title: DiANNA 1.1: an extension of the DiANNA web server for ternary cysteine classification.
abstract: DiANNA is a recent state-of-the-art artificial neural network and web server, which determines the cysteine oxidation state and disulfide connectivity of a protein, given only its amino acid sequence. Version 1.0 of DiANNA uses a feed-forward neural network to determine which cysteines are involved in a disulfide bond, and employs a novel architecture neural network to predict which half-cystines are covalently bound to which other half-cystines. In version 1.1 of DiANNA, described here, we extend functionality by applying a support vector machine with spectrum kernel for the cysteine classification problem-to determine whether a cysteine is reduced (free in sulfhydryl state), half-cystine (involved in a disulfide bond) or bound to a metallic ligand. In the latter case, DiANNA predicts the ligand among iron, zinc, cadmium and carbon. Available at: http://bioinformatics.bc.edu/clotelab/DiANNA/.
authors.affiliation: Department of Biology, Boston College, Chestnut Hill, MA, USA.
authors.forename: F
authors.initials: F
authors.lastname: Ferrè
authors.forename: P
authors.initials: P
authors.lastname: Clote
mesh_terms: D001185:Artificial Intelligence; D003545:Cysteine / Q000737:chemistry* / Q000145:classification*; D004220:Disulfides / Q000737:chemistry; D020407:Internet; D010084:Oxidation-Reduction; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein; D012984:Software; D014584:User-Computer Interface
chemical_list: D004220:Disulfides; D011506:Proteins; D003545:Cysteine