Research Interests
Research Interests: Computational biophysics, biochemistry and proteomics; Modeling and simulation including deterministic and stochastic simulation of metabolism using both kinetic and state simulations; microbial metabolism; statistics, statistical mechanics and statistical proteomics data analysis; Cloud computing and high performance computing.
Projects
Multiscale Modeling of the Circadian Clock of Neurospora spora
In this project we are using a novel method based on statistical thermodynamics to bridge data-poor (parameters for mass action dynamics in metabolism) and data-rich scales (chemical potentials of metabolites, and metabolite, protein & transcript data) to enable predictive modeling across scales from enzymatic reactions (10-3 to 100 s-1) to gene and protein regulation (~20 minutes) to circadian rhythms (24 hours). Specifically, we are:
- Implementing in software that will be available to the community a new approach to the law of mass action that uses chemical potentials rather than rate constants. This approach can be viewed as a time-rescaling of the fast degrees of freedom, resulting in a reduction of the multiscale time-dependence to fewer relative scales. In addition, pseudo-steady state processes can be ‘telescopically’ modeled to address the scale of interest while collapsing faster scales. We will apply this method to the metabolism of Neurospora spora.
- Expanding the multiscale model of metabolism to include the dynamics of regulation of the circadian clock. We will use the implementation of the new method (Aim 1) to understand the relationship between central metabolism and circadian rhythms and to create experimentally testable hypotheses of the feedback from metabolism to the circadian clock.
Mesoscale Imaging and Modeling
Using the methods that we have developed, we are using modeling and simulation in an iterative fashion with multimodal imaging to develop and test hypotheses of how cell structure affects function and vice versa.
We are focusing on Ostreococcus tauri because the small cell size and relatively simple cell architecture is more amenable to an iterative imaging and modeling approach. Specifically, we are testing hypotheses regarding physical principles that relate function and structure. One of our aims is to understand whether the localization of protein complexes within the cell is influenced by diffusional feedback and concentration gradients.
My Links:
W.R. Cannon 