Sul-BertGRU: an ensemble deep learning method integrating information entropy-enhanced BERT and directional multi-GRU for S-sulfhydration sites prediction.

Journal: Bioinformatics (Oxford, England)
PMID: 39977366

Abstract

MOTIVATION: S-sulfhydration, a crucial post-translational protein modification, is pivotal in cellular recognition, signaling processes, and the development and progression of cardiovascular and neurological disorders, so identifying S-sulfhydration sites is crucial for studies in cell biology. Deep learning shows high efficiency and accuracy in identifying protein sites compared to traditional methods that often lack sensitivity and specificity in accurately locating nonsulfhydration sites. Therefore, we employ deep learning methods to tackle the challenge of pinpointing S-sulfhydration sites.

Authors

  • Xirun Wei
    Department of Information Science and Technology, Dalian Maritime University, Dalian 116026, P.R. China.
  • Qiao Ning
    School of Computer Science and Information Technology, Northeast Normal University, Changchun, 130117, China.
  • Kuiyang Che
    Department of Information Science and Technology, Dalian Maritime University, Dalian 116026, P.R. China.
  • Zhaowei Liu
    Department of Electrical and Computer Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA.
  • Hui Li
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Shikai Guo
    Department of Information Science and Technology, Dalian Maritime University, Dalian 116026, P.R. China.

Keywords

External Resources

Popular Topics
Recent Journals