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Advances in Bioinformatics
Volume 2008, Article ID 369830, 9 pages
http://dx.doi.org/10.1155/2008/369830
Research Article

Genomic Promoter Analysis Predicts Functional Transcription Factor Binding

1Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
2Department of Pathology & Laboratory Medicine and Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA

Received 31 January 2008; Revised 15 May 2008; Accepted 17 July 2008

Academic Editor: Ramana Davuluri

Copyright © 2008 J. Sunil Rao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background. The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology. Results. We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor binding site (CONFAC) software. CONFAC identified 16296 human-mouse ortholog gene pairs, and of those pairs, 9107 genes contained conserved TFBS in the 3 kb proximal promoter and first intron. To attempt to predict in vivo occupancy of transcription factor binding sites, we developed a novel marginal effect isolator algorithm that builds upon Bayesian methods for multigroup TFBS filtering and predicted the in vivo occupancy of two transcription factors with an overall accuracy of 84%. Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo.