Estimation & Observation of Stochastic Biochemical Networks

University Of Washington, Seattle WA

Investigators

Abstract

Gaining insight into the operation of biochemical reaction networks in the cell is an important problem. Understanding the mechanisms by which biochemical networks function will help us develop the design principles to systematically build synthetic biochemical networks. Unfortunately, the dynamics of processes inside cells cannot be observed directly, limiting our ability to design and analyze biochemical networks. We will investigate problems related to estimation and observation in stochastic biochemical networks using dynamic data generated by single cells. Our approach to the problems of state estimation and parameter estimation is based on the theory of stochastic chemical reaction networks, applicable to systems observed through experimental methods like time-lapse microscopy in which stochastic phenomena dominate. Intellectual Merit The PI proposes to test his approach experimentally by applying the theory to synthetic gene regulatory networks that we construct in E. coli and observe with time-lapse microscopy. Success will lead to the development of new tools for evaluating time-lapse microscopy data and motivate new techniques for experiment design. The results will impact research in systems and synthetic biology by introducing new methods for verifying the performance of engineered networks. Broader Impact The PIs will develop an educational module on the quantitative techniques used in this research and integrate it into the already existing three-course sequence on systems and synthetic biology offered at the University of Washington. In addition, the PIs will work with several University of Washington programs that promote diversity by offering research opportunities to under-represented students.