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Research Article
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Published Online: 5 July 2004

A Discriminative Framework for Detecting Remote Protein Homologies

Publication: Journal of Computational Biology
Volume 7, Issue Number 1-2

Abstract

A new method for detecting remote protein homologies is introduced and shown to perform well in classifying protein domains by SCOP superfamily. The method is a variant of support vector machines using a new kernel function. The kernel function is derived from a generative statistical model for a protein family, in this case a hidden Markov model. This general approach of combining generative models like HMMs with discriminative methods such as support vector machines may have applications in other areas of biosequence analysis as well.

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Published In

cover image Journal of Computational Biology
Journal of Computational Biology
Volume 7Issue Number 1-2February 2000
Pages: 95 - 114
PubMed: 10890390

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Published online: 5 July 2004
Published in print: February 2000

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Tommi Jaakkola
MIT Artificial Intelligence Laboratory, Cambridge, MA 02139.
Mark Diekhans
Department of Computer Science, University of California, Santa Cruz, CA 95064.
David Haussler
Department of Computer Science, University of California, Santa Cruz, CA 95064.

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