
| Long Abstract: Click Here |
| Poster B39 |
| Applications of Homozygosity Haplotype in the Study of Human Genetic Diseases with High Density SNP Genotype |
| Haiyan Jiang- Dalhousie University |
| Duane Guernsey (Dalhousie University, Department of Pathology); Mark Samuels (University of Montreal, Department of Medicine); Andrew Orr (Dalhousie University, Department of Ophthalmology and Visual Sciences); |
| Short Abstract: Genome-wide detection of haplotype sharing is a difficult problem. A Homozygosity Haplotype (HH) method was proposed recently. The applicability and the effectiveness of HH in identifying the candidate region of causative gene were studied, and a new strategy for the genome-wide screening of the known causative genes was developed. |
| Long Abstract: Click Here |
| Poster B40 |
| The ROP-K family of Toxoplasma gondii: the parasite kinome reveals an expanded family of secreted kinases with possible role in host-pathogen interaction. |
| Lucia Peixoto- University of Pennsylvania |
| Omar Harb (Posdoctoral Fellow, Biology, SAS); Paul H. Davis (Posdoctoral Fellow, Biology, SAS); Daniel Beiting (Posdoctoral Fellow, Biology, SAS); Feng Chen (PhD student, Chemistry, SAS); David S. Roos (Professor, Biology, SAS); |
| Short Abstract: Toxoplasma gondii is an important human pathogen and model apicomplexan. Since parasite kinases are likely to be central to both parasite-specific regulation and host-cell modulation, we characterized the entire T.gondii kinome and revealed the presence of an expanded family of secreted kinases expected to have a role in host-pathogen interaction. |
| Long Abstract: Click Here |
| Poster B41 |
| A metagenomics pipeline for identifying pathogens from clinical specimens |
| Heather Kent- National Microbiology Laboratories, Public Health Agency of Canada |
| Shaun Tyler (National Microbiology Laboratories, PHAC, Genomics Core Facility); Christine Bonner (National Microbiology Laboratories, PHAC, Genomics Core Facility); Geoff Peters (National Microbiology Laboratories, PHAC, Genomics Core Facility); Shane Thiessen (National Microbiology Laboratories, PHAC, Bioinformatics Core Facility); Franklin Bristow (National Microbiology Laboratories, PHAC, Bioinformatics Core Facility); Philip Mabon (National Microbiology Laboratories, PHAC, Bioinformatics Core Facility); Gary Van Domselaar (National Microbiology Laboratories, PHAC, Bioinformatics Core Facility); Morag Graham (National Microbiology Laboratories, PHAC, Genomics Core Facility); |
| Short Abstract: Rapid pathogen identification is crucial in the diagnosis of severe clinical infections. Pyrosequencing technology rapidly generates vast amounts of sequence data that can be used to survey complex clinical specimens. We present a metagenomics sequencing strategy and bioinformatics pipeline to facilitate the identification of the microbial community within clinical samples. |
| Long Abstract: Click Here |
| Poster B42 |
| Analysis for Concordance of Evolution Between the Large, Medium and Small Segments of Hantavirus Genome |
| Nutan Mayande- New Mexico State University |
| Brook Milligan (New Mexico State University, Department of Biology); |
| Short Abstract: Rodents carrying different subtypes of hantavirus coexist in the same geographic area and individual hosts may be coinfected. This creates the possibility that different strains could be important in the origin of new ones. To ascertain the prevalence of this phenomenon, we performed a phylogenetic analysis of the three genome segments. |
| Long Abstract: Click Here |
| Poster B43 |
| Integrating methylation and gene expression microarray data |
| Shuying Sun- The Ohio State University |
| No additional authors |
| Short Abstract: DNA methylation has been shown to play an important role in the silencing of tumor suppressor genes in varying tumor types. We apply a regression model to study the correlations between DNA methylation and gene expression in breast cancer cell line microarray data. |
| Long Abstract: Click Here |
| Poster B44 |
| Bioinformatics characterization of Novel Malaria Drug Targets |
| Omolola Akinyemi- Covenant University |
| Segun Fatumo (Covenant University, Department of Computer and Information Sciences); Ezekiel Adebiyi (Covenant University, Department of Computer and Information Sciences); Olalere Alao (University of Nssukka, Department of Mathematics and Statistics); |
