Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naïve Bayes

PLoS ONE

Volumn 9, Issue 1, 2014, Pages

  Lou, Wangchao ^a   Wang, Xiaoqing ^a   Chen, Fan ^a   Chen, Yixiao ^a   Jiang, Bo ^a   Zhang, Hua ^a  

^a ZHEJIANG GONGSHANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DNA BINDING PROTEIN; RNA BINDING PROTEIN; AMINO ACID; DNA;

AMINO ACID SEQUENCE; ARTICLE; BAYES THEOREM; CLASSIFIER; DECISION TREE; GAUSSIAN NAIVE BAYES; K NEAREST NEIGHBOR; LOGISTIC REGRESSION ANALYSIS; MEASUREMENT ACCURACY; PREDICTION; PROTEIN SECONDARY STRUCTURE; RADIAL BASED FUNCTION; RANDOM FOREST; SUPPORT VECTOR MACHINE; ALGORITHM; ANIMAL; CHEMISTRY; HUMAN; INFORMATION PROCESSING; METABOLISM; NORMAL DISTRIBUTION; POSITION WEIGHT MATRIX; RECEIVER OPERATING CHARACTERISTIC; SEQUENCE ANALYSIS; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; AMINO ACIDS; ANIMALS; BAYES THEOREM; DATASETS AS TOPIC; DNA; DNA-BINDING PROTEINS; HUMANS; NORMAL DISTRIBUTION; POSITION-SPECIFIC SCORING MATRICES; PROTEIN STRUCTURE, SECONDARY; RNA-BINDING PROTEINS; ROC CURVE; SEQUENCE ANALYSIS, PROTEIN;

EID: 84899864030     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0086703     Document Type: Article

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