Original paper
Predictive features of gene expression variation reveal mechanistic link with differential expression
Abstract
For most biological processes, organisms must respond to extrinsic cues, while maintaining essential gene expression programmes. Although studied extensively in single cells, it is still unclear how variation is controlled in multicellular organisms. Here, we used a machine-learning approach to identify genomic features that are predictive of genes with high versus low variation in their expression across individuals, using bulk data to remove...
Paper Details
Title
Predictive features of gene expression variation reveal mechanistic link with differential expression
Published Date
Aug 1, 2020
Journal
Volume
16
Issue
8
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