| Short Abstract: Malaria is one of the world's most common and serious tropical diseases. In a recent work [Fatumo et al 2008] 22 novel drug targets were predicted for malaria. In this work we sought to characterize the binding sites/hotspots on the drug targets |
| Long Abstract: Click Here |
| Poster B45 |
| Bridging Experiments using Integrative Tools |
| James Cavalcoli- University of Michigan |
| No additional authors |
| Short Abstract: Data and tool integration such as tools from NCIBI is key to identifying overarching biological processes involved in common biologic processes. Use of NCIBI integrated tools such as Oncomine, MiMI and Cytoscape and NLP parsed literature combined together helps to corroborate and validate essential phenotypic assessments like metastasis. |
| Long Abstract: Click Here |
| Poster B46 |
| Non-coding RNA detection, structure prediction and miRNA target analysis in Taenia solium |
| Pablo Cordero- Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México |
| Homero Garcés-Flores (Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Immunology); Marco José (Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Immunology); José Pascual (Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Immunology); Juan Laclette (Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Immunology); |
| Short Abstract: In this work, we explore the presence and possible roles of non-protein coding genes (ncRNA) in the most recent contigs of the larval stage of Taenia solium. Using standard computational methods, we detected the presence of many ncRNA putative genes and micro RNAs as well as their putative targets. |
| Long Abstract: Click Here |
| Poster B47 |
| GOSteiner: a graph theoretic measure of protein functional coherence |
| Adam Richards- Medical University of South Carolina |
| Baerbel Rohrer (Medical University of South Carolina, Department of Ophthalmology, Department of Neurosciences, Division of Research); Lam Tsoi (Medical University of South Carolina, Department of Biostatistics, Bioinformatics and Epidemiology); Brian Muller (Medical University of South Carolina, Department of Biostatistics, Bioinformatics and Epidemiology); Xinghua Lu (Medical University of South Carolina, Department of Biostatistics, Bioinformatics and Epidemiology); |
| Short Abstract: The results of microarray and other high-throughput experiments are often in the form of gene/protein lists. For validation the Gene Ontology which is organized as a complex network, along with methods from graph theory can be used to develop a general statistical measure of gene/protein group functional relatedness. |
| Long Abstract: Click Here |
| Poster B48 |
| METRIC MATRICES k-MEANS (MMk-MEANS) FOR CLUSTERING MALARIA MICROARRAY DATA |
| VICTOR OSAMOR- COVENANT UNIVERSITY |
| EZEKIEL ADEBIYI (COVENANT UNIVERSITY, COMPUTER AND INFO. SCI., CST); JELILLI OYELADE (COVENANT UNIVERSITY, COMPUTER AND INFO. SCI., CST); SEYDOU DOUMBIA (UNIVERSITY OF BAMAKO, MALARIA RESEARCH TRAINING CENTER); |
| Short Abstract: Urgent control and drug remedies arising from microarray analysis result can provide good solution to the malaria pandemic in Africa. We develop a novel Pearson correlation-based enhanced MMk-means with improved run-time than traditional k-means, O(nkl), overlapped and enhanced k-means, O(kn) (Fahim et al 2006) to efficiently cluster malaria data. |
| Long Abstract: Click Here |
| Poster B49 |
| Ethnic Polymorphism Evaluation Tool (E-Pet) |
| Mariam Nersisyan- University |
| Deendayal Dinakarpandian (University of Missouri Kansas City, Department of Electrical Engineering and Computer Science); |
| Short Abstract: E-Pet is an online tool that can be used to compare two sets of sequences. E-Pet is integrated with sequence data from the SNP500 Cancer Project and can be used to compare gene sequences of deidentified humans to highlight polymorphic differences between African/African-American, Caucasian, Hispanic and Pacific Rim ethnic groups. |
| Long Abstract: Click Here |
| Poster B50 |
| Belgium |
| Geert Trooskens- Oncomethylome BVBA |
