其他摘要：Our concern is the tuning of mathematical models describing rationally designed genetic biocir- cuits. Based on a deterministic lumped continuous-time approach, we propose a tuning methodology combining both exact algebraic parameter reconstruction and nonlinear parameter estimation of a given model supporting the design of a specific genetic biocircuit, i.e. , we bridge the gap between model-based design and implementation as the solution of a systems inverse problem. As a proof of concept, our proposal is constrained to cyclic feedback systems characterizing synthesized transcriptional networks conditioned to display sustained oscillatory behavior. Our proposed methodology is illustrated via computer–based simu- lations involving the tuning of a state–based model describing a well–know cyclic feedback biocircuit: the celebrated repressilator . Tuning in our case is conceived as a procedure to adjust the parameter values of the mathematical model taking into account for this the actual behavior observed from the corresponding synthesized biocircuit.
其他关键词：Systems biology; synthetic biology; tuning of mathematical models; algebraic parameter reconstruction; observer based system identification; synthetic transcriptional networks; cyclic feedback biocircuits.
