Probabilistic model of the human protein-protein interaction network

被引:302
作者
Rhodes, DR
Tomlins, SA
Varambally, S
Mahavisno, V
Barrette, T
Kalyana-Sundaram, S
Ghosh, D
Pandey, A
Chinnaiyan, AM [1 ]
机构
[1] Univ Michigan, Sch Med, Bioinformat Program, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Sch Med, Dept Pathol, Ann Arbor, MI 48109 USA
[3] Univ Michigan, Sch Med, Dept Biostat, Ann Arbor, MI 48109 USA
[4] Univ Michigan, Sch Med, Dept Urol, Ann Arbor, MI 48109 USA
[5] Univ Michigan, Sch Med, Ctr Comprehens Canc, Ann Arbor, MI 48109 USA
[6] Johns Hopkins Univ, McKusick Nathans Inst Genet Med, Baltimore, MD 21205 USA
[7] Johns Hopkins Univ, Dept Biol Chem, Baltimore, MD 21205 USA
关键词
D O I
10.1038/nbt1103
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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.
引用
收藏
页码:951 / 959
页数:9
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