Poster B-1
MPVAD: System of integration of biological data
R Puga (Faculty of Medicine of Ribeirão Preto, Department of Genetic, University of São Paulo, Ribeirão Pret);
S Amui (Faculty of Pharmaceutical Sciences, University of São Paulo, Ribeirão Preto, SP, Brazil);
D Jorge (Faculty of Medicine of Ribeirão Preto, Department of Genetic, University of São Paulo, Ribeirão Pret);
M Junior (Department of Biotechnology, University of Ribeirão Preto, Ribeirão Preto, SP, Brazil);
A Soares (Faculty of Pharmaceutical Sciences, University of São Paulo, Ribeirão Preto, SP, Brazil);
S Giuliatti (Faculty of Medicine of Ribeirão Preto, Department of Genetic, University of São Paulo, Ribeirão Pret);
Short Abstract: In order to establish a relationship between scientific data of medicinal plants ant poison and poisons of animals and Venom was developed the Medicinal system Plants of Animals Database (MPVAD)
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Poster B-2
IDconverter and IDClight: Conversion and enrichment of
Patricio Yankilevich (Centro Nacional de Investigaciones Oncologicas (CNIO));
Andreu Alibés (Centro Nacional de Investigaciones Oncologicas (CNIO));
Andrés Cañada (Centro Nacional de Investigaciones Oncologicas (CNIO));
Ramón Diaz Uriarte (Centro Nacional de Investigaciones Oncologicas (CNIO));
Short Abstract: IDconverter and IDClight are two extremely user-friendly, high-throughput oriented, freely available web server applications designed and developed to help researchers map accession numbers and identifiers among clones, genes, proteins and chromosomal positions. They also map the identifiers on to pathways and Gene Ontology terms and literature references.
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Poster B-3
A Graph-relational Integrated Database of Human and Mouse Omics data
Junaid Gamieldien (NBN South Africa);
Darren Otgaar (NBN South Africa);
Nadeen Southgate (NBN South Africa);
Daniel A. Jacobson (NBN South Africa);
Short Abstract: We describe a graph-relational integrated data model of human and mouse data, which includes orthology, expression, trait/phenotype information, and several ontologies. Although a prototype, the existing model allows users to perform infinitely complex queries across the integrated resources in a way that approaches ‘in-silico hypothesis generation’.
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Poster B-4
Cyberinfrastructure for Emerging and Re-Emerging Infectious Diseases
Oswald R. Crasta (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Eric Snyder (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Stephen Cammer (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Darius Dziuda (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Zhangjun Fei (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Mike Czar (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Eric Nordberg (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Boyu Yang (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Chengdong Zhang (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Chaitanya Kommidi (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Ranjan Jha (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Yan Zhang (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Anjan Purkayastha (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Rebecca Wattam (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Kelly Williams (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Ron Kenyon (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Rebecca Will (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Joao Setubal (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Bruno W. Sobral (Cyberinfrastructure Group, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and Sta);
Short Abstract: We have established functional cyberinfrastructure (CI) systems in the area of bioinformatics. The resources and outreach activities developed include tools for the curation of the genomes and pathosystems, database and knowledgebase systems for organizing the high-throughput data from pathosystems biology and software systems for analysis and visualization of the data.
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Poster B-5
UniProt: the Universal Protein Resource.
Raja Mazumder (Protein Information Resource, Georgetown University);
Claire ODonovan (European Bioinformatics Institute);
Short Abstract: UniProt is a comprehensive catalog of protein sequence and function, produced by EBI, PIR and SIB. It consists of the UniProt Knowledgebase (expertly curated database), the UniProt Reference Clusters (merged sequences based on sequence identity) and the UniProt Archive (comprehensive sequence repository). An additional component consisting of environmental sequences will be made available later this year.
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Poster B-6
NMR Manager – Metabolomics software for interpreting NMR spectra
Robert Stones (Central Science Laboratory);
Adrian Charlton (Central Science Laboratory);
James Donarski (Central Science Laboratory);
Short Abstract: Metabolomics software developed to analyze/store NMR spectra; with the capability to graphically display and compare experimental and database spectra. Harnessing automated peak detection algorithms and statistical methods to compare experimental NMR against statistically generated populations of NMR, and identifying significant peak variations between NMR for rapid metabolite profiling.
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Poster B-8
The BioMAZE System: an environment for representation and analysis of biological processes.
