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

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Szklarczyk, Damian, Kirsch, Rebecca, Koutrouli, Mikaela, Nastou, Katerina, Mehryary, Farrokh, Hachilif, Radja, Gable, Annika L, Fang, Tao +5 more·2023·Nucleic Acids Research
DOI 10.1093/nar/gkac1000PMC PMC9825434
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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.

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  • According to the STRING database, even at the low confidence interaction score of 0.15, GAL3ST2 and MUC-16 do not share a functional connection.

    “According to the STRING database41, even at the low confidence interaction score of 0.15, GAL3ST2 and MUC-16 do not share a functional connection.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [41]

    The Database Content section describes STRING as a protein-association database with confidence scores for protein pairs. Our copy does not report a query for GAL3ST2 and MUC-16 or establish that they lack a functional connection at a score threshold of 0.15. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • At the low confidence interaction score of 0.15, TMEM119 and SELPLG have a shared connection due to co-expression and co-mentioning in PubMed abstracts, and the functional link was also supported by GeneMANIA.

    “However, at the low confidence interaction score of 0.15, TMEM119 and SELPLG have a shared connection due to co-expression and co-mentioning in PubMed abstracts, functional link was also supported by GeneMANIA.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [41]

    The DATABASE CONTENT section (page unavailable) says STRING uses co-mentions in PubMed abstracts, and IMPROVED CO-EXPRESSION ANALYSIS (page unavailable) describes co-expression as evidence for functional associations. But the paper does not report a TMEM119–SELPLG connection at score 0.15 or say GeneMANIA supported that link; the claim’s specific result is unsupported. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • KRT19 and STAT5B associations with GDF-15 were supported by GeneMANIA as well as STRING database.

    “KRT19 and STAT5B associations with GDF-15 were supported by GeneMANIA as well as STRING database.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [41]

  • Based on the STRING database, at the medium confidence interaction score of 0.4, TMEM119 and SELPLG do not have a shared link.

    “Based on the STRING database41, at the medium confidence interaction score of 0.4, TMEM119 and SELPLG do not have a shared link.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [41]

  • At the medium confidence interaction score of 0.4 in STRING, there was no shared network with GDF-15.

    “We conducted additional network analysis using the STRING database41; at the medium confidence interaction score of 0.4, there was no shared network with GDF-15.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [41]

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Authors
Szklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A. L., Fang, T., Doncheva, N. T., Pyysalo, S., Bork, P., Jensen, L. J., & von Mering, C.
Affiliations
  • SIB Swiss Institute of Bioinformatics (CH)
  • University of Copenhagen (DK)
  • University of Turku (FI)
  • Structural and Computational Biology Unit, European Molecular Biology Laboratory , 69117 Heidelberg, Germany
  • Department of Molecular Life Sciences, University of Zurich , 8057 Zurich, Switzerland
Corresponding author
Jensen, Lars J
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2022-11-12
Volume
51
Issue
D1
Pages
D638-D646
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gkac1000
PMC
PMC9825434
OpenAlex
W4308834893
Cited by
9,726
References
3
Citations by year
2026: 3593 · 2025: 3510 · 2024: 2134 · 2023: 479 · 2022: 3 · 2021: 2 · 2012: 1
FWCI
510.61
Type
journal article
Language
en
Open access
Licence
Locations
  • Nucleic Acids Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion, cc-by)
  • UTUPub (University of Turku) (submittedVersion, cc-by)
  • Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
  • Zurich Open Repository and Archive (University of Zurich)
Funders
  • Swiss Institute of Bioinformatics
  • Novo Nordisk Foundation (NNF14CC0001, NNF20SA0035590)
  • European Molecular Biology Laboratory
  • European Union's Horizon 2020
  • Marie Sklodowska-Curie (101023676)
  • Academy of Finland (332844)
  • University of Zurich
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
STRING database, protein-protein interaction, functional association, interaction networks, functional enrichment, variational autoencoder, single-cell RNA sequencing, proteomics
MeSH terms
Proteins, User-Computer Interface, Genomics, Protein Interaction Mapping, Databases, Protein, Proteomics

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