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STRING v9.1: protein-protein interaction networks, with increased coverage and integration

Describes STRING v9.1, a database integrating known and predicted protein-protein interactions across 1100+ organisms with improved text mining.

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STRING v9.1: protein-protein interaction networks, with increased coverage and integration

By Andrea Franceschini, Damian Szklarczyk, Sune Frankild et al.Nucleic Acids Res.
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STRING is a database that aims to give a global perspective on protein-protein interactions and associations for as many organisms as feasible. Because interaction data are annotated at many levels of detail across resources ranging from raw repositories to formalized pathway databases, STRING scores and integrates both known and predicted associations—including lower-quality data and computational predictions—into comprehensive protein networks covering more than 1100 organisms.

This paper describes the update to version 9.1, which introduces several improvements: the automated mining of scientific texts was extended to include full-text articles, the algorithm for transferring interactions from one model organism to another was entirely redesigned, and users are provided with statistical information on any functional enrichment observed in their networks. These enhancements increased the database's coverage and integration, making it more useful for analyzing cellular mechanisms and functions.

Abstract

Complete knowledge of protein interactions would be a major step toward understanding cellular mechanisms, yet such data are scattered across resources at varying detail. The STRING database gives a global view of all interaction data—including lower-quality data and predictions—by scoring and integrating known and predicted associations into networks covering over 1100 organisms. Version 9.1 adds full-text text mining, a redesigned cross-organism interaction-transfer algorithm, and functional-enrichment statistics for user networks.

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STRINGprotein-protein interactionbiological networkstext miningfunctional enrichmentbioinformatics database
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