Bioinformatics Advance Access originally published online on May 19, 2005
Bioinformatics 2005 21(15):3241-3247; doi:10.1093/bioinformatics/bti497
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Published by Oxford University Press 2005
Semi-supervised protein classification using cluster kernels
1NEC Research Institute 4 Independence Way, Princeton, NJ 08540, USA
2Center for Computational Learning Systems, Columbia University Interchuch Center, 475 Riverside Drive, Mail Code 7717, New York, NY 10115, USA
3Max-Planck Institute for Biological Cybernetics Spemannstraße 38, 72076 Tübingen, Gxermany
4Department of Genome Sciences, University of Washington 1705 NE Pacific Street, Seattle, WA 98195, USA
*To whom correspondence should be addressed.
Motivation: Building an accurate protein classification system depends critically upon choosing a good representation of the input sequences of amino acids. Recent work using string kernels for protein data has achieved state-of-the-art classification performance. However, such representations are based only on labeled data—examples with known 3D structures, organized into structural classes—whereas in practice, unlabeled data are far more plentiful.
Results: In this work, we develop simple and scalable cluster kernel techniques for incorporating unlabeled data into the representation of protein sequences. We show that our methods greatly improve the classification performance of string kernels and outperform standard approaches for using unlabeled data, such as adding close homologs of the positive examples to the training data. We achieve equal or superior performance to previously presented cluster kernel methods and at the same time achieving far greater computationalefficiency.
Availability: Source code is available at www.kyb.tuebingen.mpg.de/bs/people/weston/semiprot. The Spider matlab package is available at www.kyb.tuebingen.mpg.de/bs/people/spider
Contact: jasonw{at}nec-labs.com
Supplementary information: www.kyb.tuebingen.mpg.de/bs/people/weston/semiprot
Received on January 2, 2005; revised on April 26, 2005; accepted on May 12, 2005
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