YModPred: an interpretable prediction method for multi-type RNA modification sites in S. cerevisiae based on deep learning.

Journal: BMC biology
Published Date: Aug 29, 2025

Abstract

BACKGROUND: RNA post-transcriptional modifications involve the addition of chemical groups to RNA molecules or alterations to their local structure. These modifications can change RNA base pairing, affect thermal stability, and influence RNA folding, thereby impacting alternative splicing, translation, cellular localization, stability, and interactions with proteins and other molecules. Accurate prediction of RNA modification sites is essential for understanding modification mechanisms.

Authors

  • Chunyan Ao
    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, P. R. China.
  • Mengting Niu
    School of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, China. yunzeer@gmail.com.
  • Quan Zou
  • Liang Yu
    School of Computer Science and Technology, Xidian University, Xi'an, 710071, PR China. Electronic address: lyu@xidian.edu.cn.
  • Yansu Wang
    Postdoctoral Innovation Practice Base, Shenzhen Polytechnic, China.

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