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

2012; Oxford University Press; Volume: 41; Issue: D1 Linguagem: Inglês

10.1093/nar/gks1094

1362-4962

Andrea Franceschini, Damian Szklarczyk, Sune Pletscher-Frankild, Michael Kuhn, Milan Simonovic, Alexander Röth, Jianyi Lin, Pablo Mínguez, Peer Bork, Christian von Mering, Lars Juhl Jensen,

Microbial Metabolic Engineering and Bioproduction

Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made—particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.