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Bioinformatics 2007 23(7):859-865; doi:10.1093/bioinformatics/btm012
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Functional evaluation of domain–domain interactions and human protein interaction networks

Andreas Schlicker , Carola Huthmacher , Fidel Ramírez , Thomas Lengauer and Mario Albrecht *

Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany

*To whom correspondence should be addressed.


  Abstract

Motivation: Large amounts of protein and domain interaction data are being produced by experimental high-throughput techniques and computational approaches. To gain insight into the value of the provided data, we used our new similarity measure based on the Gene Ontology (GO) to evaluate the molecular functions and biological processes of interacting proteins or domains. The applied measure particularly addresses the frequent annotation of proteins or domains with multiple GO terms.

Results: Using our similarity measure, we compare predicted domain–domain and human protein–protein interactions with experimentally derived interactions. The results show that our similarity measure is of significant benefit in quality assessment and confidence ranking of domain and protein networks. We also derive useful confidence score thresholds for dividing domain interaction predictions into subsets of low and high confidence.

Contact: mario.albrecht{at}mpi-inf.mpg.de

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Dmitrij Frishman

Received on October 31, 2006; revised on December 23, 2006; accepted on January 14, 2007

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