MethylNet: an automated and modular deep learning approach for DNA methylation analysis
Abstract
Background DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from multiple hypothesis testing and multi-collinearity due to the high-dimensional, continuous, interacting and non-linear nature of the data. Deep learning analyses have shown much promise to study disease...
Paper Details
Title
MethylNet: an automated and modular deep learning approach for DNA methylation analysis
Published Date
Mar 17, 2020
Journal
Volume
21
Issue
1
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