STRING v10: protein–protein interaction networks, integrated over the tree of life

By Damian Szklarczyk, Andrea Franceschini, S. Wyder, Kristoffer Forslund, Davide Heller, Jaime Huerta-Cepas, Milan Simonovic, Alexander C. J. Roth, Alberto Santos, Kalliopi Tsafou and 4 more. 2014

9,777 citations recorded by the source corpus.

The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein–protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein–protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.

Subfields: Molecular Biology

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Citations in the corpus

The SWISS-MODEL Repository—new features and functionality (2016, background): “Information about the target protein includes the name of the target protein, links to UniProtKB (26), InterPro (27) and STRING (28).”
Graph convolutional networks for computational drug development and discovery (2019, background): “The protein space is shared with STRING [100], a protein–protein network database.”
STITCH 5: augmenting protein–chemical interaction networks with tissue and affinity data (2015, background): “STITCH, in its fifth release, shares protein space with STRING v10 (17) and now encompasses more than 9 600 000 proteins from 2031 eukaryotic and prokaryotic genomes.”
The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible (2016, methodology): “STRING has been maintained continuously since the year 2000, and has already been described in several publications (31–34).”
Network Pharmacology Databases for Traditional Chinese Medicine: Review and Assessment (2019, background): “…et al., 2006), STITCH (Kuhn et al., 2014), ChEMBL (Gaulton et al., 2012), and PubChem (Wang et al., 2009)], target interaction databases [STRING (Szklarczyk et al., 2015), HPRD (Peri et al., 2003), MINT (Zanzoni et al., 2002), IntAct (Kerrien et al., 2012), Reactome (D’Eustachio, 2009), and…”
eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences (2015, positive): “This step is coordinated with the STRING (27) and STITCH (28) databases so that the underlying set of protein sequences and names is shared among all three resources.”
Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell‐lines (2015, methodology): “To compute this score, we ﬁrst import protein–protein interaction information from the STRING database [22], separately for each organism in PaxDb.”
HIPPIE v2.0: enhancing meaningfulness and reliability of protein–protein interaction networks (2016, background): “There are other resources integrating PPIs and gene functional interactions (40,41), and some of them make it possible to generate tissue-specific (42,43) or more general context-specific networks (44).”