Bayesian Inference of Dependent Population Dynamics in Coalescent Models

Explore Bayesian inference techniques for analyzing dependent population dynamics in coalescent models through this informative conference talk from the Computational Genomics Summer Institute. Delve into the research presented by Jaehee Kim, Assistant Professor at Cornell University, as she discusses advanced statistical methods for studying population genetics. Gain insights into the application of these techniques to track the evolution of SARS-CoV-2 and evaluate the effects of spike mutations on transmissibility and pathogenicity. Learn about the challenges and recent advancements in coalescent modeling, with references to related papers that provide deeper context on Bayesian inference in population dynamics and its relevance to understanding viral evolution.

Jaehee Kim | Bayesian Inference of Dependent Population Dynamics in Coalescent Models | CGSI 2022