a biophysical model for analysis of transcription factor interaction and binding site arrangement from genome-wide binding data转录因子的生物物理模型分析从全基因组绑定数据交互和结合位点的安排.pdf

A Biophysical Model for Analysis of Transcription Factor Interaction and Binding Site Arrangement from Genome-Wide Binding Data 1 2 3 4 1 4 1,2,3 Xin He , Chieh-Chun Chen , Feng Hong , Fang Fang , Saurabh Sinha , Huck-Hui Ng , Sheng Zhong * 1 Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America, 2 Department of Bioengineering, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America, 3 Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America, 4 Gene Regulation Laboratory, Genome Institute of Singapore, Singapore, Singapore Abstract Background: How transcription factors (TFs) interact with cis-regulatory sequences and interact with each other is a fundamental, but not well understood, aspect of gene regulation. Methodology/Principal Findings: We present a computational method to address this question, relying on the established biophysical principles. This method, STAP (sequence to affinity prediction), takes into account all combinations and configurations of strong and weak binding sites to analyze large scale transcription factor (TF)-DNA binding data to discover cooperative interactions among TFs, infer sequence rules of interaction and predict TF target genes in new conditions with no TF-DNA binding data. The distinctions between STAP and other statistical approaches for analyzing cis-regulatory sequences include the utility of physical principles and the treatment of the DNA binding data as quantitative representation of bind