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Publications of Eduardo D. Sontag jointly with S. Bruno
and D. Del Vecchio.
Stochastic analysis of genetic feedback controllers to reprogram a pluripotency gene regulatory network.
In Proc. 2019 Automatic Control Conference,
chemical master equations.
Cellular reprogramming is traditionally accomplished through an open loop control approach, wherein key transcription factors are injected in cells to steer a gene regulatory network toward a pluripotent state. Recently, a closed loop feedback control strategy was proposed in order to achieve more accurate control. Previous analyses of the controller were based on deterministic models, ignoring the substantial stochasticity in these networks, Here we analyze the Chemical Master Equation for reaction models with and without the feedback controller. We computationally and analytically investigate the performance of the controller in biologically relevant parameter regimes where stochastic effects dictate system dynamics. Our results indicate that the feedback control approach still ensures reprogramming even when analyzed using a stochastic model.
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