Back to search

Article

COVIDOUTCOME – Estimating COVID Severity Based on Mutation Signatures in the SARS-CoV-2 Genome

2021-04-02

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Introduction</h4> Numerous studies demonstrate frequent mutations in the genome of SARS-CoV-2. Our goal was to statistically link mutations to severe disease outcome. <h4>Methods</h4> We used an automated machine learning approach where 1,594 viral genomes with available clinical follow-up data were used as the training set (797 “severe” and 797 “mild”). The best algorithm, based on random...

Topics

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

Identifiers and source

Literature Corpus work
a515b276-ca26-51cb-82a1-c6a0cd2fa7f7
DOI
10.1101/2021.04.01.438063
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.
COVIDOUTCOME – Estimating COVID Severity Based on Mutation Signatures in the SARS-CoV-2 GenomeDOI 10.1101/2021.04.01.438063
Select a neighboring publication to make it the new centre.