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A Novel Alignment-Free Method for Comparing Transcription Factor Binding Site Motifs
Author(s) -
Minli Xu,
Zhengchang Su
Publication year - 2010
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0008797
Subject(s) - computational biology , sequence motif , dna binding site , sequence alignment , motif (music) , binding site , transcription factor , multiple sequence alignment , structural motif , cluster analysis , consensus sequence , computer science , pattern recognition (psychology) , data mining , biology , artificial intelligence , genetics , promoter , dna , peptide sequence , base sequence , gene , physics , acoustics , biochemistry , gene expression
Background Transcription factor binding site (TFBS) motifs can be accurately represented by position frequency matrices (PFM) or other equivalent forms. We often need to compare TFBS motifs using their PFMs in order to search for similar motifs in a motif database, or cluster motifs according to their binding preference. The majority of current methods for motif comparison involve a similarity metric for column-to-column comparison and a method to find the optimal position alignment between the two compared motifs. In some applications, alignment-free methods might be preferred; however, few such methods with high accuracy have been described. Methodology/Principal Findings Here we describe a novel alignment-free method for quantifying the similarity of motifs using their PFMs by converting PFMs into k -mer vectors. The motifs could then be compared by measuring the similarity among their corresponding k -mer vectors. Conclusions/Significance We demonstrate that our method in general achieves similar performance or outperforms the existing methods for clustering motifs according to their binding preference and identifying similar motifs of transcription factors of the same family.

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