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

STRING v9.1 : protein-protein interaction networks, with increased coverage and integration / A. Franceschini, D. Szklarczyk, S. Frankild, M. Kuhn, M. Simonovic, A. Roth, J. Lin, P. Minguez, P. Bork, C. von Mering, L. J. Jensen. - In: NUCLEIC ACIDS RESEARCH. - ISSN 0305-1048. - 41:D1(2013 Jan 01), pp. D808-D815. [10.1093/nar/gks1094]

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

J. Lin;
2013

Abstract

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
molecular interaction database; large gene lists; metabolic pathways; evolution; prediction; organisms; screens; visualization; enrichment; proteomics; algorithm; article; automation; computer interface; computer prediction; data base; data mining; molecular dynamics; natural language processing; online system; orthology; priority journal; process optimization; protein binding; protein domain; protein protein interaction; quality control; STRING version 9.1
Settore INF/01 - Informatica
Settore BIO/11 - Biologia Molecolare
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/249920
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