Article

Unsupervised deep learning with variational autoencoders applied to breast tumor genome-wide DNA methylation data with biologic feature extraction

2018-10-02

Abstract excerpt

Recent advances in deep learning, particularly unsupervised approaches, have shown promise for furthering our biological knowledge through their application to gene expression datasets, though applications to epigenomic data are lacking. Here, we employ an unsupervised deep learning framework with variational autoencoders (VAEs) to learn latent representations of the DNA methylation landscape from three independen...

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Literature Corpus work: 90efee4c-d3e5-59ad-adbc-3b5ff48c4e0d
DOI: 10.1101/433763

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