A Bayesian walker coupled with a computational workflow that generates the micro-evolution of SARS-CoV-2 and makes predictions of new mutations that can emerge.

Abstract excerpt

In this work, a Bayesian walker was constructed that generates mutations that are more prone as per UNIPROT variant data. The Bayesian walker was used to search the mutational landscape of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) and a computational workflow was followed to evaluate whether a particular mutation would satisfy natural selection's fitness criteria. For SARS-CoV-2, the empirical...

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