| Geert Trooskens (Oncomethylome BVBA, Research & Development); Josef Straub (Oncomethylome BVBA, Research & Development); Jean-Pierre Renard (Oncomethylome BVBA, Research & Development); Johan Vandersmissen (Oncomethylome BVBA, Research & Development); An Nijs (Oncomethylome BVBA, Research & Development); Luc Dehaspe (Oncomethylome BVBA, Research & Development); Wim Van Criekinge (Oncomethylome BVBA, Research & Development); |
| Short Abstract: Designing Methylation Specific PCR (MSP) primers can be time consuming and error-prone. In addition, the design of a working MSP assay can be the bottleneck for high-throughput screening. We present an automated algorithm, beginning from a gene list all the way through to the primer sequences. |
| Long Abstract: Click Here |
| Poster B51 |
| Analysis of Correlated Mutations in HIV-1 Protease Using Spectral Clustering |
| ying liu- University of Pittsburgh |
| Eran Eyal (University of Pittsburgh, Department of Computational Biology); Ivet Bahar (University of Pittsburgh, Department of Computational Biology); |
| Short Abstract: We performed sequence covariance analysis for HIV-1 protease with spectral clustering. Two distinctive clusters of correlated residues were obtained: one related to multi-drug resistance mutations; and the other to the phylogenetic mutations. These two clusters correspond to the hinge and flexible regions, respectively, by normal mode analysis of the structure. |
| Long Abstract: Click Here |
| Poster B52 |
| A weighted human network for the identification of modifiers of disease genes application to Noonam and Leopard syndrome. |
| Gianni Cesareni- University of Rome Tor Vergata |
| Andrew Chatr Aryamontri (University of Rome Tor Vergata, Biology); Luisa Castagnoli (University of Rome Tor Vergata, Biology); Arnaud Ceol (University of Rome Tor Vergata, Biology); Stefano Costa (University of Rome Tor Vergata, Biology); Luana Licata (University of Rome Tor Vergata, Biology); Emanuela Ferrari (University of Rome Tor Vergata, Biology); Michele Tinti (University of Rome Tor Vergata, Biology); |
| Short Abstract: We have assembled a weighted human interactome and we have used it to identify modifiers of the function of SHP2 a phosphatase whose activity is upregulated in Noonam syndrome |
| Long Abstract: Click Here |
| Poster B53 |
| postdoc |
| xiaosong wang- the National Center for Integrative Bioinformatics, the Michigan Center for Translational Pathology |
| No additional authors |
| Short Abstract: Gene fusions are important in the initial steps of carcinogenesis, and represent a critical class of therapeutic targets. Based on NCIBI tools and technologies, we discovered several novel characteristics of gene fusions in human malignancies, and created an integrative Bioinformatics model for the translation of bio-data into novel gene fusions. |
| Long Abstract: Click Here |
| Poster B54 |
| Rat Genome Database Disease Portals |
| Mary Shimoyama- Medical College of Wisconsin |
| Stan Laulederkind (Medical College of Wisconsin, Human and Molecular Genetics Center); Tim Lowry (Medical College of Wisconsin, Human and Molecular Genetics Center); Rajni NIgam (Medical College of Wisconsin, Human and Molecular Genetics Center); Victoria Petri (Medical College of Wisconsin, Human and Molecular Genetics Center); Jennifer Smith (Medical College of Wisconsin, Human and Molecular Genetics Center); Burcu Bakir (Medical College of Wisconsin, Human and Molecular Genetics Center); Jeff dePons (Medical College of Wisconsin, Human and Molecular Genetics Center); Alex Stoddard (Medical College of Wisconsin, Human and Molecular Genetics Center); Elizabeth Worthey (Medical College of Wisconsin, Human and Molecular Genetics Center); Simon Twigger (Medical College of Wisconsin, Human and Molecular Genetics Center); Melinda Dwinell (Medical College of Wisconsin, Human and Molecular Genetics Center); Howard Jacob (Medical College of Wisconsin, Human and Molecular Genetics Center); |
| Short Abstract: RGD’s Disease Portals provide research platforms utilizing multiple ontologies to integrate disease related gene, QTL, strain and pathway data. Data mining and visualization tools provide easy access to both the novice and experienced user offering genome-wide views of the data as well as functional analysis of gene sets. |
| Long Abstract: Click Here |
| Poster B55 |
| Clinical Omics Database System (CODS), integrating clinical and molecular biological information. |
