| Literature DB >> 17237068 |
Seungwoo Hwang1, Zhenkun Gou, Igor B Kuznetsov.
Abstract
UNLABELLED: 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-bind. SUPPLEMENTARY INFORMATION: http://lcg.rit.albany.edu/dp-bind/dpbind_supplement.html.Entities:
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Year: 2007 PMID: 17237068 DOI: 10.1093/bioinformatics/btl672
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937