miTAR: a hybrid deep learning-based approach for predicting miRNA targets.

Journal: BMC bioinformatics
Published Date: Feb 27, 2021

Abstract

BACKGROUND: microRNAs (miRNAs) have been shown to play essential roles in a wide range of biological processes. Many computational methods have been developed to identify targets of miRNAs. However, the majority of these methods depend on pre-defined features that require considerable efforts and resources to compute and often prove suboptimal at predicting miRNA targets.

Authors

  • Tongjun Gu
    Bioinformatics, Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, USA. tgu@ufl.edu.
  • Xiwu Zhao
    Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.
  • William Bradley Barbazuk
    Bioinformatics, Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, USA.
  • Ji-Hyun Lee
    Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Korea.

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