MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder

MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder

Abstract Background Integrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative computational methods capable of managing high-dimensional and heterogeneous datasets are required to unlock the full potential of such rich and diverse...

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Bibliographic Details
Main Authors: Xiaohui Yao, Xiaohan Jiang, Haoran Luo, Hong Liang, Xiufen Ye, Yanhui Wei, Shan Cong
Format: Article
Language:English
Published: BMC 2024-03-01
Series:BioData Mining
Subjects:
Multi-omics integration
Auxiliary classifier
Autoencoder
Attention mechanism
Trustworthy learning
Disease prediction
Online Access:https://doi.org/10.1186/s13040-024-00360-6

Internet

https://doi.org/10.1186/s13040-024-00360-6

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