Research Goals: In order to ask, ‘how sensitive is evolution?’, and whether it will unfold differently when selection pressures slightly differ, we need to sensitively quantify how cells respond to subtle perturbations.
I perform experiments in yeast to sensitively quantify the impact of subtle perturbations on intracellular physiology and cell growth rate. Perturbations studied so far include single adaptive point mutations, tiny environmental shifts, mild inhibition of a protein folding chaperone, and misfolding of a superfluous protein.
Ultimately, I want to know how properties of cells (e.g. induction dynamics of a signaling pathway or the structure of a gene network) shape the way genes and proteins can evolve. Then I want to use this knowledge to improve our ability to predict phenotype from genotype.
Results from my experiments teach us about evolutionary processes, and also about cell biology and quantitative genetics. My research is at the intersection of multiple disciplines, so I consider myself an evolutionary systems biologist.
In addition to performing experiments, I spend a lot of time analyzing data using a variety of statistical tools (linear models, Bayesian methods) implemented in python or the R programming language.
I am currently a postdoctoral researcher in the Petrov Lab at Stanford University. I continue to work closely with my previous postdoctoral advisor, Mark Siegal, at the Center for Genomics and Systems Biology at New York University. Prior to this I was a graduate student with Daniel Hartl and D. Allan Drummond at Harvard University.