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In-silico control of complex stochastic biological systems is a promising area of cybergenetics, which provides enabling theoretical and practical tools for the real-time control of living cells with digital computers. We demonstrate here that simple proportional-integral control laws can be used to control both the mean and the variance of the expression product of a simple gene expression network. Extensions to more general unimolecular networks, networks with input delay, and to a gene expression network involving protein dimerization are also provided. Notably, no moment closure method is used for dealing with the network with dimerization. The obtained results are illustrated by simulations. [ABSTRACT FROM AUTHOR]

9780821852286 Randomization, relaxation, and complexity in polynomial equation solving; proceedings. Banff Int'l Research Station Workshop on Randomization, Relaxation, and Complexity (2010: Branff, Canada). Ed. by Leonid Gurvits et al. American [...]