ACE2 polymorphisms and individual susceptibility to SARS-CoV-2 infection: insights from an in silico study M Calcagnile et al, BIORXIV, April 24, 2020

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 Coronavirus

ACE2 polymorphisms and individual susceptibility to SARS-CoV-2 infection: insights from an in silico study
M Calcagnile et al, BIORXIV, April 24, 2020

A transcription regulatory network within the ACE2 locus may promote a pro-viral environment for SARS-CoV-2 by modulating expression of host factors.
T Fadason et al, BIORXIV, April 25, 2020

ACE2 Homo-dimerization, Human Genomic variants and Interaction of Host Proteins Explain High Population Specific Differences in Outcomes of COVID19
S Sharma et al, BIORXIV, April 24, 2020

Prediction of novel virus-host interactions by integrating clinical symptoms and protein sequences
WL Wei et al, BIORXIV, April 25, 2020

Rapid, sensitive, full genome sequencing of Severe Acute Respiratory Syndrome Virus Coronavirus 2 (SARS-CoV-2)
CR Paden et a, BIORXIV, April 24, 2020

Heterogeneous expression of the SARS-Coronavirus-2 receptor ACE2 in the human respiratory tract
ME Ortiz-Bezara et al, BIORXIV April 23, 2020

Preliminary support for a 'dry swab, extraction free' protocol for SARS-CoV-2 testing via RT-qPCR
S Srivatsan et al, BIORXIV, April 23, 2020

TARGETED PROTEOMICS FOR THE DETECTION OF SARS-COV-2 PROTEINS.
BIORXIV, April 23, 2020

The genomic variation landscape of globally-circulating clades of SARS-CoV-2 defines a genetic barcoding scheme
Q Guan et al, BioRXIV, April 23, 2020

UK Biobank-COVID-19 Data Release
UK Biobank, April 2020

Crucial new data on the health of 500,000 UK Biobank participants are being made available to scientists tackling the COVID-19 emergency. The pioneering UK Biobank resource, which follows the health of 500,000 volunteers in England, Scotland and Wales, is well placed to help answer a wide range of questions about the pandemic .

Why The True Fatality Rate Of COVID-19 Is Hard To Estimate
All Things Considered, NPR, April 24, 2020

Why Forecasting COVID-19 Deaths in the US is Critical
CDC, April 2020 

Forecasts based on the use of statistical or mathematical models (subsequently referred to as “models”) aim to predict changes in national- and state-level cumulative reported COVID-19 deaths for the next four weeks.