| Hiroshi Mizushima- Tokyo Medical And Dental University |
| Yasen Mahmut (Information Center For Medical Sciences, Tokyo Medical And Dental University); Kazuo Shimokawa (Information Center For Medical Sciences, Tokyo Medical And Dental University); Kaoru Mogushi (Information Center For Medical Sciences, Tokyo Medical And Dental University); Ken Miyaguchi (Information Center For Medical Sciences, Tokyo Medical And Dental University); Masaya Itoda (Information Center For Medical Sciences, Tokyo Medical And Dental University); Hiroshi Tanaka (Information Center For Medical Sciences, Tokyo Medical And Dental University); |
| Short Abstract: Development of “TMDU Clinical Omics Database” has been conducted by integrating OMICS information and clinical informa-tion. We currently collected 500+ cases including hepatic, colon, and oral cancer. Database server can be accessed at http://omix.tmd.ac.jp/. This would be the first integrated clinical database with both clinical and molecular biological information. |
| Long Abstract: Click Here |
| Poster B56 |
| The Association study of gene expression data and SNP array data on MDS model |
| Jing Fan- The Methodist Hospitial Research Institute |
| Xiaobo Zhou (The Methodist Hospital Research Institute, Center for Biotechnology & Informatics and Department of Radiology); Stephen Wong (The Methodist Hospital Research Institute, Center for Biotechnology & Informatics and Department of Radiology); Lingyun Wu (The Methodist Hospital Research Institute, Center for Biotechnology & Informatics and Department of Radiology); Wan-Ting Huang (The Methodist Hospital, Department of Pathology); Chung-Che Chang (The Methodist Hospital, Department of Pathology); |
| Short Abstract: Two models are developed to discover the regulatory mechanism by association study of gene expression and SNP array data. One model focus on identification and ranking regulatory SNPs on single gene while the other discovers SNP-contained regulation motifs within clusters of co-expressed genes. |
| Long Abstract: Click Here |
| Poster B57 |
| Machine Learning Analysis of Cancer Cachexia |
| Roman Eisner- University of Alberta |
| Jianguo Xia (University of Alberta, Computing Science); David Hau (University of Alberta, Biological Sciences); Cynthia Stretch (University of Alberta, Oncology); Russ Greiner (University of Alberta, Computing Science); Vickie Baracos (University of Alberta, Oncology); David Wishart (University of Alberta, Computing Science); |
| Short Abstract: Cachexia is the wasting away of bodily tissues in people who are not trying to lose weight. Late stage cancer patients can become cachectic, but this change is not fully understood. We analyze urinary metabolomic data to investigate important metabolites involved in cachexia, and predict cachectic status of patients. |
| Long Abstract: Click Here |
| Poster B58 |
| Identification of Key Amino Acid Properties for HLA Class I Peptides: A Computational Approach |
| Mitra Basu- Johns Hopkins University |
| Ankit Rakha (Johns Hopkins University, Computer Science); |
| Short Abstract: A regular and a meta classifier are used to show that the selected 8 key amino acid properties when used as descriptors for classification of HLA binding peptides, performed 5 to 17% better than other numerical descriptors. Our study elucidates the role of amino acid structure in H.LA peptide binding. |
| Long Abstract: Click Here |
| Poster B59 |
| Integrating large-scale data from splicing microarray experiments |
| Ana Rita Grosso- Institute of Molecular Medicine |
| Ines Mollet (Institute of Molecular Medicine, Cell Biology Unit); Maria Carmo-Fonseca (Institute of Molecular Medicine, Cell Biology Unit); |
| Short Abstract: Some of the splicing decisions occurring in specific physiological or pathological conditions are expected to be caused by differences in the concentration and/or activity of regulatory proteins. We have initiated a global meta-analysis that integrates data from microarray experiments in several cancer types making use of ExonMine database (http://www.imm.fm.ul.pt/exonmine). |
| Long Abstract: Click Here |
| Poster B60 |
| The Network Properties of Prognostic Markers for Cancer |
| Paul Boutros- University of Toronto |
