Integrate multi-omics data with biological interaction networks using Multi-view Factorization AutoEncoder (MAE)

Integrate multi-omics data with biological interaction networks using Multi-view Factorization AutoEncoder (MAE)

Abstract Background Comprehensive molecular profiling of various cancers and other diseases has generated vast amounts of multi-omics data. Each type of -omics data corresponds to one feature space, such as gene expression, miRNA expression, DNA methylation, etc. Integrating multi-omics data can lin...

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Bibliographic Details
Main Authors: Tianle Ma, Aidong Zhang
Format: Article
Language:English
Published: BMC 2019-12-01
Series:BMC Genomics
Subjects:
Multi-omics data
Biological interaction networks
Deep learning
Multi-view learning
Autoencoder
Data integration
Online Access:https://doi.org/10.1186/s12864-019-6285-x

Internet

https://doi.org/10.1186/s12864-019-6285-x

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