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Nucleic Acids Research Advance Access originally published online on November 7, 2006
Nucleic Acids Research 2007 35(Database issue):D732-D736; doi:10.1093/nar/gkl816
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Nucleic Acids Research, 2007, Vol. 35, Database issue D732-D736
© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Articles

KBERG: KnowledgeBase for Estrogen Responsive Genes

Suisheng Tang*, Zhuo Zhang, Sin Lam Tan, Man-Hung Eric Tang, Arun Prashanth Kumar, Suresh Kumar Ramadoss and Vladimir B. Bajic1

Institute for Infocomm Research, 21 Heng Mui Keng Terrace Singapore 119613 1 South African National Bioinformatics Institute, Private Bag X17 Bellville 7535, South Africa

*To whom correspondence should be addressed. Tel: +65 6874 8809; Fax: +65 6774 8056; Email: suisheng{at}i2r.a-star.edu.sg

Received August 14, 2006. Revised October 4, 2006. Accepted October 4, 2006.

Estrogen has a profound impact on human physiology affecting transcription of numerous genes. To decipher functional characteristics of estrogen responsive genes, we developed KnowledgeBase for Estrogen Responsive Genes (KBERG). Genes in KBERG were derived from Estrogen Responsive Gene Database (ERGDB) and were analyzed from multiple aspects. We explored the possible transcription regulation mechanism by capturing highly conserved promoter motifs across orthologous genes, using promoter regions that cover the range of [–1200, +500] relative to the transcription start sites. The motif detection is based on ab initio discovery of common cis-elements from the orthologous gene cluster from human, mouse and rat, thus reflecting a degree of promoter sequence preservation during evolution. The identified motifs are linked to transcription factor binding sites based on the TRANSFAC database. In addition, KBERG uses two established ontology systems, GO and eVOC, to associate genes with their function. Users may assess gene functionality through the description terms in GO. Alternatively, they can gain gene co-expression information through evidence from human EST libraries via eVOC. KBERG is a user-friendly system that provides links to other relevant resources such as ERGDB, UniGene, Entrez Gene, HomoloGene, GO, eVOC and GenBank, and thus offers a platform for functional exploration and potential annotation of genes responsive to estrogen. KBERG database can be accessed at http://research.i2r.a-star.edu.sg/kberg.


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