Predicting miRNA-disease associations using an ensemble learning framework with resampling method.

Journal: Briefings in bioinformatics
Published Date: Jan 17, 2022

Abstract

MOTIVATION: Accumulating evidences have indicated that microRNA (miRNA) plays a crucial role in the pathogenesis and progression of various complex diseases. Inferring disease-associated miRNAs is significant to explore the etiology, diagnosis and treatment of human diseases. As the biological experiments are time-consuming and labor-intensive, developing effective computational methods has become indispensable to identify associations between miRNAs and diseases.

Authors

  • Qiguo Dai
    School of Computer Science and Engineering, Dalian Minzu University, 116600, Dalian, China.
  • Zhaowei Wang
    School of Computer Science and Engineering, Dalian Minzu University, 116600, Dalian, China.
  • Ziqiang Liu
    School of Computer Science and Engineering, Dalian Minzu University, 116600, Dalian, China.
  • Xiaodong Duan
    SEAC Key Laboratory of Big Data Applied Technology, Dalian Minzu University, 116600, Dalian, China.
  • Jinmiao Song
    College of Information Science and Engineering, Xinjiang University, Urumqi, Xinjiang, China.
  • Maozu Guo
    School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China.

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