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

Juan Carlos Martinez-Garcia, Carlos Aguilar-Ibanez, Alberto Soria-Lopez


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.


Systems biology, synthetic biology, tuning of mathematical models, algebraic parameter reconstruction, observer based system identification, synthetic transcriptional networks, cyclic feedback biocircuits

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