EDLmAPred: ensemble deep learning approach for mRNA mA site prediction.

Journal: BMC bioinformatics
Published Date: May 29, 2021

Abstract

BACKGROUND: As a common and abundant RNA methylation modification, N6-methyladenosine (mA) is widely spread in various species' transcriptomes, and it is closely related to the occurrence and development of various life processes and diseases. Thus, accurate identification of mA methylation sites has become a hot topic. Most biological methods rely on high-throughput sequencing technology, which places great demands on the sequencing library preparation and data analysis. Thus, various machine learning methods have been proposed to extract various types of features based on sequences, then occupied conventional classifiers, such as SVM, RF, etc., for mA methylation site identification. However, the identification performance relies heavily on the extracted features, which still need to be improved.

Authors

  • Lin Zhang
    Laboratory of Molecular Translational Medicine, Centre for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, Clinical Research Center for Birth Defects of Sichuan Province, West China Second Hospital, Sichuan University, Chengdu, Sichuan, 610041, China. Electronic address: zhanglin@scu.edu.cn.
  • Gangshen Li
    Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, 221116, China.
  • Xiuyu Li
    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
  • Honglei Wang
    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
  • Shutao Chen
    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
  • Hui Liu
    Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

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