INFERENCE FOR EVOLUTIONARY AND ECOLOGICAL DYNAMICS

WELCOME SEMINAR IN BIODIVERSITY AND EVOLUTION

I will discuss inference for evolutionary and ecological dynamical systems. This will be done using three examples from my own work, namely single cell breast cancer evolution, epidemiological dynamics of measles and pertussis and inferring selective dynamics of selective sweeps from sequence data. These systems will be used to illustrate the inference of parameters for ecology and evolutionary models using both massive and sparse data, incomplete data and modeling error and uncertainty for complex and massive data sets. The principal focus of my talk will be primarily on the application of innovative technologies to develop personalized medicine for cancer patients using matched experimental and computational platforms. However, in doing this I will introduce broader concepts such as development of workflow for NGS data analysis and its downstream analysis using fast, whole genome simulation-based computational tools such as serial (backward) coalescent analysis.

Daniel Vasco has earned his PhD in evolutionary game theory from the University of Texas at Austin, and has subsequently worked mainly in developing statistical and computational methods for analyzing ecology and evolutionary data sets. Dan has published mathematical biology papers in evolution and epidemiology. However, he has also worked in the field and published papers on both butterfly (Euphydryas) and Drosophila evolutionary biology. Dan has recently joined CIBIO-InBIO to work in the Human Evolutionary Genetics Group.

Image credits: Dan Vasco