Nucleic Acids Research · 2020 · 8.6K citations · 53 references
Life SciencesBioinformaticsMolecular BiologyComputational BiologyGenomicsProtein-protein InteractionsFunctional GenomicsGenomic Data IntegrationGenomic DatabasesMolecular Interaction NetworksNetwork IntegrationProtein-protein Interaction NetworksComputational Interaction ScoringFunctional Annotation Of InteractionsLiterature-curated Interaction DatabasesProtein Interaction DatabasesProtein Interaction PredictionProtein-protein Interaction PredictionScientific Literature MiningString Analysis
Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein-protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/.
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UniProt: a worldwide hub of protein knowledge
Nucleic Acids Research · 2018 · 8.4K citations · Full text
KEGG as a reference resource for gene and protein annotation
Minoru Kanehisa, Yoko Sato, Masayuki Kawashima et al. · Nucleic Acids Research · 2015 · 7.9K citations · Full text