Drug repositioning based on heterogeneous networks and variational graph autoencoders

Predicting new therapeutic effects (drug repositioning) of existing drugs plays an important role in drug development. However, traditional wet experimental prediction methods are usually time-consuming and costly. The emergence of more and more artificial intelligence-based drug repositioning metho...

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Veröffentlicht in:	Frontiers in pharmacology Jg. 13; S. 1056605
Hauptverfasser:	Lei, Song, Lei, Xiujuan, Liu, Lian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media S.A 21.12.2022
Schlagworte:	COVID-19 drug repositioning graph representation learning heterogeneous network Pharmacology variational graph autoencoders COVID-19 graph representation learning drug repositioning heterogeneous network variational graph autoencoders
ISSN:	1663-9812, 1663-9812
Online-Zugang:	Volltext
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