EPIPDLF: a pretrained deep learning framework for predicting enhancer-promoter interactions.

Journal: Bioinformatics (Oxford, England)
PMID:

Abstract

MOTIVATION: Enhancers and promoters, as regulatory DNA elements, play pivotal roles in gene expression, homeostasis, and disease development across various biological processes. With advancing research, it has been uncovered that distal enhancers may engage with nearby promoters to modulate the expression of target genes. This discovery holds significant implications for deepening our comprehension of various biological mechanisms. In recent years, numerous high-throughput wet-lab techniques have been created to detect possible interactions between enhancers and promoters. However, these experimental methods are often time-intensive and costly.

Authors

  • Zhichao Xiao
    School of Computer Science and Technology, Xidian University, Xi'an 710071, China.
  • Yan Li
    Interdisciplinary Research Center for Biology and Chemistry, Liaoning Normal University, Dalian, China.
  • Yijie Ding
    School of Computer Science and Technology, Tianjin University, Tianjin 300350, China. wuxi_dyj@tju.edu.cn.
  • Liang Yu
    School of Computer Science and Technology, Xidian University, Xi'an, 710071, PR China. Electronic address: lyu@xidian.edu.cn.