SIDEpro: A novel machine learning approach for the fast and accurate prediction of side-chain conformations

Proteins: Structure, Function and Bioinformatics

Volumn 80, Issue 1, 2012, Pages 142-153

  Nagata, Ken ^a,b   Randall, Arlo ^a,b   Baldi, Pierre ^a,b  

^a Irvine   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Machine learning; Monte Carlo methods; Neural network; Protein structure prediction; Side chain conformation

Indexed keywords

AMINO ACID; PEPTIDE LIBRARY; RNA;

ARTICLE; ATOM; CONTROLLED STUDY; MACHINE LEARNING; MONTE CARLO METHOD; PRIORITY JOURNAL; PROBABILITY; PROTEIN CONFORMATION; PROTEIN FUNCTION; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; RIBOSOME;

ALGORITHMS; AMINO ACIDS; ARTIFICIAL INTELLIGENCE; CASPASE 9; COMPUTER SIMULATION; MODELS, MOLECULAR; PROTEIN STRUCTURE, SECONDARY; RIBOSOMES; SOFTWARE;

EID: 83555178443     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.23170     Document Type: Article

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