VTrans: A VAE-Based Pre-Trained Transformer Method for Microbiome Data Analysis

Predicting the survival outcomes and assessing the risk of patients play a pivotal role in comprehending the microbial composition across various stages of cancer. With the ongoing advancements in deep learning, it has been substantiated that deep learning holds the potential to analyze patient surv...

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Veröffentlicht in:	Journal of computational biology Jg. 32; H. 9; S. 850
Hauptverfasser:	Shi, Xinyuan, Zhu, Fangfang, Min, Wenwen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.09.2025
Schlagworte:	Algorithms Computational Biology - methods Deep Learning Humans Microbiota - genetics Neoplasms - genetics Neoplasms - microbiology Neoplasms - mortality saliency map Transformer multihead-co-attention variational autoencoder microbiome data pretraining
ISSN:	1557-8666, 1557-8666
Online-Zugang:	Weitere Angaben
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