TITLE

EFICAz2.5: application of a high-precision enzyme function predictor to 396 proteomes

AUTHOR(S)
Kumar, Narendra; Skolnick, Jeffrey
PUB. DATE
October 2012
SOURCE
Bioinformatics;Oct2012, Vol. 28 Issue 20, p2687
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Summary: High-quality enzyme function annotation is essential for understanding the biochemistry, metabolism and disease processes of organisms. Previously, we developed a multi-component high-precision enzyme function predictor, EFICAz2 (enzyme function inference by a combined approach). Here, we present an updated improved version, EFICAz2.5, that is trained on a significantly larger data set of enzyme sequences and PROSITE patterns. We also present the results of the application of EFICAz2.5 to the enzyme reannotation of 396 genomes cataloged in the ENSEMBL database.Availability: The EFICAz2.5 server and database is freely available with a use-friendly interface at http://cssb.biology.gatech.edu/EFICAz2.5.Contact: skolnick@gatech.eduSupplementary information: Supplementary data are available at Bioinformatics online.
ACCESSION #
82563592

 

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