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

By Andrea Franceschini, Damian Szklarczyk, Sune Frankild, Michael Kuhn, Milan Simonovic, Alexander C. J. Roth, Jianyi Lin, Pablo Minguez, Peer Bork, C. von Mering and 1 more. 2012

4,385 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

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Citations in the corpus

Computational solutions for omics data (2013, background): “Although far from complete, large-scale networks have been determined for numerous organisms, including humans and other model organisms 110–114 .”
Pathway and Network Analysis of Cancer Genomes (2015, neutral): “Examples of recommended network construction algorithms include GeneMANIA 39 , ReactomeFIViz 40 , STRING 38 , ResponseNet 41 , NetBox 42 , MEMo 43 , and EnrichNet 44 ( Supplementary Table 2 ).”
Tensor Factorization for Precision Medicine in Heart Failure with Preserved Ejection Fraction (2017, positive): “such as STRING [34], KEGG [35], InterPro [36], Aceview [37], and Pfam [38].”
Unexpected features of the dark proteome (2015, methodology): “Franceschini A, et al. (2013) STRING v9.”
A highly conserved program of neuronal microexons is misregulated in autistic brains (2014, background): “, 2013) databases with the dashed lines representing indirect interactions that are either between proteins found within same protein complex but not interacting directly or predicted interactions based on paralogs (Franceschini et al., 2013).”
STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets (2018, methodology): “…particular network (counts denote how many records covered at least two of the proteins in the network; not all of these records contributed high-scoring links after score calibration). defined in eggNOG (32), in order to transfer associations between organisms where applicable (described in (29)).”