STRING: Known and predicted protein-protein associations, integrated and transferred across organisms

European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.
Nucleic Acids Research (Impact Factor: 9.11). 02/2005; 33(Database issue):D433-7. DOI: 10.1093/nar/gki005
Source: PubMed

ABSTRACT A full description of a protein's function requires knowledge of all partner proteins with which it specifically associates. From a functional perspective, 'association' can mean direct physical binding, but can also mean indirect interaction such as participation in the same metabolic pathway or cellular process. Currently, information about protein association is scattered over a wide variety of resources and model organisms. STRING aims to simplify access to this information by providing a comprehensive, yet quality-controlled collection of protein-protein associations for a large number of organisms. The associations are derived from high-throughput experimental data, from the mining of databases and literature, and from predictions based on genomic context analysis. STRING integrates and ranks these associations by benchmarking them against a common reference set, and presents evidence in a consistent and intuitive web interface. Importantly, the associations are extended beyond the organism in which they were originally described, by automatic transfer to orthologous protein pairs in other organisms, where applicable. STRING currently holds 730,000 proteins in 180 fully sequenced organisms, and is available at

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Available from: Markus Krupp, Aug 19, 2015
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    • "The default cutoff for confident interactions is 0.4 [11] [17]. Chemical– protein interactions were transferred among species based on the sequence similarity of the proteins [17]. The chemical–protein interactions have also been successfully utilized to predict nongenotoxic hepatocarcinogenicity [18] [19]. "
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    Chemico-Biological Interactions 09/2014; 223. DOI:10.1016/j.cbi.2014.09.004 · 2.98 Impact Factor
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    • "Importantly, STRING does not need to be comprehensive to assess the presence of secondary binding proteins in our data set. This secondary PIP interaction analysis, based upon experimental prediction methods and high-confidence STRING interactors (confidence score > 0.9 [von Mering et al., 2005]), revealed that the vast majority of proteins identified in our PIP interactome are likely to be direct PIP interactors, since only a few functional interactions are recorded in STRING among the PIPinteracting proteins (Figure S3). Pfam domain analysis revealed that PIP-interacting domains, such as the pleckstrin homology (PH) (Haslam et al., 1993), calponin homology (CH) (Fukami et al., 1996), RNA recognition motif (RBD) (Okada and Ye, 2009), and DOCK homology region (DHR) (Cô té et al., 2005) domains, were highly enriched among our identified PIP-interacting proteins (Figure 4B). "
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    Cell Reports 01/2014; 6(3). DOI:10.1016/j.celrep.2013.12.038 · 8.36 Impact Factor
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    • "which is a unique resource that classifies genes and proteins by their functions (Mi et al., 2007; Mi and Thomas, 2009). The differentially expressed protein interaction network was built automatically by the STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) system with default setting except that organism, confidence score), and interactors shown were set to ''human'', ''0.20'', and ''no more than 10 interactors'', respectively (von Mering et al., 2007, 2005). The gene symbol list of these proteins was input to search against the database which contains known and predicted protein protein interactions. "
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