Estimation & Observation of Stochastic Biochemical Networks

深入了解细胞内生化反应网络的运作是一个重要的问题。了解生化网络的作用机制将有助于我们制定设计原则，系统地构建合成生化网络。不幸的是，细胞内部过程的动态不能直接观察到，限制了我们设计和分析生化网络的能力。我们将研究使用单细胞生成的动态数据在随机生化网络中与估计和观察相关的问题。我们解决状态估计和参数估计问题的方法基于随机化学反应网络理论，适用于通过延时显微镜等实验方法观察到的随机现象占主导地位的系统。PI建议通过实验验证他的方法，将该理论应用于我们在大肠杆菌中构建的合成基因调控网络，并用延时显微镜观察。成功将导致开发新的工具来评估延时显微镜数据和激发实验设计的新技术。该结果将通过引入验证工程网络性能的新方法，影响系统和合成生物学的研究。更广泛的影响pi将开发一个关于本研究中使用的定量技术的教育模块，并将其整合到华盛顿大学现有的系统和合成生物学三门课程序列中。此外，pi将与华盛顿大学的几个项目合作，通过向代表性不足的学生提供研究机会来促进多样性。

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 MeritThe 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 ImpactThe 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.