| Igor Jurisica (University of Toronto, Department of Medical Biophysics); Linda Penn (University of Toronto, Department of Medical Biophysics); Ming-Sound Tsao (University of Toronto, Department of Medical Biophysics); |
| Short Abstract: Cancer is a heterogeneous disease, but current therapies treat most patients similarly. Many groups seek to use mRNA signatures to personalize therapy. We demonstrate the network properties of effective prognostic signatures, relative to ineffective ones. We exploit the large I2D PPI database and develop a novel permutation analysis methodology. |
| Long Abstract: Click Here |
| Poster B61 |
| Candidate Genes Prioritization with Tissue Expression Profiles |
| Fabien Campagne- Weill Cornell Medical College |
| No additional authors |
| Short Abstract: This poster will review the use of tissue expression profiles to prioritize disease candidate genes and illustrate these approaches with the prioritization of genetic risk factors for late-onset Alzheimer’s disease (LOAD) and Ataxia. The recent discovery of the P86L polymorphism in CALHM1 as a LOAD risk factor will be highlighted. |
| Long Abstract: Click Here |
| Poster B62 |
| A 12-gene expression signature prognostic for squamous cell lung carcinoma |
| ChangQi Zhu- Ontario Cancer Institute, University Health Network, University of Toronto |
| Dan Strumpf (Ontario Cancer Institute, University Health Network, University of Toronto, Applied Molecular Oncology); ChunYan Li (School of Medicine, Jishou University, Parmacology); Frances Shepherd (University Health Network, University of Toronto, Medicine); Igor Jurisica (University Health Network, University of Toronto, Computer Science); Ming-sound Tsao (Ontario Cancer Institute,University Health Network, University of Toronto, Medical Biophysics); |
| Short Abstract: We identified a 12-gene expression signature prognostic for squamous cell carcinoma of the lung based on goodness-of-fit (R square). The signature was validated in two independent microarray datasets. In addition, its superior performance over Raponi's original 50-gene signature and a newly publshed 50-gene signature was demonstrated by side-by-side comparison. |
| Long Abstract: Click Here |
| Poster B63 |
| Inferring pathway activity toward precise disease classification |
| Eunjung Lee- Korea Advanced Institute of Science and Technology |
| Han-Yu Chuang (University of California San Diego, Bioinformatics Program); Trey Ideker (University of California San Diego, Department of Bioengineering); Doheon Lee (Korea Advanced Institute of Science and Technology, Department of Bio and Brain Engineering); |
| Short Abstract: The proposed method incorporates pathway information in a condition-specific manner into the disease classification procedure to address challenges due to the genetic heterogeneity in complex diseases. It not only predicts disease risks more accurately than previous approaches but also provides putative molecular models for the disease of interest. |
| Long Abstract: Click Here |
| Poster B64 |
| Systematically determining the key biological mechanisms underlying non-small cell lung cancer by integrative computational biology approach |
| Dan Strumpf- Ontario Cancer Institute, Princess Margaret Hospital, University Health Network |
| Wing Xie (Princess Margaret Hospital, University Health Network, Ontario Cancer Institute); Chang-Qi Zhu (Princess Margaret Hospital, University Health Network, Ontario Cancer Institute); Frances A. Shepherd (Ontario Cancer Institute, Princess Margaret Hospital, University Health Network, Department of Medical Oncology and Hematology); Ming-Sound Tsao (Princess Margaret Hospital, University Health Network, Ontario Cancer Institute); Igor Jurisica (Princess Margaret Hospital, University Health Network, Ontario Cancer Institute); |
| Short Abstract: Multiple prognostic gene-based classifiers for non-small cell lung cancer (NSCLC), with little overlap between gene sets, were used to generate protein interaction network from I2D database. This network is significantly more inter-connected compared to random networks, containing sets of “critical” nodes connecting multiple classifier-assigned proteins, linking pathways potentially underlying NSCLC. |
| Long Abstract: Click Here |
| Poster B65 |
