Prediction of turn types in protein structure by machine-learning classifiers

Proteins: Structure, Function and Bioinformatics

Volumn 74, Issue 2, 2009, Pages 344-352

  Meissner, Michael ^a   Koch, Oliver ^b   Klebe, Gerhard ^b   Schneider, Gisbert ^a  

^a GOETHE UNIVERSITY   (Germany)

^b PHILIPPS UNIVERSITY MARBURG   (Germany)

Author keywords

Bioinformatics; Kernel function; Prediction; Probabilistic neural network; Secondary structure; Self organizing map; Support vector machine; Turn classification

Indexed keywords

AMINO ACID; PROTEIN;

ACCURACY; ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BETA TURN; CLASSIFICATION; COMPUTER PROGRAM; DATA BASE; HYDROGEN BOND; KERNEL METHOD; MACHINE LEARNING; MOLECULAR INTERACTION; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; RELIBASE; SELF ORGANIZING MAP; STRUCTURAL BIOINFORMATICS; SUPPORT VECTOR MACHINE; ARTIFICIAL INTELLIGENCE; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER SIMULATION; EVALUATION; METHODOLOGY; PROTEIN DATABASE; SEQUENCE ANALYSIS;

AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATABASES, PROTEIN; MODELS, MOLECULAR; NEURAL NETWORKS (COMPUTER); PROTEIN STRUCTURE, SECONDARY; PROTEINS; SEQUENCE ANALYSIS, PROTEIN;

EID: 59449110365     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.22164     Document Type: Article

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