Learning about natural selection in populations evolving under recombination, with an application to epistasis between SARS-CoV-2 genes

The distribution over genotypes in a population is shaped by evolution, a process driven by natural selection, mutations, genetic drift (finite-N noise) and recombination. It was discovered by Motoo Kimura in the mid-60ies that if recombination is the fastest mechanism, the stationary distribution over genotypes is of the Ising/Potts type from equilibrium statistical mechanics. With the advances in genome sequencing it is now in many cases possible to sample the distribution over genotypes. It is hence possible to leverage methodological advances in statistical physics and AI to infer properties of natural selection from data. I will describe how this works in simple models of evolving populations, and as applied to a large collection of SARS-CoV-2 genomes

Zoom: https://us02web.zoom.us/j/83829318876?pwd=Z2pqbUtIMEV3NUQvU0hpakp0NGtsUT09

Meeting ID: 838 2931 8876

Passcode: 797728

Contact details:

Tobias Galla

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