Prediction of functional microexons by transfer learning.

Journal: BMC genomics
PMID: 34836511

Abstract

BACKGROUND: Microexons are a particular kind of exon of less than 30 nucleotides in length. More than 60% of annotated human microexons were found to have high levels of sequence conservation, suggesting their potential functions. There is thus a need to develop a method for predicting functional microexons.

Authors

  • Qi Cheng
    Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Bo He
    Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Chengkui Zhao
    College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Hongyuan Bi
    The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
  • Duojiao Chen
    College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Shuangze Han
    College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Haikuan Gao
    College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Weixing Feng
    Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.

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