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PhysBinder: improving the prediction of transcription factor binding sites by flexible inclusion of biophysical properties
Author(s) -
Stefan Broos,
Arne Soete,
Bart Hooghe,
Raymond J. Moran,
Frans van Roy,
Pieter De Bleser
Publication year - 2013
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkt288
Subject(s) - in silico , biology , dna binding site , transcription factor , computational biology , binding site , dna , web site , dna sequencing , genetics , transcription (linguistics) , sequence (biology) , bioinformatics , computer science , data mining , promoter , gene , world wide web , the internet , linguistics , gene expression , philosophy
The most important mechanism in the regulation of transcription is the binding of a transcription factor (TF) to a DNA sequence called the TF binding site (TFBS). Most binding sites are short and degenerate, which makes predictions based on their primary sequence alone somewhat unreliable. We present a new web tool that implements a flexible and extensible algorithm for predicting TFBS. The algorithm makes use of both direct (the sequence) and several indirect readout features of protein-DNA complexes (biophysical properties such as bendability or the solvent-excluded surface of the DNA). This algorithm significantly outperforms state-of-the-art approaches for in silico identification of TFBS. Users can submit FASTA sequences for analysis in the PhysBinder integrative algorithm and choose from >60 different TF-binding models. The results of this analysis can be used to plan and steer wet-lab experiments. The PhysBinder web tool is freely available at http://bioit.dmbr.ugent.be/physbinder/index.php.

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