Title: “Inferring natural selection on and within protein networks by coupling network- and population-scale models with genomic data”

Abstract: My group aims to understand how mutations and natural selection drive the evolution of the complex biomolecular networks that underlie life. To do so, we build detailed computational models to compare with genomic and experimental data. I will first discuss recent “bottom-up” work in which we are using sensitivity analysis of biochemically-detailed network models to predict rates of protein evolution. Contrary to much recent work, our results suggest that natural selection on protein function is as important as selection on protein biophysics. I will also discuss recent “top-down” work in which we are fitting novel models of demographic history and natural selection to population genetic data. Here, our results quantify the differences in purifying selection between populations and connect selection in natural populations with recent mutation scanning experiments.