Optimizing module matching for synthetic gene circuit design automation

An integral challenge in automated synthetic circuit design is to select the optimal set of parts to populate an abstract circuit topology, so that the circuit behavior best approximates the desired one. In some cases, it is also possible to reuse multi-part constructs, or modules that have been already built and experimentally characterized. Efficient part and module matching algorithms are essential to systematically search the solution space and their significance will only increase in the following years due to the projected explosion in part libraries and circuit complexity. Here, we present a matching method based on an iterative node traversal algorithm that can guarantee optimality in the set selection. Results from the integration of the proposed method in the SBROME CAD tool show scalable performance and optimal set selection in a database of experimentally constructed parts and modules. This work represents a fundamental departure from the previous heuristic-based part matching methods [1][2][3][4][5] and is a step towards maximizing efficiency in synthetic circuit design.