CORE_TF: A user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated genes

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Abstract

Background: The identification of transcription factor binding sites is difficult since they are only a small number of nucleotides in size, resulting in large numbers of false positives and false negatives in current approaches. Computational methods to reduce false positives are to look for over-representation of transcription factor binding sites in a set of similarly regulated promoters or to look for conservation in orthologous promoter alignments. Results: 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. Conclusion: The program CORE_TF is accessible in a user friendly web interface at http://www.LGTC.nl/CORE_TF. 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. © 2008 Hestand et al; licensee BioMed Central Ltd.

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Hestand, M. S., Van Galen, M., Villerius, M. P., Van Ommen, G. J. B., den Dunnen, J. T., & ’t Hoen, P. A. C. (2008). CORE_TF: A user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated genes. BMC Bioinformatics, 9. https://doi.org/10.1186/1471-2105-9-495

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