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Large‐scale mapping of human protein interactome using structural complexes
Author(s) -
Tyagi Manoj,
Hashimoto Kosuke,
Shoemaker Benjamin A,
Wuchty Stefan,
Panchenko Anna R
Publication year - 2012
Publication title -
embo reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.584
H-Index - 184
eISSN - 1469-3178
pISSN - 1469-221X
DOI - 10.1038/embor.2011.261
Subject(s) - interactome , computational biology , computer science , modular design , construct (python library) , protein–protein interaction , false positive paradox , complement (music) , interaction network , identification (biology) , biology , artificial intelligence , genetics , phenotype , gene , botany , complementation , programming language , operating system
Although the identification of protein interactions by high‐throughput (HTP) methods progresses at a fast pace, ‘interactome’ data sets still suffer from high rates of false positives and low coverage. To map the human protein interactome, we describe a new framework that uses experimental evidence on structural complexes, the atomic details of binding interfaces and evolutionary conservation. The structurally inferred interaction network is highly modular and more functionally coherent compared with experimental interaction networks derived from multiple literature citations. Moreover, structurally inferred and high‐confidence HTP networks complement each other well, allowing us to construct a merged network to generate testable hypotheses and provide valuable experimental leads.