A Machine Learning Framework to Identify the Correlates of Disease Severity in Acute Arbovirus Infection

Vanessa Herder(MRC University of Glasgow Centre for Virus Research), Massimo Palmarini(MRC University of Glasgow Centre for Virus Research)
bioRxiv (Cold Spring Harbor Laboratory)
February 24, 2024
10.1101/2024.02.23.581333
Cited by 0

Related Papers

Genomic epidemiology reveals multiple introductions of SARS-CoV-2 from mainland Europe into Scotland
|Nature Microbiology|2020|129
Phenotypic evolution of SARS-CoV-2 spike during the COVID-19 pandemic
|Nature Microbiology|2025|18
The Timing and Magnitude of the Type I Interferon Response Are Correlated with Disease Tolerance in Arbovirus Infection
|mBio|2023|14
Correlates of disease severity in bluetongue as a model of acute arbovirus infection
|PLoS Pathogens|2024|5
Timing and magnitude of the type-I interferon response are determinants of disease tolerance in arbovirus infection
|bioRxiv (Cold Spring Harbor Laboratory)|2022|1