MAVGAE: a multimodal framework for predicting asymmetric drug-drug interactions based on variational graph autoencoder

Drug-drug interactions refer to the phenomena wherein the potency, duration, or effectiveness of one or multiple drugs undergo alterations of varying degrees as a result of their concurrent or sequential usage. The accurate identification of potential drug interactions plays a pivotal role in mitiga...

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Veröffentlicht in:	Computer methods in biomechanics and biomedical engineering Jg. 28; H. 7; S. 1098 - 1110
Hauptverfasser:	Deng, Zengqian, Xu, Jie, Feng, Yinfei, Dong, Liangcheng, Zhang, Yuanyuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Taylor & Francis 19.05.2025
Schlagworte:	Algorithms Artificial intelligence asymmetric drug-drug interaction Autoencoder Drug Interactions multimodal variational autoencoder multimodal asymmetric drug-drug interaction Artificial intelligence variational autoencoder
ISSN:	1025-5842, 1476-8259, 1476-8259
Online-Zugang:	Volltext
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