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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Bibliographic Details

Published in:	Frontiers in pharmacology Vol. 15; p. 1484639
Main Authors:	Ye, Sheng, Wang, Jue, Zhu, Mingmin, Yuan, Sisi, Zhuo, Linlin, Chen, Tiancong, Gao, Jinjian
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media S.A 22.10.2024
Subjects:	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
Online Access:	Get full text
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