DeepMirTar: a deep-learning approach for predicting human miRNA targets.

Journal: Bioinformatics (Oxford, England)
PMID: 29868708

Abstract

MOTIVATION: MicroRNAs (miRNAs) are small non-coding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates.

Authors

  • Ming Wen
    College of Chemistry and Chemical Engineering, Central South University, Changsha, People's Republic of China.
  • Peisheng Cong
    School of Chemical Science and Engineering, Tongji University, Shanghai, People's Republic of China.
  • Zhimin Zhang
    School of Control Science and Engineering, Shandong University, Jinan, People's Republic of China. School of Information Technology and Electrical Engineering, University of Queensland, Queensland, Australia.
  • Hongmei Lu
    College of Chemistry and Chemical Engineering, Central South University, Changsha, People's Republic of China.
  • Tonghua Li
    School of Chemical Science and Engineering, Tongji University, Shanghai, People's Republic of China.

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