Opportunities for mathematical analysis in microbiology


Microbiology is largely an empirical science, with results more likely to be communicated through cartoons than equations and models. As a result, experiments are not designed to gather data that would support modeling efforts. In general, the benefits of theory and modeling are not obvious to microbiologists, while mathematicians are not aware of the opportunities to contribute to this research. In this talk, I will discuss several areas where we and others are starting to bridge this gap, explicitly designing experiments to develop and validate quantitative models that can be used for engineering design. Examples include kinetic models of biomolecular networks or microbial community dynamics, network models of horizontal gene transfer, and statistical models of microbial evolution.

Biography:  Josh got bachelor’s degrees in chemical engineering and biology from MIT, followed by doctoral research in protein and metabolic engineering at Caltech. There, he worked with Christina Smolke, Frances Arnold, and Richard Murray, receiving a PhD in 2012 in Bioengineering. He was an NSF Graduate Research Fellow, a Nordic Research Fellow with Jens Nielsen at the Chalmers Institute of Technology, and a visiting researcher at Stanford. He then moved to Boston, where he was a Kirschstein Fellow of the NIGMS, studying microbial evolution after horizontal gene transfer with Chris Marx at Harvard Organismic and Evolutionary Biology and Eric Alm at MIT Biological Engineering. In 2015, he came to ORNL as a Wigner Fellow, transitioning to Staff Scientist in 2018, where his team is developing genetic and evolutionary methods to discover and optimize metabolic pathways in microbes and microbial communities.

Last Updated: May 28, 2020 - 4:06 pm