The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest

Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modal...

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Published in:	Nucleic acids research Vol. 51; no. D1; pp. D638 - D646
Main Authors:	Szklarczyk, Damian, Kirsch, Rebecca, Koutrouli, Mikaela, Nastou, Katerina, Mehryary, Farrokh, Hachilif, Radja, Gable, Annika L, Fang, Tao, Doncheva, Nadezhda T, Pyysalo, Sampo, Bork, Peer, Jensen, Lars J, von Mering, Christian
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 06.01.2023
Subjects:	Database Issue Databases, Protein Genomics Protein Interaction Mapping - methods Proteins - genetics Proteins - metabolism Proteomics User-Computer Interface
ISSN:	0305-1048, 1362-4962, 1362-4962
Online Access:	Get full text
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Abstract	Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database (https://string-db.org/) systematically collects and integrates protein–protein interactions—both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes.
AbstractList	Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database (https://string-db.org/) systematically collects and integrates protein–protein interactions—both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes. Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database (https://string-db.org/) systematically collects and integrates protein-protein interactions-both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes.Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database (https://string-db.org/) systematically collects and integrates protein-protein interactions-both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes.
Author	Koutrouli, Mikaela Nastou, Katerina Jensen, Lars J Szklarczyk, Damian Bork, Peer Fang, Tao Doncheva, Nadezhda T Kirsch, Rebecca Gable, Annika L von Mering, Christian Mehryary, Farrokh Pyysalo, Sampo Hachilif, Radja
Author_xml	– sequence: 1 givenname: Damian surname: Szklarczyk fullname: Szklarczyk, Damian – sequence: 2 givenname: Rebecca surname: Kirsch fullname: Kirsch, Rebecca – sequence: 3 givenname: Mikaela orcidid: 0000-0002-8953-3561 surname: Koutrouli fullname: Koutrouli, Mikaela – sequence: 4 givenname: Katerina orcidid: 0000-0003-3611-5726 surname: Nastou fullname: Nastou, Katerina – sequence: 5 givenname: Farrokh orcidid: 0000-0002-5555-2828 surname: Mehryary fullname: Mehryary, Farrokh – sequence: 6 givenname: Radja surname: Hachilif fullname: Hachilif, Radja – sequence: 7 givenname: Annika L surname: Gable fullname: Gable, Annika L – sequence: 8 givenname: Tao orcidid: 0000-0001-9659-7726 surname: Fang fullname: Fang, Tao – sequence: 9 givenname: Nadezhda T orcidid: 0000-0002-8806-6850 surname: Doncheva fullname: Doncheva, Nadezhda T – sequence: 10 givenname: Sampo surname: Pyysalo fullname: Pyysalo, Sampo – sequence: 11 givenname: Peer surname: Bork fullname: Bork, Peer – sequence: 12 givenname: Lars J surname: Jensen fullname: Jensen, Lars J – sequence: 13 givenname: Christian orcidid: 0000-0001-7734-9102 surname: von Mering fullname: von Mering, Christian
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/36370105$$D View this record in MEDLINE/PubMed
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Snippet	Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known,...
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SubjectTerms	Database Issue Databases, Protein Genomics Protein Interaction Mapping - methods Proteins - genetics Proteins - metabolism Proteomics User-Computer Interface
Title	The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest
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