Ontology highlight
ABSTRACT: Motivation
Experimental and predicted data concerning gene transcriptional regulation are distributed among many heterogeneous sources. However, there are no resources to integrate these data automatically or to provide a 'one-stop shop' experience for users seeking information essential for deciphering and modeling gene regulatory networks.Results
IntegromeDB, a semantic graph-based 'deep-web' data integration system that automatically captures, integrates and manages publicly available data concerning transcriptional regulation, as well as other relevant biological information, is proposed in this article. The problems associated with data integration are addressed by ontology-driven data mapping, multiple data annotation and heterogeneous data querying, also enabling integration of the user's data. IntegromeDB integrates over 100 experimental and computational data sources relating to genomics, transcriptomics, genetics, and functional and interaction data concerning gene transcriptional regulation in eukaryotes and prokaryotes.Availability
IntegromeDB is accessible through the integrated research environment BiologicalNetworks at http://www.BiologicalNetworks.orgContact
baitaluk@sdsc.eduSupplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Baitaluk M
PROVIDER: S-EPMC2887046 | biostudies-literature | 2010 Jul
REPOSITORIES: biostudies-literature
Baitaluk Michael M Ponomarenko Julia J
Bioinformatics (Oxford, England) 20100428 13
<h4>Motivation</h4>Experimental and predicted data concerning gene transcriptional regulation are distributed among many heterogeneous sources. However, there are no resources to integrate these data automatically or to provide a 'one-stop shop' experience for users seeking information essential for deciphering and modeling gene regulatory networks.<h4>Results</h4>IntegromeDB, a semantic graph-based 'deep-web' data integration system that automatically captures, integrates and manages publicly a ...[more]