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Bioinformatics Advance Access published online on February 2, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl014
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received April 14, 2005
Revised January 9, 2006
Accepted January 20, 2006

Article

Predicting interactions in protein networks by completing defective cliques

Haiyuan Yu 1 *, Alberto Paccanaro 1 *, Valery Trifonov 1 *, and Mark Gerstein 1 *

1 Department of Molecular Biophysics and Biochemistry, 266 Whitney Avenue, Yale University, PO Box 208114, New Haven, CT 06520, USA

* To whom correspondence should be addressed.
Mark Gerstein, E-mail: Mark.Gerstein{at}yale.edu


  Abstract

Datasets obtained by large-scale, high-throughput methods for detecting protein-protein interactions typically suffer from a relatively high level of noise. We describe a novel method for improving the quality of these datasets by predicting missed protein-protein interactions, using only the topology of the protein interaction network observed by the large-scale experiment. The central idea of the method is to search the protein interaction network for defective cliques (nearly complete complexes of pair-wise interacting proteins), and predict the interactions that complete them. We formulate an algorithm for applying this method to large-scale networks, and show that in practice it is efficient and has good predictive performance. More information can be found on our website: http://topnet.gersteinlab.org/clique/.

*These authors contributed equally to this work.

Associate Editor: Thomas Lengauer


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