KGRDR: a deep learning model based on knowledge graph and graph regularized integration for drug repositioning

KGRDR: a deep learning model based on knowledge graph and graph regularized integration for drug repositioning

Computational drug repositioning, serving as an effective alternative to traditional drug discovery plays a key role in optimizing drug development. This approach can accelerate the development of new therapeutic options while reducing costs and mitigating risks. In this study, we propose a novel de...

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Bibliographic Details
Main Authors: Huimin Luo, Hui Yang, Ge Zhang, Jianlin Wang, Junwei Luo, Chaokun Yan
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Pharmacology
Subjects:
drug repositioning
drug-disease interaction prediction
multi-similarity fusion
biomedical knowledge graph
feature fusion
Online Access:https://www.frontiersin.org/articles/10.3389/fphar.2025.1525029/full
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https://www.frontiersin.org/articles/10.3389/fphar.2025.1525029/full

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