Model-based design of synthetic networks

While significant progress had been made in synthetic biology over the last decade, researchers still lack a reliable tool for computeraided design of gene regulatory networks (GRN), one that can reveal the full range of nonlinear dynamic behaviors in a single run. Here, we propose a network design cycle that utilizes both the qualitative simulation of GRNs modeled by a class of ODE equations and the intrinsic stochasticity of regulation to ultimately design a network that exhibits a specified desired behavior with the highest probability. Finally, to show the power and ease of our method, we perform a case study with a real-life benchmark gene network to get a synthetic oscillator.