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Bioinformatics Advance Access published online on January 19, 2007
Bioinformatics, doi:10.1093/bioinformatics/btl672
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

DP-Bind: a web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins

Seungwoo Hwang {dagger}, Zhenkun Gou {dagger} and Igor B. Kuznetsov *

Gen*NY*Sis Center for Excellence in Cancer Genomics, Department of Epidemiology and Biostatistics, One Discovery Drive, University at Albany, Rensselaer, NY 12144, USA

* To whom correspondence should be addressed. Igor B. Kuznetsov, E-mail: IKuznetsov{at}albany.edu


  Abstract

Summary: This paper describes DP-Bind, a web server for predicting DNA-binding sites in a DNA-binding protein from its amino acid sequence. The web server implements three machine learning methods: support vector machine, kernel logistic regression, and penalized logistic regression. Prediction can be performed using either the input sequence alone or an automatically generated profile of evolutionary conservation of the input sequence in the form of PSI-BLAST position-specific scoring matrix (PSSM). PSSM-based kernel logistic regression achieves the accuracy of 77.2%, sensitivity of 76.4%, and specificity of 76.6%. The outputs of all three individual methods are combined into a consensus prediction to help identify positions predicted with high level of confidence.

Availability: Freely available at http://lcg.rit.albany.edu/dp-bind

Supplementary information: http://lcg.rit.albany.edu/dpbind/dpbind_supplement.html

{dagger} Joint first authors.

Associate Editor: Thomas Lengauer

Received on August 29, 2006; revised on November 16, 2006; accepted on January 3, 2007

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