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

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 certa...

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Autores principales: Franceschini, Andrea, Szklarczyk, Damian, Frankild, Sune, Kuhn, Michael, Simonovic, Milan, Roth, Alexander, Lin, Jianyi, Minguez, Pablo, Bork, Peer, von Mering, Christian, Jensen, Lars J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531103/
https://www.ncbi.nlm.nih.gov/pubmed/23203871
http://dx.doi.org/10.1093/nar/gks1094
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author Franceschini, Andrea
Szklarczyk, Damian
Frankild, Sune
Kuhn, Michael
Simonovic, Milan
Roth, Alexander
Lin, Jianyi
Minguez, Pablo
Bork, Peer
von Mering, Christian
Jensen, Lars J.
author_facet Franceschini, Andrea
Szklarczyk, Damian
Frankild, Sune
Kuhn, Michael
Simonovic, Milan
Roth, Alexander
Lin, Jianyi
Minguez, Pablo
Bork, Peer
von Mering, Christian
Jensen, Lars J.
author_sort Franceschini, Andrea
collection PubMed
description 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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spelling pubmed-35311032013-03-07 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. Nucleic Acids Res Articles 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. Oxford University Press 2013-01 2012-11-29 /pmc/articles/PMC3531103/ /pubmed/23203871 http://dx.doi.org/10.1093/nar/gks1094 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.
spellingShingle Articles
Franceschini, Andrea
Szklarczyk, Damian
Frankild, Sune
Kuhn, Michael
Simonovic, Milan
Roth, Alexander
Lin, Jianyi
Minguez, Pablo
Bork, Peer
von Mering, Christian
Jensen, Lars J.
STRING v9.1: protein-protein interaction networks, with increased coverage and integration
title STRING v9.1: protein-protein interaction networks, with increased coverage and integration
title_full STRING v9.1: protein-protein interaction networks, with increased coverage and integration
title_fullStr STRING v9.1: protein-protein interaction networks, with increased coverage and integration
title_full_unstemmed STRING v9.1: protein-protein interaction networks, with increased coverage and integration
title_short STRING v9.1: protein-protein interaction networks, with increased coverage and integration
title_sort string v9.1: protein-protein interaction networks, with increased coverage and integration
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531103/
https://www.ncbi.nlm.nih.gov/pubmed/23203871
http://dx.doi.org/10.1093/nar/gks1094
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