Genomic Promoter Analysis Predicts Functional Transcription Factor Binding. (30th October 2008)

• Record Type: Journal Article
• Authors: Rao, J. Sunil; Karanam, Suresh; McCabe, Colleen D.; Moreno, Carlos S.
• Other Names: Davuluri Ramana Academic Editor.
• Is Part Of: Advances in bioinformatics. Volume 2008(2008)
• Publication Date: 2008-10-30
• Subjects: Bioinformatics -- Periodicals; Bioinformatics; Computational Biology -- Periodicals; Periodicals; 570.285
• DOI: 10.1155/2008/369830
• Languages: English
• ISSNs: 1687-8027

Abstract

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.