Identification of DNA-binding proteins using support vector machine with sequence information

Computational and Mathematical Methods in Medicine

Volumn 2013, Issue , 2013, Pages

  Ma, Xin ^a   Wu, Jiansheng ^b   Xue, Xiaoyun ^c  

^a NANJING AUDIT UNIVERSITY   (China)

^b NANJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^c INSTITUTE OF PLANT PROTECTION   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DNA; OPTIMIZATION; PHYSICOCHEMICAL PROPERTIES; PREDICTIVE ANALYTICS; STATISTICAL TESTS; SUPPORT VECTOR MACHINES;

CORRELATION COEFFICIENT; DNA-BINDING PROTEIN; EVOLUTIONARY INFORMATION; OVERALL ACCURACIES; PERFORMANCE COMPARISON; SEQUENCE INFORMATIONS; SEQUENTIAL MINIMAL OPTIMIZATION; STATE-OF-THE-ART METHODS;

PROTEINS;

DNA BINDING PROTEIN;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; BINDING AFFINITY; DNA BINDING; PHYSICAL CHEMISTRY; PROTEIN ANALYSIS; PROTEIN DNA INTERACTION; SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINE; ARTIFICIAL INTELLIGENCE; BINDING SITE; EVALUATION STUDY; GENETICS; METABOLISM; PROTEIN DATABASE; STATISTICS; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; BINDING SITES; DATABASES, PROTEIN; DNA-BINDING PROTEINS; SUPPORT VECTOR MACHINES;

EID: 84885590446     PISSN: 1748670X     EISSN: 17486718     Source Type: Journal    
DOI: 10.1155/2013/524502     Document Type: Article

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