Journal Article

HHsvm: fast and accurate classification of profile–profile matches identified by HHsearch

Mensur Dlakić

in Bioinformatics

Volume 25, issue 23, pages 3071-3076
Published in print December 2009 | ISSN: 1367-4803
Published online September 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp555
HHsvm: fast and accurate classification of profile–profile matches identified by HHsearch

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Motivation: Recently developed profile–profile methods rival structural comparisons in their ability to detect homology between distantly related proteins. Despite this tremendous progress, many genuine relationships between protein families cannot be recognized as comparisons of their profiles result in scores that are statistically insignificant.

Results: Using known evolutionary relationships among protein superfamilies in SCOP database, support vector machines were trained on four sets of discriminatory features derived from the output of HHsearch. Upon validation, it was shown that the automatic classification of all profile–profile matches was superior to fixed threshold-based annotation in terms of sensitivity and specificity. The effectiveness of this approach was demonstrated by annotating several domains of unknown function from the Pfam database.

Availability: Programs and scripts implementing the methods described in this manuscript are freely available from http://hhsvm.dlakiclab.org/.

Contact: mdlakic@montana.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  4838 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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