Prediction of the bonding state of cysteine residues in proteins with machine-learning methods

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6685 LNBI, Issue , 2011, Pages 98-111

  Savojardo, Castrense ^a   Fariselli, Piero ^a   Martelli, Pier Luigi ^a   Shukla, Priyank ^a   Casadio, Rita ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

Conditional Random Fields; Disulfide Bonding State; Disulfide Prediction; Machine Learning; Protein Folding; Protein Structure Prediction

Indexed keywords

CONDITIONAL RANDOM FIELD; DISULFIDE BONDING; DISULFIDE PREDICTION; MACHINE-LEARNING; PROTEIN STRUCTURE PREDICTION; CORRELATION COEFFICIENT; EVOLUTIONARY INFORMATION; HIDDEN CONDITIONAL RANDOM FIELDS; MACHINE LEARNING METHODS; POSITION SPECIFIC SCORING MATRIX;

AMINO ACIDS; ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; CONTENT BASED RETRIEVAL; COVALENT BONDS; FORECASTING; HIDDEN MARKOV MODELS; MICROORGANISMS; PROTEIN FOLDING; SUPPORT VECTOR MACHINES; MARKOV PROCESSES; PROTEINS; RANDOM PROCESSES; SULFUR COMPOUNDS;

PROTEINS; LEARNING SYSTEMS;

EID: 80051681914     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21946-7_8     Document Type: Conference Paper

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