Title
An efficient algorithm for improving structure-based prediction of transcription factor binding sites.
Abstract
Gene expression is regulated by transcription factors binding to specific target DNA sites. Understanding how and where transcription factors bind at genome scale represents an essential step toward our understanding of gene regulation networks. Previously we developed a structure-based method for prediction of transcription factor binding sites using an integrative energy function that combines a knowledge-based multibody potential and two atomic energy terms. While the method performs well, it is not computationally efficient due to the exponential increase in the number of binding sequences to be evaluated for longer binding sites. In this paper, we present an efficient pentamer algorithm by splitting DNA binding sequences into overlapping fragments along with a simplified integrative energy function for transcription factor binding site prediction.A DNA binding sequence is split into overlapping pentamers (5 base pairs) for calculating transcription factor-pentamer interaction energy. To combine the results from overlapping pentamer scores, we developed two methods, Kmer-Sum and PWM (Position Weight Matrix) stacking, for full-length binding motif prediction. Our results show that both Kmer-Sum and PWM stacking in the new pentamer approach along with a simplified integrative energy function improved transcription factor binding site prediction accuracy and dramatically reduced computation time, especially for longer binding sites.Our new fragment-based pentamer algorithm and simplified energy function improve both efficiency and accuracy. To our knowledge, this is the first fragment-based method for structure-based transcription factor binding sites prediction.
Year
DOI
Venue
2017
10.1186/s12859-017-1755-0
BMC Bioinformatics
Keywords
Field
DocType
Binding motif,Fragment-based method,Integrative energy function,Pentamer,Structure-based prediction,Transcription factor binding site
Transcription (biology),Binding site,DNA binding site,Biology,Position weight matrix,Algorithm,Pentamer,Bioinformatics,Genetics,Base pair,Transcription factor,A-DNA
Journal
Volume
Issue
ISSN
18
1
1471-2105
Citations 
PageRank 
References 
1
0.38
7
Authors
2
Name
Order
Citations
PageRank
Alvin Farrel130.80
Juntao Guo2155.49