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

A. Franceschini; M. Simonovic; A. Roth; C. Von Mering; D. Szklarczyk; Sune Pletscher-Frankild; L.J. Jensen; Melanie Michelsen Kuhn; J. Lin; P. Minguez; P. Bork

doi:10.1093/nar/gks1094

STRING v9.1

Authors:

Franceschini, A. ;
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University of Zurich
Simonovic, M. ;
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University of Zurich
Roth, A. ;
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University of Zurich
Von Mering, C. ;
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University of Zurich
Szklarczyk, D. ;
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Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, Københavns Universitet
Pletscher-Frankild, Sune ;
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Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, Københavns Universitet
Jensen, L.J. ;
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0000-0001-7885-715X
Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, Københavns Universitet
Kuhn, Melanie Michelsen ;
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Aalborg University
Lin, J. ;
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University of Milan
Minguez, P. ;
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European Molecular Biology Laboratory, Heidelberg
Bork, P.
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European Molecular Biology Laboratory, Heidelberg

Subtitle:

Protein-protein interaction networks, with increased coverage and integration

DOI:

10.1093/nar/gks1094

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.

Type:

Journal article

Language:

English

Published in:

Nucleic Acids Research, 2013, Vol 41, Issue D1

Main Research Area:

Medical science

Publication Status:

Published

Review type:

Peer Review

Submission year:

2013

Scientific Level:

Scientific

ID:

234075246

STRING v9.1

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