Back to search

Article

Hierarchical Markov Random Field model captures spatial dependency in gene expression, demonstrating regulation via the 3D genome

2019-12-17

Abstract excerpt

<h4> A bstract </h4> HiC technology has revealed many details about the eukaryotic genome’s complex 3D architecture. It has been shown that the genome is separated into organizational structures which are associated with gene expression. However, to the best of our knowledge, no studies have quantitatively measured the level of gene expression in the context of the 3D genome. Here we present a novel model that...

Topics

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

Identifiers and source

Literature Corpus work
352722d7-70bf-5fda-a439-c69cd652b0cd
DOI
10.1101/2019.12.16.878371
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.
Hierarchical Markov Random Field model captures spatial dependency in gene expression, demonstrating regulation via the 3D genomeDOI 10.1101/2019.12.16.878371
Select a neighboring publication to make it the new centre.