Improved and promising identificationof human microRNAs by incorporatinga high-quality negative set

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 11, Issue 1, 2014, Pages 192-201

  Wei, Leyi ^a   Liao, Minghong ^a   Gao, Yue ^b   Ji, Rongrong ^a   He, Zengyou ^c   Zou, Quan ^a  

^a XIAMEN UNIVERSITY   (China)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c DALIAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

high quality negative set; MicroRNA; microRNA identification; multi level negative sample selection

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS;

BIOLOGICAL PROCESS; HIGH QUALITY; HUMAN CHROMOSOME 19; MACHINE LEARNING METHODS; MICRORNAS; NEGATIVE SAMPLES; PREDICTIVE PERFORMANCE; REGULATORY PROCESS;

RNA;

MICRORNA;

BIOLOGY; DNA SEQUENCE; GENETICS; HUMAN; PROCEDURES; SUPPORT VECTOR MACHINE;

COMPUTATIONAL BIOLOGY; HUMANS; MICRORNAS; SEQUENCE ANALYSIS, DNA; SUPPORT VECTOR MACHINE;

EID: 84901332555     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2013.146     Document Type: Article

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