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Bioinformatics Advance Access originally published online on November 10, 2006
Bioinformatics 2007 23(2):134-141; doi:10.1093/bioinformatics/btl565
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© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Predicting transcription factor affinities to DNA from a biophysical model

Helge G. Roider , Aditi Kanhere , Thomas Manke and Martin Vingron *

Max-Planck-Institute for Molecular Genetics Ihnestrasse 73, 14195 Berlin, Germany

*To whom correspondence should be addressed.


  Abstract

Motivation: Theoretical efforts to understand the regulation of gene expression are traditionally centered around the identification of transcription factor binding sites at specific DNA positions. More recently these efforts have been supplemented by experimental data for relative binding affinities of proteins to longer intergenic sequences. The question arises to what extent these two approaches converge. In this paper, we adopt a physical binding model to predict the relative binding affinity of a transcription factor for a given sequence.

Results: We find that a significant fraction of genome-wide binding data in yeast can be accounted for by simple count matrices and a physical model with only two parameters. We demonstrate that our approach is both conceptually and practically more powerful than traditional methods, which require selection of a cutoff. Our analysis yields biologically meaningful parameters, suitable for predicting relative binding affinities in the absence of experimental binding data.

Availability: The C source code for our TRAP program is freely available for non-commercial use at http://www.molgen.mpg.de/~manke/papers/TFaffinities/

Contact: vingron{at}molgen.mpg.de

Associate Editor: Chris Stoeckert

Received on October 1, 2006; revised on November 6, 2006; accepted on November 6, 2006

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