%0 Journal Article %1 Baitaluk:2010:Bioinformatics:20427517 %A Baitaluk, M %A Ponomarenko, J %D 2010 %J Bioinformatics %K dataintegration %R 10.1093/bioinformatics/btq231 %T Semantic Integration of Data on Transcriptional Regulation %U http://www.ncbi.nlm.nih.gov/pubmed/20427517?dopt=Abstract %X 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 paper. 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.org.

@article{Baitaluk:2010:Bioinformatics:20427517, 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 paper. 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.org.}, added-at = {2010-05-06T00:15:21.000+0200}, author = {Baitaluk, M and Ponomarenko, J}, biburl = {https://www.bibsonomy.org/bibtex/2a063c43d81b75406c1a9bd7feca83fc5/wnpxrz}, description = {Semantic Integration of Data on Transcriptional Re... [Bioinformatics. 2010] - PubMed result}, doi = {10.1093/bioinformatics/btq231}, interhash = {4fc988fe56daf82759d554c8393cbf38}, intrahash = {a063c43d81b75406c1a9bd7feca83fc5}, journal = {Bioinformatics}, keywords = {dataintegration}, month = apr, pmid = {20427517}, timestamp = {2010-05-06T00:15:21.000+0200}, title = {Semantic Integration of Data on Transcriptional Regulation}, url = {http://www.ncbi.nlm.nih.gov/pubmed/20427517?dopt=Abstract}, year = 2010 }