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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Bibliographic Details

Published in:	Analytical chemistry (Washington) Vol. 97; no. 42; p. 23222
Main Authors:	Zhao, Jinhui, He, Jiarui, Guan, Pengwei, Bao, Han, Zhao, Xinjie, Zhao, Chunxia, Qin, Wangshu, Lu, Xin, Xu, Guowang
Format:	Journal Article
Language:	English
Published:	United States 28.10.2025
Subjects:	Autoencoder Data Mining Deep Learning Humans
ISSN:	1520-6882, 1520-6882
Online Access:	Get more information
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