Drug-target interaction prediction with collaborative contrastive learning and adaptive self-paced sampling strategy.

Journal: BMC biology
PMID:

Abstract

BACKGROUND: Drug-target interaction (DTI) prediction plays a pivotal role in drug discovery and drug repositioning, enabling the identification of potential drug candidates. However, most previous approaches often do not fully utilize the complementary relationships among multiple biological networks, which limits their ability to learn more consistent representations. Additionally, the selection strategy of negative samples significantly affects the performance of contrastive learning methods.

Authors

  • Zhen Tian
    School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People's Republic of China.
  • Yue Yu
    Department of Mathematics, Lehigh University, Bethlehem, PA, USA.
  • Fengming Ni
    Department of Gastroenterology, The First Hospital of Jilin University, Changchun, 130021, China. n_fengming@jlu.edu.cn.
  • Quan Zou