Christian LEMER (Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Br);
Hassan ANHEROUR (Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Br);
Fabian COUCHE (Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Br);
Simon DE KEYZER (Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Br);
Yves DEVILLE (Computing Science and Engineering Department, Université catholique de Louvain, Place Saint-Barbe 2,);
Frederic FAYS (Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Br);
Olivier HUBAUT (Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Br);
Jacques VAN HELDEN (Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Br);
Shoshana J. WODAK (Department of Biochemistry and Structural Biology, Department of Medical Genetics, University of Tor);
Short Abstract: The BioMAZE System is a workbench for the representation and analysis of networks of molecular interactions and cellular processes, genetic expression and regulation, enzymatic transformations and regulation, metabolic pathways, signal transduction. The BioMAZE system integrates the aMAZE database and various tools for analyzing and visualizing the stored information.
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Poster B-9
MiDaR: Microarray Database Resource for Customized Chip Design
Eric C. Rouchka (Department of Computer Engineering and Computer Science, University of Louisville);
Ravishrikanth Gundlapalli (Department of Computer Engineering and Computer Science, University of Louisville);
Nigel G.F. Cooper (Deparment of Anatomical Sciences and Neurobiology, University of Louisville);
Short Abstract: Often it is desirable to design a customized microarray chip for a subset of genes or a particular organism of interest. We have created a solution, MiDaR (Microarray Database Resource), to aid in the process of creating and storing custom microarrays based on gene information and GO annotations.
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Poster B-10
PhenoLink - Linking phenotype to genotype
Pieter Neerincx (Laboratory of Bioinformatics, WUR);
Blaise Alako (Laboratory of Bioinformatics, WUR);
Jack Leunissen (Laboratory of Bioinformatics, WUR);
Short Abstract: PhenoLink Project
Linkage analysis studies provide genomic regions to narrow the search for genes involved in a certain trait. But there might still be dozens of candidate genes left after linkage analysis and screening all of them is a laborious task. The PhenoLink project provides a data-mining framework using mapping, co-expression and interaction data to rank candidate genes.
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Poster B-11
Implementation of a query processing model and view based data integration system
Myung-Eun Lim (Bioinformatics Team, Electronics and Telecommunications Research Institute);
Myung-Guen Chung (Bioinformatics Team, Electronics and Telecommunications Research Institute);
Yong-Ho Lee (Bioinformatics Team, Electronics and Telecommunications Research Institute);
Soo-jun Park (Bioinformatics Team, Electronics and Telecommunications Research Institute);
Short Abstract: We designed a query processing model to dispersed biological databases and implemented data integration system based on mediator-wrapper concept. To reduce the response time when extracting data from data source, we induced a kind of wrapper cache. By using them, we got a reasonable response time in extracting data.
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Poster B-12
Integr8 – Access to Complete Genomes and Proteomes
Manuela Pruess (EMBL Outstation - European Bioinformatics Institute (EBI));
Lawrence Bower (EMBL Outstation - European Bioinformatics Institute (EBI));
Paul Kersey (EMBL Outstation - European Bioinformatics Institute (EBI));
Rajesh Radhakrishnan (EMBL Outstation - European Bioinformatics Institute (EBI));
Rolf Apweiler (EMBL Outstation - European Bioinformatics Institute (EBI));
Short Abstract: Integr8 is a web portal for exploring the biology of organisms with completely deciphered genomes. For 250 species, Integr8 provides access to general information, publications, and a statistical overview of the genome and proteome of the organism constructed using data resources such as UniProtKB, GenomeReviews, IPI, InterPro, CluSTr and GOA.
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Poster B-13
Development of Data Templates for Data Collection, Storage and Database Submission.
Miguel Anducho (Crop Research Informatics Laboratory, CIMMYT.);
Kyle Braak (Crop Research Informatics Laboratory, CIMMYT.);
Richard Bruskiewich (Crop Research Informatics Laboratory, IRRI.);
Victoria Carollo (Center for Computational Biology, Montana State University.);
Tom Hazekamp (International Plant Genetic Resources Institute.);
Andrew Farmer (National Center for Genomic Resources.);
David Marshall (Scottish Crop Research Center.);
Dave Matthews (GrainGenes, Cornell University.);
Ayton Meintjes (Bioinformatics and Computational Biology Unit, University of Pretoria.);
Thomas Metz (Crop Research Informatics Laboratory, IRRI.);
Jane Morris (African Centre for Gene Technologies.);
Manuel Ruiz (TropDB, CIRAD.);
Mary Schaeffer (MaizeGDB, University of Missouri.);
Theo van Hintum (Centre for Genetic Resources, The Netherlands.);
Susan McCouch (Gramene, Cornell University.);
Guy Davenport (Crop Research Informatics Laboratory, CIMMYT.);
Short Abstract: A large amount of data is generated each year that needs to be made accessible to the scientific community. We have developed database submission templates that define the format of the data and provide sufficient information to allow scientists capture the data, metadata and available controls.
