Graph generative and adversarial strategy-enhanced node feature learning and self-calibrated pairwise attribute encoding for prediction of drug-related side effects

Background: Inferring drug-related side effects is beneficial for reducing drug development cost and time. Current computational prediction methods have concentrated on graph reasoning over heterogeneous graphs comprising the drug and side effect nodes. However, the various topologies and node attri...

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Vydané v:	Frontiers in pharmacology Ročník 14; s. 1257842
Hlavní autori:	Xuan, Ping, Xu, Kai, Cui, Hui, Nakaguchi, Toshiya, Zhang, Tiangang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Frontiers Media S.A 04.09.2023
Predmet:	graph convolutional autoencoder graph generative and adversarial strategy Pharmacology representation-level attention self-calibrated pairwise attributes topologies and attributes from heterogeneous graphs
ISSN:	1663-9812, 1663-9812
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