Using support vector machine to predict β- and γ-turns in proteins

Journal of Computational Chemistry

Volumn 29, Issue 12, 2008, Pages 1867-1875

  Hu, Xiuzhen ^a,b   Li, Qianzhong ^a  

^a INNER MONGOLIA UNIVERSITY   (China)

^b INNER MONGOLIA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

turn; turn; Increment of diversity; Position conservation scoring function; Support vector machine

Indexed keywords

BOOLEAN FUNCTIONS; CHAINS; CORRELATION METHODS; FORECASTING; IMAGE RETRIEVAL; LEARNING SYSTEMS; PREDICTIVE CONTROL SYSTEMS; PROTEINS; VECTORS;

CORRELATION COEFFICIENT (CC); CROSS-VALIDATION (CV); PREDICTION ACCURACY; PREDICTIVE MODELING; PROTEIN CHAINS; RECEIVER OPERATING CHARACTERISTIC (ROC); SCORING FUNCTIONS; SECONDARY STRUCTURES; SUPPORT VECTOR MACHINE (SVM); SVM METHOD; TRAINING AND TESTING;

SUPPORT VECTOR MACHINES;

PROTEIN;

ALGORITHM; ARTICLE; CHEMICAL STRUCTURE; CHEMISTRY; PROTEIN SECONDARY STRUCTURE;

ALGORITHMS; MODELS, MOLECULAR; PROTEIN STRUCTURE, SECONDARY; PROTEINS;

EID: 47549095849     PISSN: 01928651     EISSN: 1096987X     Source Type: Journal    
DOI: 10.1002/jcc.20929     Document Type: Article

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