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Poster B-14
Contextual Analysis and Visualization of High Throughput Experimental Data
Nenad Bartonicek (Bioinformatics Group, Faculty of Science, Zagreb University, Horvatovac 102a, 10000 Zagreb, Croatia.);
Igor Segota (Department of Physics, Faculty of Science, Zagreb University, Bijenička cesta 32, 10000 Zagreb,);
Kristian Vlahovicek (Bioinformatics Group, Faculty of Science, Zagreb University, Horvatovac 102a, 10000 Zagreb, Croatia.);
Short Abstract: MADNet (MicroArray Database Network) is a user-friendly data mining tool for rapid analysis of diverse biological data such as microarray, phage display or even metagenomes. It presents biological information in the context of metabolic and signaling pathways, gene orthologs, transcription factors and drugs through minimal user input.
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Poster B-15
Patho-Gene and Pathos Databases – Support for Biodefense and Emerging Infectious Disease Research
Elizabeth M. Glass (Argonne National Laboratory);
Mark D’Souza (University of Chicago);
Alexis Rodriguez (Argonne National Laboratory);
Dinanath Sulakhe (University of Chicago);
Mustafa Syed (Argonne National Laboratory);
Natalia Maltsev (Argonne National Laboratory);
Short Abstract: Presentation describes an interactive, integrated, bioinformatics environment to support biodefense and emerging infectious disease research. This environment has two components, PathoGene, a database of pathogenic factors that provides a knowledgebase for analysis of pathogenic organisms and Pathos. Pathos provides an integrated bioinformatics environment for analysis of genomes of pathogenic bacteria.
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Poster B-18
The TIGR Rice Genome Annotation Database
Shu Ouyang (The Institute for Genomic Research);
Haining Lin (The Institute for Genomic Research);
Kevin L. Childs (The Institute for Genomic Research);
Wei Zhu (The Institute for Genomic Research);
John Hamilton (The Institute for Genomic Research);
Dan Lee (The Institute for Genomic Research);
Mathew Campbell (The Institute for Genomic Research);
Renae Malek (The Institute for Genomic Research);
Li Zheng (The Institute for Genomic Research);
Joshua Orvis (The Institute for Genomic Research);
Brian Haas (The Institute for Genomic Research);
Jennifer Wortman (The Institute for Genomic Research);
Robin Buell (The Institute for Genomic Research);
Short Abstract: We have been funded to annotate the rice genome. Our Osa1 database contains pseudomolecules representing the 12 rice chromosomes. Ab initio gene finders, full length cDNA, EST and protein evidence were used to generate gene models and functional assignments for those models. The annotation is available http://rice.tigr.org.
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Poster B-19
APID: Agile Protein Interaction DataAnalyzer
Prieto C. (Cancer Research Center (CIC, CSIC/USAL));
De Las Rivas J. (Cancer Research Center (CIC, CSIC/USAL));
Short Abstract: Nowadays the assessment of the reliability and broader coverage of the interactome network are two of the main research areas in protein interactions. With these purposes APID (http://bioinfow.dep.usal.es/apid/) has been developed to analyze and integrate in a comparative web platform all the currently known data about protein-protein interactions.
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Poster B-20
The PIRSF system for protein classification, rule-based annotation, and ontology mapping
Darren A. Natale (PIR/GUMC);
Cecilia Arighi (PIR/GUMC);
Winona Barker (PIR/GUMC);
Zhangzhi Hu (PIR/GUMC);
Hongzhan Huang (PIR/GUMC);
Robel Kahsay (PIR/GUMC);
Raja Mazumder (PIR/GUMC);
Anastasia Nikolskaya (PIR/GUMC);
Sona Vasudevan (PIR/GUMC);
C. R. Vinayaka (PIR/GUMC);
Lai-Su Yeh (PIR/GUMC);
Cathy H. Wu (PIR/GUMC);
Short Abstract: PIRSF are a set of curated, hierarchical, whole protein families that form the basis for automated, rule-based annotation of individual proteins and for connecting various ontologies to protein entities.
