Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection

BioMed Research International

Volumn 2015, Issue , 2015, Pages

  Ma, Xin ^a   Guo, Jing ^b   Sun, Xiao ^b  

^a NANJING AUDIT UNIVERSITY   (China)

^b SOUTHEAST UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

RNA BINDING PROTEIN; AMINO ACID; RNA;

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; INFORMATION; PHYSICAL CHEMISTRY; PREDICTION; PREDICTOR VARIABLE; RANDOM FOREST; ALGORITHM; BIOLOGY; CHEMICAL PHENOMENA; CHEMISTRY; PROCEDURES; PROTEIN DATABASE; REPRODUCIBILITY; STATIC ELECTRICITY; STATISTICAL MODEL;

ALGORITHMS; AMINO ACIDS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; HYDROPHOBIC AND HYDROPHILIC INTERACTIONS; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS; RNA; RNA-BINDING PROTEINS; STATIC ELECTRICITY;

EID: 84945894566     PISSN: 23146133     EISSN: 23146141     Source Type: Journal    
DOI: 10.1155/2015/425810     Document Type: Article

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