Towards a proteome-scale map of the human protein-protein interaction network |
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Authors: | Rual Jean-François Venkatesan Kavitha Hao Tong Hirozane-Kishikawa Tomoko Dricot Amélie Li Ning Berriz Gabriel F Gibbons Francis D Dreze Matija Ayivi-Guedehoussou Nono Klitgord Niels Simon Christophe Boxem Mike Milstein Stuart Rosenberg Jennifer Goldberg Debra S Zhang Lan V Wong Sharyl L Franklin Giovanni Li Siming Albala Joanna S Lim Janghoo Fraughton Carlene Llamosas Estelle Cevik Sebiha Bex Camille Lamesch Philippe Sikorski Robert S Vandenhaute Jean Zoghbi Huda Y Smolyar Alex Bosak Stephanie Sequerra Reynaldo Doucette-Stamm Lynn Cusick Michael E Hill David E Roth Frederick P Vidal Marc |
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Institution: | Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, 44 Binney Street, Boston, Massachusetts 02115, USA. |
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Abstract: | Systematic mapping of protein-protein interactions, or 'interactome' mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein-protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of approximately 8,100 currently available Gateway-cloned open reading frames and detected approximately 2,800 interactions. This data set, called CCSB-HI1, has a verification rate of approximately 78% as revealed by an independent co-affinity purification assay, and correlates significantly with other biological attributes. The CCSB-HI1 data set increases by approximately 70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project. |
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