Nature Biotechnology
23, 951 - 959 (2005)
doi:10.1038/nbt1103
Probabilistic model of the human protein-protein interaction networkDaniel R Rhodes1, 2, 7, Scott A Tomlins2, 7, Sooryanarayana Varambally2, 7, Vasudeva Mahavisno2, Terrence Barrette2, Shanker Kalyana-Sundaram2, Debashis Ghosh3, Akhilesh Pandey6
& Arul M Chinnaiyan1, 2, 4, 51
Bioinformatics Program, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA. 2
Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA. 3
Department of Biostatistics, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA. 4
Department of Urology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA. 5
Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA. 6
Mc-Kusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University, Baltimore, Maryland 21205, USA. 7
These authors contributed equally to this work.
Correspondence should be addressed to Arul M Chinnaiyan arul@umich.edu A catalog of all human protein-protein interactions would provide scientists with a framework to study protein deregulation in complex diseases such as cancer. Here we demonstrate that a probabilistic analysis integrating model organism interactome data, protein domain data, genome-wide gene expression data and functional annotation data predicts nearly 40,000 protein-protein interactions in humans—a result comparable to those obtained with experimental and computational approaches in model organisms. We validated the accuracy of the predictive model on an independent test set of known interactions and also experimentally confirmed two predicted interactions relevant to human cancer, implicating uncharacterized proteins into definitive pathways. We also applied the human interactome network to cancer genomics data and identified several interaction subnetworks activated in cancer. This integrative analysis provides a comprehensive framework for exploring the human protein interaction network.
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