TY - JOUR
T1 - The STRING database in 2025
T2 - protein networks with directionality of regulation
AU - Szklarczyk, Damian
AU - Nastou, Katerina
AU - Koutrouli, Mikaela
AU - Kirsch, Rebecca
AU - Mehryary, Farrokh
AU - Hachilif, Radja
AU - Hu, Dewei
AU - Peluso, Matteo E.
AU - Huang, Qingyao
AU - Fang, Tao
AU - Doncheva, Nadezhda T.
AU - Pyysalo, Sampo
AU - Bork, Peer
AU - Jensen, Lars J.
AU - Von Mering, Christian
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2025
Y1 - 2025
N2 - 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/.
AB - 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/.
U2 - 10.1093/nar/gkae1113
DO - 10.1093/nar/gkae1113
M3 - Journal article
C2 - 39558183
AN - SCOPUS:85214368997
VL - 53
SP - D730-D737
JO - Nucleic Acids Research
JF - Nucleic Acids Research
SN - 0305-1048
IS - D1
ER -