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ETAscape: analyzing protein networks to predict enzymatic function and substrates in Cytoscape
Author(s) -
Benjamin J. Bachman,
Eric Venner,
Rhonald C. Lua,
Serkan Erdin,
Olivier Lichtarge
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts331
Subject(s) - plug in , computer science , annotation , visualization , computational biology , set (abstract data type) , function (biology) , protein function , data mining , biology , artificial intelligence , evolutionary biology , genetics , programming language , gene
Most proteins lack experimentally validated functions. To address this problem, we implemented the Evolutionary Trace Annotation (ETA) method in the Cytoscape network visualization environment. The result is the ETAscape plugin, which builds a structural genomics network based on local structural and evolutionary similarities among proteins and then globally diffuses known annotations across the resulting network. The plugin displays these novel functional annotations, their confidence, the molecular basis for individual matches and the set of matches that lead to a prediction.

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