STRING v9.1: Protein-protein interaction networks, with increased coverage and integration
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STRING v9.1 : Protein-protein interaction networks, with increased coverage and integration. / Franceschini, A.; Simonovic, M.; Roth, A.; Von Mering, C.; Szklarczyk, D.; Pletscher-Frankild, Sune; Jensen, L.J.; Kuhn, Melanie Michelsen; Lin, J.; Minguez, P.; Bork, P.
In: Nucleic Acids Research, Vol. 41, No. D1, 01.01.2013, p. D808-D815.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - STRING v9.1
T2 - Protein-protein interaction networks, with increased coverage and integration
AU - Franceschini, A.
AU - Simonovic, M.
AU - Roth, A.
AU - Von Mering, C.
AU - Szklarczyk, D.
AU - Pletscher-Frankild, Sune
AU - Jensen, L.J.
AU - Kuhn, Melanie Michelsen
AU - Lin, J.
AU - Minguez, P.
AU - Bork, P.
PY - 2013/1/1
Y1 - 2013/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84876515907&partnerID=8YFLogxK
U2 - 10.1093/nar/gks1094
DO - 10.1093/nar/gks1094
M3 - Journal article
C2 - 23203871
AN - SCOPUS:84876515907
VL - 41
SP - D808-D815
JO - Nucleic Acids Research
JF - Nucleic Acids Research
SN - 0305-1048
IS - D1
ER -
ID: 46438797