Article

Harnessing machine learning models for epigenome to transcriptome association studies

2025-05-15

Abstract excerpt

Understanding how epigenome variation contributes to gene expression in disease and development is a fundamental challenge. Regulatory regions show cell type-specific epigenome activity and differ in their location, size, and distance to their target genes, complicating discovery and analysis. Recent machine learning models have been proposed to address these problems by learning functions for the prediction of ge...

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Literature Corpus work: 06201ae3-1f37-5faf-942b-f51f9c43c48a
DOI: 10.1101/2025.05.09.653095

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