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A computational interactome and functional annotation for the human proteome

We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current Pr...

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Autores principales: Garzón, José Ignacio, Deng, Lei, Murray, Diana, Shapira, Sagi, Petrey, Donald, Honig, Barry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5115866/
https://www.ncbi.nlm.nih.gov/pubmed/27770567
http://dx.doi.org/10.7554/eLife.18715
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author Garzón, José Ignacio
Deng, Lei
Murray, Diana
Shapira, Sagi
Petrey, Donald
Honig, Barry
author_facet Garzón, José Ignacio
Deng, Lei
Murray, Diana
Shapira, Sagi
Petrey, Donald
Honig, Barry
author_sort Garzón, José Ignacio
collection PubMed
description We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein’s function. We provide annotations for most human proteins, including many annotated as having unknown function. DOI: http://dx.doi.org/10.7554/eLife.18715.001
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spelling pubmed-51158662016-11-28 A computational interactome and functional annotation for the human proteome Garzón, José Ignacio Deng, Lei Murray, Diana Shapira, Sagi Petrey, Donald Honig, Barry eLife Computational and Systems Biology We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein’s function. We provide annotations for most human proteins, including many annotated as having unknown function. DOI: http://dx.doi.org/10.7554/eLife.18715.001 eLife Sciences Publications, Ltd 2016-10-22 /pmc/articles/PMC5115866/ /pubmed/27770567 http://dx.doi.org/10.7554/eLife.18715 Text en © 2016, Garzón et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Garzón, José Ignacio
Deng, Lei
Murray, Diana
Shapira, Sagi
Petrey, Donald
Honig, Barry
A computational interactome and functional annotation for the human proteome
title A computational interactome and functional annotation for the human proteome
title_full A computational interactome and functional annotation for the human proteome
title_fullStr A computational interactome and functional annotation for the human proteome
title_full_unstemmed A computational interactome and functional annotation for the human proteome
title_short A computational interactome and functional annotation for the human proteome
title_sort computational interactome and functional annotation for the human proteome
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5115866/
https://www.ncbi.nlm.nih.gov/pubmed/27770567
http://dx.doi.org/10.7554/eLife.18715
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