MODAPro: Explainable Heterogeneous Networks with Variational Graph Autoencoder for Mining Disease-Specific Functional Molecules and Pathways from Omics Data

The rapid growth of multiomics data has revolutionized our ability to investigate disease mechanisms, yet significant challenges persist in achieving meaningful integration due to inherent data heterogeneity, characteristic sparsity patterns, and the persistent interpretability gap in current analyt...

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Vydané v:	Analytical chemistry (Washington) Ročník 97; číslo 42; s. 23222
Hlavní autori:	Zhao, Jinhui, He, Jiarui, Guan, Pengwei, Bao, Han, Zhao, Xinjie, Zhao, Chunxia, Qin, Wangshu, Lu, Xin, Xu, Guowang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 28.10.2025
Predmet:	Autoencoder Data Mining Deep Learning Humans
ISSN:	1520-6882, 1520-6882
On-line prístup:	Zistit podrobnosti o prístupe
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