Bridging the Gap Between Model-Based Design and Reliable Implementation of Feedback-Based Biocircuits: A Systems Inverse Problem Approach.

Our concern is the tuning of mathematicalmodels describing rationally designed genetic biocircuits.Based on a deterministic lumped continuous-timeapproach, we propose a tuning methodology combiningboth exact algebraic parameter reconstruction andnonlinear parameter estimation of a given modelsupporting the design of a specific genetic biocircuit,i.e., we bridge the gap between model-based designand implementation as the solution of a systems inverseproblem. As a proof of concept, our proposal isconstrained to cyclic feedback systems characterizingsynthesized transcriptional networks conditioned todisplay sustained oscillatory behavior. Our proposedmethodology is illustrated via computer–based simulationsinvolving the tuning of a state–based modeldescribing a well–know cyclic feedback biocircuit: thecelebrated repressilator. Tuning in our case is conceivedas a procedure to adjust the parameter values ofthe mathematical model taking into account for thisthe actual behavior observed from the correspondingsynthesized biocircuit.