There have been recent and notable advances in the field of computer-aided tools for synthetic circuit design at the system level. While most approaches focus on providing visualization and simulation capabilities for the users to explore, there is a lack of a much needed end-to-end integrated framework capable of automated optimization of synthetic circuits based on user-defined constraints. The goal of the proposed project is to develop an integrated synthetic biology framework and tools for the automated systems-level design of mixed-signal synthetic circuits. This framework will serve as a computational tool for synthetic biologists and will lay the theoretical foundations for system level synthetic circuit design.
The project will explore a global optimization platform with both approximate and exact techniques for finding the optimal set of parts for any given configuration, which will provide guarantees on the optimality, reproducibility or bounds of the solution. This work will explore matching past validated designs to the circuit at hand, by employing graph-querying and graph partitioning algorithms that will transform the original design to equivalent graphs which can be solved efficiently. This will promote modular and reusable designs, and result in an increase in the level of achievable complexity and a decrease in the cost of construction.
