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  Semi-Supervised Protein Classification using Cluster Kernels

Weston, J., Leslie, C., Zhou, D., Elisseeff, A., & Noble, W. (2004). Semi-Supervised Protein Classification using Cluster Kernels. Advances in Neural Information Processing Systems 16, 595-602.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D8FD-C Version Permalink: http://hdl.handle.net/21.11116/0000-0005-5383-9
Genre: Conference Paper

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 Creators:
Weston, J1, 2, Author              
Leslie, C, Author
Zhou, D1, 2, Author              
Elisseeff, A1, 2, Author              
Noble, WS, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: A key issue in supervised protein classification is the representation of 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 --- while in practice, unlabeled data is far more plentiful. 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 while achieving far greater computational efficiency.

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 Dates: 2004-06
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2336
 Degree: -

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Title: Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2003-12-09 - 2003-12-11

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Title: Advances in Neural Information Processing Systems 16
Source Genre: Journal
 Creator(s):
Thrun, S, Editor
Saul, LK, Editor
Schölkopf, B1, Editor            
Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794            
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 595 - 602 Identifier: ISBN: 0-262-20152-6