| A novel and powerful method in the analysis of array-based comparative genomic hybridization (aCGH) data |
| Yang Xiang- LSCDD |
| Gopinath Ganji (LSCDD, LSCDD); Ketan Patel (LSCDD, LSCDD); Vinisha Khemani (LSCDD, LSCDD); Greg Tucker-Kellogg (LSCDD, LSCDD); Michael Bittner (TGEN, TGEN); Amit Aggarwal (LSCDD, LSCDD); |
| Short Abstract: A novel and very powerful method for the analysis of array-based comparative genomic hybridization (aCGH) data, accurate detection of DNA copy number (ADDCN), has been developed. This method has been applied into a selection of cancer cell lines and produce very good result. |
| Long Abstract: Click Here |
| Poster B66 |
| Microarray meta-analysis in cystic fibrosis context |
| VOISIN Grégory- IRIC/ CHUM |
| Grégory Voisin (IRIC, Bioinformatics); François Lefebvre (IRIC, Bioinformatics); Sébastien Lemieux (IRIC, Bioinformatics); andre dagenais (CR CHUM, Respiratory Health); Yves Berthiaume (CR CHUM, Respiratory Health); |
| Short Abstract: We have developed a new approach in microarray analysis exploitation. Based on the standardized statistical method, we compare several microarray experiments either sharing the same biological problematic, or using the same analysis platform. The combination of these two methodologies allows us to detect the specific modulation. |
| Long Abstract: Click Here |
| Poster B67 |
| A empirical comparative study of prediction model in type 2 diabetes mellitus using molecular epidemiological data |
| Lee Ju Young- Centers for Disease Control and Prevention |
| Lee Ji-Young (Centers for Disease Control and Prevention, div. of structural and functional Genomics); Kim Dan Bi (Centers for Disease Control and Prevention, div. of biomedical informatics); Heo Jee Yeon (Centers for Disease Control and Prevention, div. of biomedical informatics); Mi Sun park (Centers for Disease Control and Prevention, div. of biomedical informatics); Lee Chang-Hoon (Seoul National University College of Medicine, Department of Internal Medicine and Lung Institute); Lee Jong Young (Centers for Disease Control and Prevention, div. of structural and functional Genomics); Kim Hyung-Lae (Centers for Disease Control and Prevention/NIH, general director); |
| Short Abstract: Information in the human genome is believed to provide a means of elucidating the genetic causes of complex diseases, such as Type 2 diabetes mellitus (T2DM). To search for an early warning system for T2DM, we compared our new models with existing models in terms of the rate of errors |
| Long Abstract: Click Here |
| Poster B68 |
| Exploring molecular pathways related to psychiatric diseases using PADB database |
| Hwanseok Rhee- Yonsei University Health System |
| Jin-Sung Lee (Yonsei University Health System, Clinical Genetics); Chul-Ho Lee (Yonsei University Health System, Clinical Genetics); |
| Short Abstract: We will present the utilities of the PADB database to explore molecular pathways related to psychiatric diseases such as schizophrenia and bipolar disorder. The PADB database will help researchers to review previously investigated genes more efficiently, and will expand knowledge by using the genomic and functional contexts of the genes. |
| Long Abstract: Click Here |
| Poster B69 |
| Drug Resistance Prediction Using Gene Expression Profiling |
| Pavithra Shivakumar- Yale University |
| Michael Krauthammer (Yale University, Pathology); |
| Short Abstract: The NCI anticancer drug screen has made available the sensitivities of 60 cancer cell lines to 40,000 compounds. Using the associated gene expression profiles, we would like to explore the prediction of drug sensitivity for cell lines and drugs that are not part of the initial drug screen. |
| Long Abstract: Click Here |
| Accepted Posters |
| View Posters By Category |
- A) Arrays
- B) Bioinformatics of Health and Disease
- C) Chemical and Pharmaceutical Informatics
- D) Comparative Genomics
- E) Databases
- F) Evolution
- G) Functional Genomics
- H) Gene Prediction
- I) Genome Annotation
- J) Genomics
- K) Interactions
- L) Machine Learning
- M) Population Genetics and Variation
- N) Proteomics
- O) Regulation
- P) Sequence Analysis
- Q) Structure and Function Prediction
- R) Systems Biology and Networks
- S) text mining
- T) Other (includes posters with fewer than 10 submissions)
| Search Posters: |