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Nucleic Acids Res. 2018 Nov 22. doi: 10.1093/nar/gky1131. [Epub ahead of print]

STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets.

Author information

1
Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
2
Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark.
3
Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM)-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28223 Madrid, Spain.
4
Center for non-coding RNA in Technology and Health, University of Copenhagen, 2200 Copenhagen N, Denmark.
5
Resource on Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA 94158-2517, USA.
6
Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
7
Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
8
Max Delbrück Centre for Molecular Medicine, 13125 Berlin, Germany.
9
Department of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, Germany.

Abstract

Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

PMID:
30476243
DOI:
10.1093/nar/gky1131

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