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Poster B-21
INOH pathway data ontologies
Ken FUKUDA (CBRC, AIST);
Satoko YAMAMOTO (BIRD, JST);
Noriko SAKAI (BIRD, JST);
Hiromi NAKAMURA (Information and Mathematical Science Laboratory, Inc.);
Toshihisa TAKAGI (Graduate School of Frontier Sciences, University of Tokyo);
Short Abstract: INOH is a manually curated database of signal transduction pathways. While conventional pathway data are highly structured, they use open vocabularies to annotate their pathway components. To resolve the problem of data integration or mapping between data from different sources, INOH pathway objects are annotated by our pathway annotation ontologies.
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Poster B-22
Online dynamic visualization and statistical analyses of rat phenome data
Anne E Kwitek (Medical College of Wisconsin);
Zhanchi Wang (Medical College of Wisconsin);
Allen W. Cowley Jr. (Medical College of Wisconsin);
Andrew S. Greene (Medical College of Wisconsin);
Richard J. Roman (Medical College of Wisconsin);
Howard J. Jacob (Medical College of Wisconsin);
Short Abstract: PhysGen has generated and characterized over 200 phenotypes in two panels of rat chromosome substitution strains. All data is released to the public via our website (http://pga.mcw.edu). To facilitate more streamlined mining of the PhysGen data, we have developed flexible and dynamic visualization tools, with linked online statistical analysis.
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Poster B-23
A cell type transcriptional atlas database for rice
Matthew Holford (Yale University);
Teresa Ceserani (Yale University);
Mei Chen (Yale University);
Neeru Gandotra (Yale University);
Yuling Jiao (Yale University);
Naixin Li (Yale University);
Tie Liu (Yale University);
Ligeng Ma (Yale University);
Ning Sun (Yale University);
Susan Tausta (Yale University);
Xing-Wang Deng (Yale University);
Hongyu Zhao (Yale University);
Timothy Nelson (Yale University);
Short Abstract: We have constructed a transcriptional atlas database for rice using cells isolated by laser microdissection to facilitate the comparison of data between differing cell types. This database backs a web application that offers a variety of views to browse the data and analyze it within the context of biological pathways.
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Poster B-24
WebLab: a workflow-based platform integrating bioinformatics resources
Jianmin Wu (Center of Bioinformatics, Peking University, Beijing 100871, China);
Ge Gao (Center of Bioinformatics, Peking University, Beijing 100871, China);
Xiaoqiao Liu (Center of Bioinformatics, Peking University, Beijing 100871, China);
Lei Kong (Center of Bioinformatics, Peking University, Beijing 100871, China);
Zhe Li (Center of Bioinformatics, Peking University, Beijing 100871, China);
Di Liu (Center of Bioinformatics, Peking University, Beijing 100871, China);
Wen Tang (Center of Bioinformatics, Peking University, Beijing 100871, China);
Jingchu Luo (Center of Bioinformatics, Peking University, Beijing 100871, China);
Short Abstract: We developed a bioinformatics platform WebLab integrating various sequence analysis tools. WebLab was designed biological end-users with a single and simple Web interface which allows users to input sequence data and manage analysis results. WebLab can also be used by bioinformaticians as a workflow-based system for further development.
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Poster B-25
eSLDB: eukaryotic Subcellular Localization DataBase.
Andrea Pierleoni (Biocomputing Group, Department of Biology, University of Bologna);
Pier Luigi Martelli (Biocomputing Group, Department of Biology, University of Bologna);
Piero Fariselli (Biocomputing Group, Department of Biology, University of Bologna);
Rita Casadio (Biocomputing Group, Department of Biology, University of Bologna);
Short Abstract: eESLB is the first database of eukaryotic proteomes fully annotated for subcellular localization, containing experimental annotations derived from primary protein databases, homology based annotations and computational predictions. In its first release, the database contains subcellular annotations of proteins from five entire eukaryotic proteomes. eSLDB is publicly available at http://gpcr.biocomp.unibo.it/esldb/.
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Poster B-26
NUDLE: A Tool for Inferring Nutrient Disease Relationships from Metabolic Networks
Anoop Kumar ( Department of Computer Science, Tufts University, Medford, MA, USA);
Jennifer S. Buell (Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA);
Lenore J. Cowen ( Department of Computer Science, Tufts University, Medford, MA, USA);
Inga Peter ( Institute for Clinical Research and Health Policy Studies, Tufts-New England Medical Center, Boston);
Short Abstract: We have developed NUtrient-Disease Link Estimator (NUDLE), a tool that infers nutrient disease relationships using data from metabolic, genomic and disease databases. It constructs metabolic networks and allows the inference of relationships between genes, diseases and nutrients from distance properties within the networks.
