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The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

Jensen Lars J; Bork Peer; Gable Annika L; Doncheva Nadezhda T; Fang Tao; Legeay Marc; Kirsch Rebecca; Szklarczyk Damian; Nastou Katerina C; von Mering Christian; Pyysalo Sampo; Lyon David

The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

Jensen Lars J
Bork Peer
Gable Annika L
Doncheva Nadezhda T
Fang Tao
Legeay Marc
Kirsch Rebecca
Szklarczyk Damian
Nastou Katerina C
von Mering Christian
Pyysalo Sampo
Lyon David
Katso/Avaa
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Oxford University Press
doi:10.1093/nar/gkaa1074
URI
https://academic.oup.com/nar/article/49/D1/D605/6006194
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2021042823829
Tiivistelmä

Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein–protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/.

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