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Volumn 19, Issue 4, 2012, Pages 388-397

Predicting protein structural class by incorporating patterns of over-represented k-mers into the general form of Chou's PseAAC

Author keywords

Markov model; Protein structural class; Relative polypeptide composition; Support vector machine; T statistic

Indexed keywords

ACCURACY; AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ARTICLE; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; DATA ANALYSIS; HIDDEN MARKOV MODEL; INTERMETHOD COMPARISON; JACKKNIFE TEST; LEARNING ALGORITHM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PREDICTION; PROTEIN DOMAIN; SENSITIVITY AND SPECIFICITY; SEQUENCE HOMOLOGY; SUPPORT VECTOR MACHINE;

EID: 84863389371     PISSN: 09298665     EISSN: None     Source Type: Journal    
DOI: 10.2174/092986612799789350     Document Type: Article
Times cited : (27)

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