Fusing graph transformer with multi-aggregate GCN for enhanced drug–disease associations prediction

Fusing graph transformer with multi-aggregate GCN for enhanced drug–disease associations prediction

Abstract Background Identification of potential drug–disease associations is important for both the discovery of new indications for drugs and for the reduction of unknown adverse drug reactions. Exploring the potential links between drugs and diseases is crucial for advancing biomedical research an...

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Bibliographic Details
Main Authors:	Shihui He, Lijun Yun, Haicheng Yi
Format:	Article
Language:	English
Published:	BMC 2024-02-01
Series:	BMC Bioinformatics
Subjects:	Drug repositioning Drug–disease associations Graph transformer Graph neural networks Neural collaborative filtering
Online Access:	https://doi.org/10.1186/s12859-024-05705-w

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