Title: "Detection and Refinement of Transcription Factor Binding Sites Using Hybrid Monte Carlo Method"
Speaker: Steve Qin, Department of Biostatistics, University of Michigan
Place: Physics (PHYS) 112; March 30, 2010, Tuesday, 4:30pm


Coupling chromatin immunoprecipitation (ChIP) with recently developed massively parallel sequencing technologies has enabled genome-wide detection of protein-DNA interactions with unprecedented sensitivity and specificity. In this study, we explore the value of using ChIP-Seq data to better detect and refine transcription factor binding sites (TFBS). We introduce a novel computational algorithm named Hybrid Motif Sampler (HMS), specifically designed for TFBS motif discovery in ChIP-Seq data. We also propose a more sophisticated model that allows intra-motif dependency to describe more accurately the underlying motif pattern. Simulation studies demonstrate favorable performance of HMS compared to other existing methods. When applying HMS to real ChIP-Seq datasets, we find that (i) the accuracy of existing TFBS motif patterns can be significantly improved and (ii) there is significant intra-motif dependency inside all the TFBS motifs we tested; modeling these dependencies further improves the accuracy of these TFBS motif patterns. Our finding potentially offers new biological insights into the mechanisms of transcription factor regulation.

Associated Reading:
Hu M, Yu J, Taylor, JMG, Chinnaiyan AM, Qin ZS. (2010) On the Detection and Refinement of Transcription Factor Binding Sites Using ChIP-Seq Data. Nucleic Acids Res. Jan 6. [Epub ahead of print].

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