Back to search

Article

Predicting gene expression from histone marks using chromatin deep learning models depends on histone mark function, regulatory distance and cellular states

2024-03-29

Abstract excerpt

To understand the complex relationship between histone mark activity and gene expression, recent advances have used in silico predictions based on large-scale machine learning models. However, these approaches have omitted key contributing factors like cell state, histone mark function or distal effects, that impact the relationship, limiting their findings. Moreover, downstream use of these models for new biolog...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
63296bd3-de37-5ec2-909c-cb93759800b7
DOI
10.1101/2024.03.29.587323
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Predicting gene expression from histone marks using chromatin deep learning models depends on histone mark function, regulatory distance and cellular statesDOI 10.1101/2024.03.29.587323
Select a neighboring publication to make it the new centre.