Back to search

Article

Genome-wide regulatory model from MPRA data predicts functional regions, eQTLs, and GWAS hits

2017-02-20

Abstract excerpt

Massively-parallel reporter assays (MPRA) enable unprecedented opportunities to test for regulatory activity of thousands of regulatory sequences. However, MPRA only assay a subset of the genome thus limiting their applicability for genome-wide functional annotations. To overcome this limitation, we have used existing MPRA datasets to train a machine learning model that uses DNA sequence information, regulatory mo...

Topics

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

Identifiers and source

Literature Corpus work
91c5baa4-50e1-58db-8cd3-83e20faa704d
DOI
10.1101/110171
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.
Genome-wide regulatory model from MPRA data predicts functional regions, eQTLs, and GWAS hitsDOI 10.1101/110171
Select a neighboring publication to make it the new centre.