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Poster B-27
Development of Computational Tools for a Dynamic Association between Genomic and Proteomic Data and Metabolic Pathways
Renato Milani (Department of Biochemistry - Unicamp);
Itaraju J. B. Brum (Department of Biochemistry - Unicamp);
Anderson R. Martins (Alellyx Applied Genomics);
Eduardo Galembeck (Department of Biochemistry - Unicamp);
Short Abstract: This project aimed to build tools for an easier association of proteomics and genomics information with metabolic pathways. GenPath and ECPath, unlike the currently available tools, offer the possibility to customize the data source analyzed, free from the pre-defined maps based on data present in metabolic pathways databases.
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Poster B-28
A Computational Pipeline for the Analysis of Data from a 500,000 SNP Whole Genome Association Study of Multiple Sclerosis
David Sexton (Center for Human Genetics Research, Vanderbilt University, International Multiple Sclerosis Genetics);
Jacob McCauley (Center for Human Genetics Research, Vanderbilt University, International Multiple Sclerosis Genetics);
Justin Giles (Center for Human Genetics Research, Vanderbilt University, International Multiple Sclerosis Genetics);
Yuki Bradford (Center for Human Genetics Research, Vanderbilt University, International Multiple Sclerosis Genetics);
Jonathan Haines (Center for Human Genetics Research, Vanderbilt University, International Multiple Sclerosis Genetics);
Short Abstract: The International Multiple Sclerosis Genetics Consortium (IMSGC) has undertaken a whole genome association study for regions with association to multiple sclerosis phenotypes. This study consists of genotyping 500,000 SNPs in 1000 affected family trios. New methods were developed to automatically upload, quality control, analyze, and report this data.
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Poster B-29
UniHI: Unifying Large-Scale Maps of the Human Protein Interactome
Gautam Chaurasia (Max-Delbrück-Centrum);
Christian Hänig (Max-Delbrück-Centrum);
Hanspeter Herzel (Institute for Theoretical Biology);
Erich Wanker (Max-Delbrück-Centrum);
Matthias E. Futschik (Institute for Theoretical Biology);
Short Abstract: We present here a web-based database called UniHI (Unified Human Interactome) which aims to integrate available protein interaction maps. It is currently based on 10 interaction maps including over 16000 unique proteins and 150000 distinct interactions in total. UniHI offers researchers a direct entry gate into the human interactome.
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Poster B-30
Prediction from complex bioinformatic databases, with application to protein--protein interactions
Berzuini Carlo (MRC BSU);
Tom M.W. Nye (MRC BSU);
Sarah A. Teichmann (MRC LMB);
Short Abstract: We consider
predictions based on a synthesis of information from a
heterogeneous collection of databases. Our method involves a
weighted combination of predictive distributions generated by each
individual database, where each weight measures the independent
predictive contribution of the corresponding database. We apply the methodology to predict
domain--domain contacts within a given multimeric protein complex, by
synthesizing information from a database of atomic-level,
three--dimensional, multimer structures and from rather crude,
genome--wide, experiments
indicating which pairs of proteins have potential to multimerise.
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Poster B-31
MS-PED: A Management System for Proteomics Experimental Data
W. Yan (Bioinformatics User Facility, University of California, Los Angeles, CA);
S. Than (School of Dentistry, University of California, Los Angeles, CA);
R. Qiao (School of Medicine, University of Southern California, Los Angeles, CA);
D.S. Parker (Department of Computer Science, University of California, Los Angeles, CA);
D. Wong (School of Dentistry, University of California, Los Angeles, CA);
Short Abstract: MS-PED: A Management System for Proteomics Experimental Data
W. Yan1, S. Than2, R. Qiao3, D.S. Parker4, D. Wong2 1Bioinformatics User Facility, 4Department of Computer Science, and 2School of Dentistry, University of California, Los Angeles, CA; 3School of Medicine, University of Southern California, Los Angeles, CA.
MS-PED is a web-based management system for proteomics experimental data. It differs from existing platforms in handling both bottom-up and top-down proteomics experimental data, its support for a PEDRo-like level of information detail, its integration of tools with the database, its portable web-based design, and its commitment to open-source availability.
