title: Semantic integration of data on transcriptional regulation.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  IntegromeDB is accessible through the integrated research environment BiologicalNetworks at http://www.BiologicalNetworks.org
  
  
  BACKGROUND
  baitaluk@sdsc.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. baitaluk@sdsc.edu
authors.forename: Michael
authors.initials: M
authors.lastname: Baitaluk
authors.forename: Julia
authors.initials: J
authors.lastname: Ponomarenko
mesh_terms: D019295:Computational Biology / Q000379:methods*; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D014158:Transcription, Genetic