The basic modeling of discrete character evolution has been a staple of evolutionary biology for several decades, but similar techniques are now seeing more frequent application in biomedical settings. The software I will discuss (corHMM) was developed to model discrete characters evolving along a phylogenetic tree while allowing for changes in the evolutionary process to depend on unknown/ unobserved hidden states. It has allowed biologists to answer questions related to rates of evolution, presence or absence of dependent processes, or reconstruct the sequence of ancestral evolutionary events. After describing some of the technical details of discrete character evolution, I will demonstrate how this modeling framework can be applied to study the evolution of antibiotic resistance.

Tool link: https://github.com/thej022214/corHMM

This presentation will be held in 2036 Palmer Commons. There will also be a remote viewing option via Zoom.