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Poster B-32
A Classification for Conceptually Layouting Protein-Protein Interaction Networks
SunLee Bang (Electronics & Telecommunications Research Institute);
JaeHun Choi (Electronics & Telecommunications Research Institute);
JongMin Park (Electronics & Telecommunications Research Institute);
SooJun Park (Electronics & Telecommunications Research Institute);
Short Abstract: To better understand interactions and protein function in the protein-protein interactions network, we nearly layout the proteins that do same function with keeping physical structure using annotated information of the protein. With this method, we can conceptually analyze the network and visualize it faster than existing graph drawing algorithms
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Poster B-33
STING Database Quality Assessment
Stanley R. M. Oliveira (Embrapa Agricultural Informatics);
Paula R. K. Falcão (Embrapa Agricultural Informatics);
Michel E. B.Yamagishi (Embrapa Agricultural Informatics);
Goran Neshich (Embrapa Agricultural Informatics);
Diego N. Rodrigues (Embrapa Agricultural Informatics);
Kassyus R. R. Souza (Embrapa Agricultural Informatics);
Douglas U. Morita (Embrapa Agricultural Informatics);
Gustavo V. Almeida (Embrapa Agricultural Informatics);
Ivan Mazoni (Embrapa Agricultural Informatics);
Edgard H. Santos (Embrapa Agricultural Informatics);
Fábio D. Vieira (Embrapa Agricultural Informatics);
José G. Jardine (Embrapa Agricultural Informatics);
Short Abstract: Inaccurate or inconsistent data can hinder our ability to interpret the research results. An effective data quality strategy can help the research to better handle its scientific objective, reducing costly operational inefficiencies. Here we present the results of our effort to access the quality of data in STING Database.
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Poster B-34
A computational system to select candidate genes for complex human traits
Kyle J Gaulton (Department of Genetics, University of North Carolina);
Karen L Mohlke (Department of Genetics, University of North Carolina);
Todd J Vision (Department of Biology, University of North Carolina);
Short Abstract: A wealth of genomic data exists that can be mined to uncover functionally relevant links between genes and traits. We developed a computational system, named CAESAR, which exploits these resources by combining text mining, data mining and data integration to prioritize potential candidate genes for complex human traits.
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Poster B-35
FlagelLink – An integrated organellar database dealing with refined pattern recognition of specific motifs/domains targeted to the eukaryotic flagellum
Fabiana Freire de Araújo (NUGEN-UECE);
Wesley Jefferson Oliveira Alcoforado (NUGEN-UECE);
João David de Lira (NUGEN-UECE);
Dácio Barros Tavares (NUGEN-UECE);
Ana Luiza Bessa de Paula Barros (LARCES-UECE);
Diana Magalhães de Oliveira (NUGEN-UECE);
Short Abstract: In order to provide a convenient bioinformatics resource covering available information about the flagellum (an organelle of intriguing motile features), an integrated relational database has been created. FlagelLink (http://nugen.lcc.uece.br/lpgate/?p=flagdb) gives this first insight on compiling the modularity of flagellar genes/proteins for allowing further analyses.
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Poster B-36
XMLPipeDB: A Reusable, Open Source Tool Chain for Building Relational Databases from XML Sources
Kam D. Dahlquist (Loyola Marymount University);
Joey Barrett (Loyola Marymount University);
Joe Boyle (Loyola Marymount University);
Adam Carasso (Loyola Marymount University);
David Hoffman (Loyola Marymount University);
Babak Naffas (Loyola Marymount University);
Jeffrey Nicholas (Loyola Marymount University);
Roberto Ruiz (Loyola Marymount University);
Scott Spicer (Loyola Marymount University);
John David N. Dionisio (Loyola Marymount University);
Short Abstract: XMLPipeDB is an open source suite of Java-based tools for automatically building relational databases from an XML schema (XSD). XMLPipeDB can be used for the management of biological data from different sources. We have used it to generate GenMAPP Gene Databases containing UniProt and Gene Ontology data for Escherichia coli and other bacterial species.
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Poster B-37
InterProScan New and Planned Features
Sarah Hunter (European Bioinformatics Institute);
Nicola Mulder (European Bioinformatics Institute);
Alberto Labarga (European Bioinformatics Institute);
Short Abstract: InterProScan is arguably the best-known tool for predicting protein functional annotation. It is a perl-based software package which wraps search algorithms for 10 protein signature databases and 4 other programs. This poster describes the architecture of the software, together with new and up-and-coming features.
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Poster B-38
Novel "shim" Service to Develop Fexible Workflows with Web Services
Toshiaki Katayama (University of Tokyo);
Minoru Kanehisa (Kyoto University);
Short Abstract: It is difficult to develop flexible pipelines for biological analysis only by the methods currently available in the public web services. We developed a new web service containing a collection of "shim" services to process various data types especially for the integration with the KEGG API.
