Mining discriminative distance context of transcription factor binding sites on ChIP enriched regions

Authors:
Hyunmin Kim;Katherina J. Kechris;Lawrence Hunter
Affiliations:
Center for Computational Pharmacology, University of Colorado Health Sciences Center, Aurora, CO;Department Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, CO;Center for Computational Pharmacology, University of Colorado Health Sciences Center, Aurora, CO
Venue:
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
Year:
2007

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Abstract

Genome-wide identification of transcription factor binding sites (TFBSs) is critical for understanding transcriptional regulation of the gene expression network. ChIP-chip experiments accelerate the procedure of mapping target TFBSs for diverse cellular conditions. We address the problem of discriminating potential TFBSs in ChIP-enriched regions from those of non ChIP-enriched regions using ensemble rule algorithms and a variety of predictive variables, including those based on sequence and chromosomal context. In addition, we developed an input variable based on a scoring scheme that reflects the distance context of surrounding putative TFBSs. Focusing on hepatocyte regulators, this novel feature improved the performance of identifying potential TFBSs, and the measured importance of the predictive variables was consistent with biological meanings. In summary, we found that distance-based features are better discriminators of ChIP-enriched TFBS over other features based on sequence or chromosomal context.