Abstract
The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.
Highlights
Cells are intrinsically noisy biochemical reactors; low reactant numbers can lead to significant statistical fluctuations in molecule numbers and reaction rates [1,2,3]
On the molecular basis of genetics, each of molecular events is subject to significant thermal fluctuations, genetic mutations and other random noises
Even in cases where population measurements often display significant heterogeneity, overall, these observations suggest that molecular events underlying cellular physiology or transmitting from parent to offspring in evolution are subject to random fluctuations and have led to the proposal of a stochastic model for gene network and biochemical network in general
Summary
Cells are intrinsically noisy biochemical reactors; low reactant numbers can lead to significant statistical fluctuations in molecule numbers and reaction rates [1,2,3]. Fluctuations in number of available polymerases or in any factor that alters the cell growth rate will change reaction rates for all genes It underscores the significance of entropy as a fundamental invariant of biological systems. It is found that the entropy production of the whole network, characterizing the dissipation costs from the combined effects of both landscapes and fluxes, decreases when the fluctuation decreases [37] These observations on entropy can help in designing robust gene networks with intrinsic random parameter fluctuations. How to design a robust synthetic gene network that works properly in a host cell under these intrinsic random parameter uncertainties and external random disturbances is the most important topic in synthetic biology. A stochastic dynamic process is given to discuss robust genetic regulatory networks in the evolutionary process from the viewpoint of nonlinear stochastic regulation theory [50,54,55,56,57,58,59,60]
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