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Bioinformatics Advance Access published online on April 21, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn198
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© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Eukaryotic transcription factor binding sites – modeling and integrative search methods

Sridhar Hannenhalli

Penn Center for Bioinformatics and Department of Genetics, University of Pennsylvania, Philadelphia, USA

To whom correspondence should be addressed. Dr. Sridhar Hannenhalli, E-mail: sridharh{at}pcbi.upenn.edu


  Abstract

A comprehensive knowledge of transcription factor binding sites is important for a mechanistic understanding of transcriptional regulation as well as for inferring gene regulatory networks. Because the DNA motif recognized by a transcription factor is typically short and degenerate, computational approaches for identifying binding sites based only on the sequence motif inevitably suffer from high error rates. Current state-of-the-art techniques for improving computational identification of binding sites can be broadly categorized into two classes: (1) Approaches that aim to improve binding motif models by extracting maximal sequence information from experimentally determined binding sites and (2) Approaches that supplement binding motif models with additional genomic or other attributes (such as evolutionary conservation). In this review we will discuss recent attempts to improve computational identification of transcription factor binding sites through these two types of approaches and conclude with thoughts on future development.

Associate Editor: Dr. Jonathan Wren

Received on February 11, 2008; revised on April 18, 2008; accepted on April 18, 2008

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