%0 Journal Article
%T CORE_TF: a user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated genes
%A Matthew S Hestand
%A Michiel van Galen
%A Michel P Villerius
%A Gert-Jan B van Ommen
%A Johan T den Dunnen
%A Peter AC 't Hoen
%J BMC Bioinformatics
%D 2008
%I BioMed Central
%R 10.1186/1471-2105-9-495
%X We have developed a novel tool, "CORE_TF" (Conserved and Over-REpresented Transcription Factor binding sites) that identifies common transcription factor binding sites in promoters of co-regulated genes. To improve upon existing binding site predictions, the tool searches for position weight matrices from the TRANSFACR database that are over-represented in an experimental set compared to a random set of promoters and identifies cross-species conservation of the predicted transcription factor binding sites. The algorithm has been evaluated with expression and chromatin-immunoprecipitation on microarray data. We also implement and demonstrate the importance of matching the random set of promoters to the experimental promoters by GC content, which is a unique feature of our tool.The program CORE_TF is accessible in a user friendly web interface at http://www.LGTC.nl/CORE_TF webcite. It provides a table of over-represented transcription factor binding sites in the users input genes' promoters and a graphical view of evolutionary conserved transcription factor binding sites. In our test data sets it successfully predicts target transcription factors and their binding sites.There are both experimental and computational approaches to identify transcription factors (TF) and their relevant binding sites. In the wet lab, hypothesis driven techniques, such as deletion constructs with luciferase reporter assays and chromatin-immunoprecipitation on microarrays (ChIP-on-chip), can be used to identify TF binding site (TFBS) regions. Luciferase assays can prove that a specific region has regulatory function, but is laborious and time consuming. ChIP-on-chip is more global, but requires prior knowledge of which TF to target using a specific antibody and is laborious, time consuming, and expensive. Faster and cheaper in silico methods have been in development which can identify potential TF and their binding sites. They also tend to target more precise the TFBS instead of just contai
%U http://www.biomedcentral.com/1471-2105/9/495