A Novel Information Contents Based Similarity Metric for Comparing TFBS Motifs

摘要：

　　Identifying binding sites recognized by transcription factors (TFs) is one of major challenges to decipher complex genetic regulatory networks encoded in a genome.A set of binding sites recognized by the same TF,called a motif,can be accurately represented by a position frequency matrix (PFM) or a position-specific scoring matrix (PSSM).Very often,we need to compare motifs when searching for similar motifs in a motif database for a query motif,or clustering motifs possibly recognized by the same TF.In this paper,we have designed a novel metric,called SPIC (Similarity between Positions with Information Contents),for quantifying the similarity between two motifs using their PFMs,PSSMs,and column information contents,and demonstrated that this metric outperforms the other state-of-the-art methods for clustering motifs of the same TF and differentiating motifs of different TFs.

关键词： transcription factor binding sites (TFBS) information contents motifs, regulatory networks similarity metric

作者: Shaoqiang Zhang Lifen Jiang Chuanbin Du Zhengchang Su

作者单位: College of Computer and Information EngineeringTianjin Normal University Tianjin 300387, China Department of Bioinformatics and Genomicsthe University of North Carolina at CharlotteCharlotte, NC

会议类型: 国际会议

会议名称: 6th International Conference on Systems Biology (第六届国际系统生物学会议)(ISB2012)

会议地点: 西安

会议语种:英文

页码: 32-36

在线出版日期: 2012-08-19（万方平台首次上网日期，不代表论文的发表时间）