A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä

The STRING database in 2025: protein networks with directionality of regulation




TekijätSzklarczyk, Damian; Nastou, Katerina; Koutrouli, Mikaela; Kirsch, Rebecca; Mehryary, Farrokh; Hachilif, Radja; Hu, Dewei; Peluso, Matteo E.; Huang, Qingyao; Fang, Tao; Doncheva, Nadezhda T.; Pyysalo, Sampo; Bork, Peer; Jensen, Lars J.; von Mering, Christian

KustantajaOxford University Press (OUP)

Julkaisuvuosi2025

JournalNucleic Acids Research

Tietokannassa oleva lehden nimiNucleic Acids Research

Vuosikerta53

NumeroD1

AloitussivuD730

LopetussivuD737

ISSN0305-1048

eISSN1362-4962

DOIhttps://doi.org/10.1093/nar/gkae1113

Verkko-osoitehttp://doi.org/10.1093/nar/gkae1113

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/470957177


Tiivistelmä

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/.


Ladattava julkaisu

This is an electronic reprint of the original article.
This reprint may differ from the original in pagination and typographic detail. Please cite the original version.




Julkaisussa olevat rahoitustiedot
Swiss Institute of Bioinformatics; Novo Nordisk Foundation [NNF14CC0001, NNF20SA0035590]; European Molecular Biology Laboratory (EMBL Heidelberg); HORIZON EUROPE Marie Skłodowska-Curie Actions [101023676 to K.N.]; Academy of Finland [332844 to F.M. and S.P.]. Funding for open access charge: University of Zurich.


Last updated on 2025-24-02 at 13:03