title: EFICAz2.5: application of a high-precision enzyme function predictor to 396 proteomes.
abstract: 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, EFICAz(2) (enzyme function inference by a combined approach). Here, we present an updated improved version, EFICAz(2.5), that is trained on a significantly larger data set of enzyme sequences and PROSITE patterns. We also present the results of the application of EFICAz(2.5) to the enzyme reannotation of 396 genomes cataloged in the ENSEMBL database.
  
  
  BACKGROUND
  The EFICAz(2.5) server and database is freely available with a use-friendly interface at http://cssb.biology.gatech.edu/EFICAz2.5.
authors.affiliation: Center for Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA 30318, USA.
authors.forename: Narendra
authors.initials: N
authors.lastname: Kumar
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Skolnick
mesh_terms: D030541:Databases, Genetic; D004798:Enzymes / Q000737:chemistry* / Q000145:classification / Q000235:genetics* / Q000378:metabolism; D016678:Genome; D006801:Humans; D058977:Molecular Sequence Annotation; D020543:Proteome / Q000235:genetics; D020539:Sequence Analysis, Protein; D012984:Software
chemical_list: D004798:Enzymes; D020543:Proteome