Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N. A2-025
P.O. Box 19024
Seattle, WA 98109-1024
Web page: http://www.smoldyn.org/andrews/index.html
On the job market: My staff scientist position at the FHCRC is scheduled to end after June. I'm looking for work in which I can teach physical science, contribute to interesting research and, hopefully, pursue my research interests. Here is my CV pdf.
I am fascinated by how the highly structured macroscopic world of living organisms is built from the stochastic microscopic world of individual molecules.
I am developing modeling algorithms and software that can simulate cell biology systems with spatial and stochastic detail. Initially, I developed methods for accurately simulating molecular diffusion, chemical reactions, and surface interactions. They are implemented in the Smoldyn software, which has become the most widely cited particle-based simulator. Currently, I am focusing on methods for simulating filaments and macromolecular complexes because these are additional essential biological components, but are hard to model with current tools. This research is providing the tools that help members of the systems biology community explore the foundations of spatial order in cell biology. It also addresses many interesting physical chemistry problems, such as how to quantify reaction rates in two-dimensional systems.
How much information can cells transmit through their signaling systems? And how have the systems evolved to improve information transmission? I am pursuing these questions in cell signaling research with my advisor, Roger Brent. In particular, we are investigating the mechanisms that can enable cells to exhibit "dose-response alignment", which is a phenomon in which multiple stages of cell signaling pathways are similarly sensitive to stimuli. We are also investigating the information transmission implications of different dose-response relationships. This work investigates the ability of cells to accurately convey inforamtion using intrinsically noisy biochemical mechanisms.