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Poster B-39
Automating the Maintenance of Bioinformatics Services with Aap
Estienne Swart (National Bioinformatics Network (South Africa));
Ruediger Brauning (National Bioinformatics Network (South Africa));
Short Abstract: Bioinformatics Services are complex systems that require a significant amount of effort to maintain. Much of this burden can be eased by using a unified framework for concise, declarative specification and flexible, imperative scripting. For our purposes we employed a generic build system, Aap (http://www.a-a-p.org).
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Poster B-40
Middleware approach to data integration for plant genomics
Pierre Larmande (Phd Student);
Isabelle Mougenot (Assitant Professor);
Christine Tranchant-Dubreuil (Ingineer);
Manuel Ruiz (Phd);
Therese Libourel (Professor);
Short Abstract: Plant functional genomics requires efficient integration and processing of related information. The difficulty lies in the integration of this information, often semantically inconsistent or expressing different viewpoints, and, very often, only available in heterogenous formats.
We present a distributed integrated environment that permits interoperability between different data sources.
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Poster B-41
Context-sensitive Evidence Integration for Predicting Biological Networks
Chad L. Myers (Lewis-Sigler Institute for Integrative Genomics, Department of Computer Science);
Olga G. Troyanskaya (Lewis-Sigler Institute for Integrative Genomics, Department of Computer Science);
Short Abstract: We developed a general probabilistic system for context-sensitive discovery of biological networks from diverse genomic data. We measure significant variation in relevance of common experimental technologies across biological processes, and exploit this information to improve prediction accuracy. Using our approach, we predicted and experimentally confirmed novel network behavior for S. cerevisiae.
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Poster B-42
Evidence handling in EMBL Third Party Annotation: a two-tiered structure.
Cochrane G.R. (EMBL-EBI);
Bates K. (EMBL-EBI);
Faruque N. (EMBL-EBI);
Kanz C. (EMBL-EBI);
Kulikova T. (EMBL-EBI);
Zhu W. (EMBL-EBI);
Apweiler R (EMBL-EBI);
Short Abstract: The EMBL Third Party Annotation database (EMBL TPA) recruits and presents peer-reviewed annotation and re-annotation of primary nucleotide sequence available in the public nucleotide sequence databases and trace archives. A recent broadening of scope of EMBL TPA increases coverage to include submitted annotation derived from non-experimental and indirect experimental evidence.
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Poster B-44
An Integrated database of structural parameters for protein analysis
Stanley R. M. Oliveira (Embrapa Agricultural Informatics);
Gustavo V. Almeida (Embrapa Agricultural Informatics);
Kassyus R. R. Souza (Embrapa Agricultural Informatics);
Diego N. Rodrigues (Embrapa Agricultural Informatics);
Goran Neshich (Embrapa Agricultural Informatics);
Paula R. Kuser-Falcão (Embrapa Agricultural Informatics);
Michel E. B.Yamagishi (Embrapa Agricultural Informatics);
Edgard H. Santos (Embrapa Agricultural Informatics);
Fábio D. Vieira (Embrapa Agricultural Informatics);
José G. Jardine (Embrapa Agricultural Informatics);
Short Abstract: STING_DB is a relational database composed of structural parameters for protein analysis operating with a collection of both publicly available data (PDB, HSSP, Prosite) and its own data (contacts, interface contacts, surface accessibility). STING_DB has over 300 parameters compiled at the single site and was implemented using free software.
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Poster B-45
Digr: A web interface for mining Digrabase graph databases
Kieran O'Neill (National Bioinformatics Network);
Dan Jacobson (National Bioinformatics Network);
Hugh Murrell (University of KwaZulu-Natal);
Short Abstract: Digr is an extensible, platform independent, free open source interface to the
graph mining functionality of DigraBase. Digr facilitates the finding of
co-annotations of objects of interest to ontology terms. It has been
applied to a molecular mammalian health model, and an endangered species
tissue bank sample tracking system.
