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STRING v9.1: protein-protein interaction networks, with increased coverage and integration


Franceschini, Andrea; Szklarczyk, Damian; Frankild, Sune; Kuhn, Michael; Simonovic, Milan; Roth, Alexander; Lin, Jianyi; Minguez, Pablo; Bork, Peer; von Mering, Christian; Jensen, Lars J (2013). STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Research, 41(D 1):D808-D815.

Abstract

Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.

Abstract

Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Molecular Life Sciences
08 University Research Priority Programs > Systems Biology / Functional Genomics
08 University Research Priority Programs > Evolution in Action: From Genomes to Ecosystems
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2013
Deposited On:26 Aug 2013 12:05
Last Modified:07 Dec 2017 22:08
Publisher:Oxford University Press
ISSN:0305-1048
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/nar/gks1094
PubMed ID:23203871

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