Classifying proteins using gapped Markov feature pairs

Neurocomputing

Volumn 73, Issue 13-15, 2010, Pages 2363-2374

  Ji, Xiaonan ^a   Bailey, James ^a   Ramamohanarao, Kotagiri ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

Delay space; Gapped Markov chains; Protein classification; Support vector machine

Indexed keywords

ANALYSIS METHOD; DISEASE DIAGNOSIS; DIVERSE RANGE; DRUG DESIGN; EXPERIMENTAL STUDIES; FEATURE SPACE; GAPPED MARKOV CHAINS; MARKOV CHAIN; PROTEIN CLASSIFICATION; PROTEIN FAMILY; PROTEIN SEQUENCES; TRANSITION PROBABILITIES;

AMINO ACIDS; CHAINS; CLASSIFIERS; DIAGNOSIS; DYNAMICAL SYSTEMS; MARKOV PROCESSES; NONLINEAR DYNAMICAL SYSTEMS; ORGANIC ACIDS; SUPPORT VECTOR MACHINES; VECTOR SPACES;

PROTEINS;

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; CLASSIFICATION ALGORITHM; CLASSIFIER; COMPUTER PREDICTION; CONTROLLED STUDY; MATHEMATICAL MODEL; NONLINEAR SYSTEM; PERFORMANCE MEASUREMENT SYSTEM; PRIORITY JOURNAL; PROBABILITY; PROTEIN ANALYSIS; SEQUENCE HOMOLOGY; STRUCTURE ANALYSIS; SUPPORT VECTOR MACHINE; THEORETICAL STUDY;

EID: 77955325171     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2009.12.038     Document Type: Article

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