Статья

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

Damian SzklarczykInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, SwitzerlandAnnika L GableInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, SwitzerlandDavid LyonInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, SwitzerlandAlexander JungeNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, DenmarkStefan WyderInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, SwitzerlandJaime Huerta‐CepasCentro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM)—Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28223 Madrid, SpainMilan SimonovicInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, SwitzerlandNadezhda T. DonchevaCenter for non-coding RNA in Technology and Health, University of Copenhagen, 2200 Copenhagen N, DenmarkJohn H. MorrisResource on Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA 94158-2517, USAPeer BorkDepartment of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, GermanyLars Juhl JensenNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, DenmarkChristian von MeringInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland

2018en

ABI

Аннотация

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/.

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Идентификаторы

DOI: 10.1093/nar/gky1131

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar