Ensemble learning can significantly improve human microRNA target prediction

Methods

Volumn 69, Issue 3, 2014, Pages 220-229

  Yu, Seunghak ^a,b   Kim, Juho ^a   Min, Hyeyoung ^c   Yoon, Sungroh ^a  

^a Seoul National University   (South Korea)

^b Korea University   (South Korea)

^c Chung Ang University   (South Korea)

Author keywords

Algorithm; Machine learning; MicroRNA; Sequence analysis; Target prediction

Indexed keywords

MICRORNA; MESSENGER RNA;

ARTICLE; CLASSIFIER; COMPARATIVE STUDY; COMPUTER MODEL; COMPUTER PREDICTION; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; DATA BASE; HUMAN; INTERACTIONS WITH RNA; LEARNING ALGORITHM; MACHINE LEARNING; MEASUREMENT ACCURACY; METHODOLOGY; PREDICTIVE VALUE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS; STACKING BASED RNA INTERACTION LEARNER ENSEMBLE; STATISTICAL ANALYSIS; ALGORITHM; COMPUTER SIMULATION; GENETICS; PROCEDURES;

ALGORITHMS; COMPUTER SIMULATION; HUMANS; MICRORNAS; RNA, MESSENGER; SEQUENCE ANALYSIS, RNA;

EID: 84927128873     PISSN: 10462023     EISSN: 10959130     Source Type: Journal    
DOI: 10.1016/j.ymeth.2014.07.008     Document Type: Article

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