Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance

Background Enormous clinical and biomedical researches have demonstrated that microbes are crucial to human health. Identifying associations between microbes and diseases can not only reveal potential disease mechanisms, but also facilitate early diagnosis and promote precision medicine. Due to the...

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Veröffentlicht in:	BMC biology Jg. 21; H. 1; S. 294 - 15
Hauptverfasser:	Zhu, Huan, Hao, Hongxia, Yu, Liang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 20.12.2023 Springer Nature B.V BMC
Schlagworte:	Ablation Accuracy Alzheimer's disease Bacteria Biomedical and Life Sciences Colorectal cancer Colorectal Neoplasms Crohn's disease Embedding Experiments Graphical representations Humans Life Sciences Medical research Microbe-disease association Microorganisms Neighborhoods Neoplasms Neural networks Neurodegenerative diseases Performance evaluation Perturbation Precision Medicine Regularization methods Research Article Variational graph autoencoder Wasserstein distance XGBoost Microbe-disease association Wasserstein distance Variational graph autoencoder XGBoost
ISSN:	1741-7007, 1741-7007
Online-Zugang:	Volltext
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