Seminar by John Barton (University of Pittsburgh)
Learning about evolution from time-series sequence data, from the lab to the globe
Abstract: In recent years, massive sequencing efforts have allowed us to observe evolution in real time. My lab develops mathematical methods, inspired by statistical physics, to use this data to understand evolutionary dynamics. In this talk I’ll give a few examples of our work studying evolution at vastly divergent scales. First, I’ll discuss short-term evolution in deep mutational scanning experiments, where we’ve used new theoretical approaches to interpret data much more reliably than existing state-of-the-art methods. Second, I’ll talk about how we’ve used epidemiological models to study the evolution of SARS-CoV-2 over the course of the pandemic, uncovering mutational drivers of increased viral transmission.