Back to search

Article

Modeling gene regulatory perturbations via deep learning from high-throughput reporter assays

2026-03-31

Abstract excerpt

Assessing likely variant effects on phenotypes is of critical importance in diagnostic settings, and while much progress has been made in interpreting genic mutations based on our understanding of coding sequence, noncoding variants can be much more challenging to reliably interpret based on DNA sequence alone. High-throughput reporter assays such as STARR-seq and MPRA have shown utility in experimentally measurin...

Topics

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

Identifiers and source

Literature Corpus work
8d25d483-4472-5f60-b1e7-6dd0ac805f68
DOI
10.64898/2026.03.27.714770
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.
Modeling gene regulatory perturbations via deep learning from high-throughput reporter assaysDOI 10.64898/2026.03.27.714770
Select a neighboring publication to make it the new centre.