MKAN-MMI: empowering traditional medicine-microbe interaction prediction with masked graph autoencoders and KANs

The growing microbial resistance to traditional medicines necessitates in-depth analysis of medicine-microbe interactions (MMIs) to develop new therapeutic strategies. Widely used artificial intelligence models are limited by sparse observational data and prevalent noise, leading to over-reliance on...

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Vydané v:	Frontiers in pharmacology Ročník 15; s. 1484639
Hlavní autori:	Ye, Sheng, Wang, Jue, Zhu, Mingmin, Yuan, Sisi, Zhuo, Linlin, Chen, Tiancong, Gao, Jinjian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Media S.A 22.10.2024
Predmet:	artificial intelligence models kolmogorov-arnold networks (KANs) masked graph autoencoder (mask GAE) medicine-microbe interactions (MMIs) Pharmacology traditional medicine (TM) artificial intelligence models masked graph autoencoder (mask GAE) medicine-microbe interactions (MMIs) kolmogorov-arnold networks (KANs) traditional medicine (TM)
ISSN:	1663-9812, 1663-9812
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