Back to search

Article

A deep learning framework for predicting human essential genes from population and functional genomic data

2021-12-23

Abstract excerpt

Being able to predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve our ability to identify genes associated with genetic disorders. Numerous computational methods have recently been developed to predict human essential genes from population genomic data; however, the existing methods have limited power in pinpointing short essential genes due to the sparsity of polymorphi...

Topics

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

Identifiers and source

Literature Corpus work
f889474a-8b54-5a9e-ae30-6c3c222acd64
DOI
10.1101/2021.12.21.473690
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.
A deep learning framework for predicting human essential genes from population and functional genomic dataDOI 10.1101/2021.12.21.473690
Select a neighboring publication to make it the new centre.