Knowledge graph convolutional network with heuristic search for drug repositioning

X Du, X Sun, M Li - Journal of Chemical Information and Modeling, 2024 - ACS Publications
Drug repositioning is a strategy of repurposing approved drugs for treating new indications,
which can accelerate the drug discovery process, reduce development costs, and lower the …

MiRAGE: mining relationships for advanced generative evaluation in drug repositioning

A Hassanali Aragh, P Givehchian… - Briefings in …, 2024 - academic.oup.com
Motivation Drug repositioning, the identification of new therapeutic uses for existing drugs, is
crucial for accelerating drug discovery and reducing development costs. Some methods rely …

Automatic collaborative learning for drug repositioning

Y Wang, Y Meng, C Zhou, X Tang, P Zeng… - … Applications of Artificial …, 2025 - Elsevier
Drug repositioning seeks to identify new therapeutic uses for existing drugs, accelerating
development and reducing costs. While traditional wet lab experiments are costly …

Heterogeneous graph contrastive learning with gradient balance for drug repositioning

H Cui, M Duan, H Bi, X Li, X Hou… - Briefings in …, 2025 - academic.oup.com
Drug repositioning, which involves identifying new therapeutic indications for approved
drugs, is pivotal in accelerating drug discovery. Recently, to mitigate the effect of label …

Draw+: network-based computational drug repositioning with attention walking and noise filtering

JH Park, YR Cho - Health Information Science and Systems, 2025 - Springer
Purpose Drug repositioning, a strategy that repurposes already-approved drugs for novel
therapeutic applications, provides a faster and more cost-effective alternative to traditional …

DRTerHGAT: A drug repurposing method based on the ternary heterogeneous graph attention network

H He, J Xie, D Huang, M Zhang, X Zhao, Y Ying… - Journal of Molecular …, 2024 - Elsevier
Drug repurposing is an effective method to reduce the time and cost of drug development.
Computational drug repurposing can quickly screen out the most likely associations from …

Cdpmf-Dda: Contrastive Deep Probabilistic Matrix Factorization for Drug-Disease Association Prediction

XF Tang, Y Hou, YJ Meng, Z Wang, C Lu, J Lv… - Available at SSRN … - papers.ssrn.com
Drug-disease association (DDA) prediction aims to identify new therapeutic uses for existing
medications. However, existing graph contrastive learning appr oaches typically rely on …