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Poster B-46
GEMINA: Genomic Metadata for Infectious Agents
Aaron Gussman (The Institute for Genomic Research, Rockville, Maryland 20850, USA.);
Sam Angiuoli (The Institute for Genomic Research, Rockville, Maryland 20850, USA.);
Lynn M. Schriml (The Institute for Genomic Research, Rockville, Maryland 20850, USA.The Institute for Genomic Researc);
Kumar Hari (Ibis Division of Isis Pharmaceuticals, 1891 Rutherford Rd., Carlsbad, CA 92008, USA.);
Alan Goates (Ibis Division of Isis Pharmaceuticals, 1891 Rutherford Rd., Carlsbad, CA 92008, USA.);
Kathy Phillippy (The Institute for Genomic Research, Rockville, Maryland 20850, USA.);
Tanja Davidsen (The Institute for Genomic Research, Rockville, Maryland 20850, USA.);
Anu Ganapathy (The Institute for Genomic Research, Rockville, Maryland 20850, USA.);
Steven Salzberg (Center for Bioinformatics and Computational Biology, University of Maryland Institute for Advanced C);
Owen White (The Institute for Genomic Research, Rockville, Maryland 20850, USA.);
Neil Hall (The Institute for Genomic Research, Rockville, Maryland 20850, USA.);
Short Abstract: The Gemina (Genomic Metadata for Infectious Agents) system, developed at TIGR, integrates pathogen and epidemiological information with genomic sequence and annotation data. It enables the identification of microbial pathogen species based on their epidemiology and pathogenesis, and supports the development of nucleotide signature-based assays for the detection of pathogens.
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Poster B-47
A Web-based Workbench for Conducting "In-Silico" Experiments Using Microarray Data
Cheryl Hornbaker (Department of Pharmacology, University of Colorado Health Sciences Center);
Lawrence Hunter (Department of Pharmacology, University of Colorado Health Sciences Center);
Tzu Phang (Department of Pharmacology, University of Colorado Health Sciences Center);
Sanjiv Bhave (Department of Pharmacology, University of Colorado Health Sciences Center);
Ravan Lapadat (Department of Pharmacology, University of Colorado Health Sciences Center);
Laura Saba (Department of Pharmacology, University of Colorado Health Sciences Center);
Jeanette Gaydos (Department of Pharmacology, University of Colorado Health Sciences Center);
Daniel McGoldrick (Department of Pharmacology, University of Colorado Health Sciences Center);
Andrew Dolbey (Department of Pharmacology, University of Colorado Health Sciences Center);
Brian Soriano (Department of Pharmacology, University of Colorado Health Sciences Center);
John Belnap (Behavioral Neuroscience, Oregon Health & Science University);
Aaron Gabow (Department of Pharmacology, University of Colorado Health Sciences Center);
Allison Ellington (Department of Pharmacology, University of Colorado Health Sciences Center);
Eric Ellington (Department of Pharmacology, University of Colorado Health Sciences Center);
Kendra Jones (Department of Pharmacology, University of Colorado Health Sciences Center);
Paula Hoffman (Department of Pharmacology, University of Colorado Health Sciences Center);
Boris Tabakoff (Department of Pharmacology, University of Colorado Health Sciences Center);
Short Abstract: The Colorado INIA Informatics website offers a suite of tools for sharing, analyzing, and interpreting microarray experiment data for worldwide collaborative research. The website allows users to combine gene expression data from an assortment of previously uploaded MIAME-compliant experiments to test novel hypotheses regarding gene expression and complex behaviors.
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Poster B-48
SOAP-based services provided by the European Bioinformatics Institute
Alberto Labarga (European Bioinformatics Institute - EMBL);
S. PIlai (European Bioinformatics Institute - EMBL);
M. Anderson (European Bioinformatics Institute - EMBL);
F. Valentin (European Bioinformatics Institute - EMBL);
H. McWilliam (European Bioinformatics Institute - EMBL);
P. Stoehr (European Bioinformatics Institute - EMBL);
K. Henrick (European Bioinformatics Institute - EMBL);
P. Rice (European Bioinformatics Institute - EMBL);
R. Lopez (European Bioinformatics Institute - EMBL);
Short Abstract: SOAP based Web Services has gained much attention as an open standard enabling interoperability among applications. The European Bioinformatics Institute (EBI) is using this technology to provide robust data retrieval and data analysis mechanisms to the scientific community and to enhance utilization of the biological resources it already provides.
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Poster B-49
BISI: an integrative, extensible and minable database of South African wildlife and indigenous livestock biomaterial information
Athlee Maclear (National Bioinformatics Network);
Darren Otgaar (National Bioinformatics Network);
Dr. Junaid Gamieldien (National Bioinformatics Network);
Dr. Paul Bartels (National Zoological Gardens/BioBankSA);
Dan Jacobson (National Bioinformatics Network);
Dr. Antoinette Kotze (Nationa
