The STRING database in 2025: protein networks with directionality of regulation
Proteins cooperate, regulate and bind each other to achieve their functions. Understanding the complex network of their interactions is essential for a systems-level description of cellular processes. The STRING database compiles, scores and integrates protein-protein association information drawn from experimental assays, computational predictions and prior knowledge. Its goal is to create comprehensive and objective global networks that encompass both physical and functional interactions. Additionally, STRING provides supplementary tools such as network clustering and pathway enrichment analysis. The latest version, STRING 12.5, introduces a new 'regulatory network', for which it gathers evidence on the type and directionality of interactions using curated pathway databases and a fine-tuned language model parsing the literature. This update enables users to visualize and access three distinct network types-functional, physical and regulatory-separately, each applicable to distinct research needs. In addition, the pathway enrichment detection functionality has been updated, with better false discovery rate corrections, redundancy filtering and improved visual displays. The resource now also offers improved annotations of clustered networks and provides users with downloadable network embeddings, which facilitate the use of STRING networks in machine learning and allow cross-species transfer of protein information. The STRING database is available online at https://string-db.org/.
Authors
- Christian von Mering (ORCID: https://orcid.org/0000-0001-7734-9102)
- Lars Juhl Jensen (ORCID: https://orcid.org/0000-0001-7885-715X)
- Tao Fang (ORCID: https://orcid.org/0000-0001-9659-7726)
- Katerina Nastou (ORCID: https://orcid.org/0000-0003-3611-5726)
- Rebecca Kirsch
- Qingyao Huang (ORCID: https://orcid.org/0000-0002-8255-4722)
- Mikaela Koutrouli (ORCID: https://orcid.org/0000-0002-8953-3561)
- Damian Szklarczyk (ORCID: https://orcid.org/0000-0002-4052-5069)
- Sampo Pyysalo (ORCID: https://orcid.org/0000-0002-6279-5000)
- Peer Bork (ORCID: https://orcid.org/0000-0002-2627-833X)
- Radja Hachilif
- Farrokh Mehryary (ORCID: https://orcid.org/0000-0002-5555-2828)
- Dewei Hu (ORCID: https://orcid.org/0009-0005-5823-1498)
- Nadezhda T. Doncheva (ORCID: https://orcid.org/0000-0002-8806-6850)
- Matteo Eustachio Peluso
Institutions
- University of Copenhagen (DK)
- SIB Swiss Institute of Bioinformatics (CH)
- University of Turku (FI)
- University of Zurich (CH)
- Max Delbrück Center (DE)
- University of Würzburg (DE)
- Novo Nordisk Foundation (DK)
- European Molecular Biology Laboratory (DE)
Publication Details
- Journal
- Nucleic Acids Research
- Published
- 2024-11-18
- DOI
- https://doi.org/10.1093/nar/gkae1113
- Citations
- 382
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 89.09
Funders
- European Molecular Biology Laboratory
- Academy of Finland
- Universität Wien
- Novo Nordisk
- China Scholarship Council
- Universität Zürich
- Novo Nordisk Fonden
- Swiss Institute of Bioinformatics
- H2020 Marie Skłodowska-Curie Actions
- HORIZON EUROPE Marie Sklodowska-Curie Actions