2OMe-LM: predicting 2'-O-methylation sites in human RNA using a pre-trained RNA language model.

Journal: Bioinformatics (Oxford, England)
Published Date: Jul 29, 2025

Abstract

MOTIVATION: 2'-O-methylation (2OMe) is a common post-transcriptional modification in RNA that plays a crucial role in regulating gene expression and is implicated in various biological processes and diseases. Computational methods offer an efficient alternative to the time-consuming and costly experimental identification of 2OMe sites. Recent advancements in RNA pre-trained language models have revolutionized RNA bioinformatics. However, there remains a gap in their application specifically for predicting 2OMe sites.

Authors

  • Qianpei Liu
    School of Computer Science and Engineering, Central South University, Changsha, 410083, China.
  • Min Zeng
    Nephrology Department, Affiliated Hospital of Southern Medical University: Shenzhen Longhua New District People's Hospital, Shenzhen, China.
  • Yiming Li
    Department of Cardiology, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Chengqian Lu
    School of Computer Science and Engineering, Central South University, Changsha 410083, China.
  • Shichao Kan
  • Fei Guo
    School of Electronic Information Engineering, Tianjin University, Tianjin 300072, China. Electronic address: gfjy001@yahoo.com.
  • Min Li
    Hubei Provincial Institute for Food Supervision and Test, Hubei Provincial Engineering and Technology Research Center for Food Quality and Safety Test, Wuhan 430075, China.

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