The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets
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- Damian Szklarczyk
- Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
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- Annika L Gable
- Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
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- Katerina C Nastou
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark
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- David Lyon
- Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
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- Rebecca Kirsch
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark
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- Sampo Pyysalo
- TurkuNLP Group, Department of Future Technologies, University of Turku, 20014 Turun Yliopisto, Finland
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- Nadezhda T Doncheva
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark
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- Marc Legeay
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark
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- Tao Fang
- Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
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- Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
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- Lars J Jensen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen N, Denmark
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- Christian von Mering
- Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
説明
<jats:title>Abstract</jats:title><jats:p>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/.</jats:p>
収録刊行物
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- Nucleic Acids Research
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Nucleic Acids Research 49 (D1), D605-D612, 2020-11-25
Oxford University Press (OUP)