Prediction of LncRNA-protein Interactions Using Auto-Encoder, SE-ResNet Models and Transfer Learning.

Journal: MicroRNA (Shariqah, United Arab Emirates)
PMID:

Abstract

BACKGROUND: Long non-coding RNA (lncRNA) plays a crucial role in various biological processes, and mutations or imbalances of lncRNAs can lead to several diseases, including cancer, Prader-Willi syndrome, autism, Alzheimer's disease, cartilage-hair hypoplasia, and hearing loss. Understanding lncRNA-protein interactions (LPIs) is vital for elucidating basic cellular processes, human diseases, viral replication, transcription, and plant pathogen resistance. Despite the development of several LPI calculation methods, predicting LPI remains challenging, with the selection of variables and deep learning structure being the focus of LPI research.

Authors

  • Jiang Huiwen
    School of Mathematics and Statistics, Qingdao University, Qingdao, Shandong, China.
  • Song Kai
    Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China. songkailw@163.com.