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



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



Bioinformatics 23(5): 634-636



This article 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-bindContact: IKuznetsov@albany.eduSupplementry information: http://lcg.rit.albany.edu/dp-bind/dpbind_supplement.html.

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Accession: 013236717

Download citation: RISBibTeXText

PMID: 17237068

DOI: 10.1093/bioinformatics/btl672



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