  While noise is generally associated with uncertainties and often has a
negative connotation in engineering, living organisms have evolved to adapt to
(and even exploit) such uncertainty to ensure the survival of a species or
implement certain functions that would have been difficult or even impossible
otherwise. In this article, we review the role and impact of noise in systems
and synthetic biology, with a particular emphasis on its role in the genetic
control of biological systems, an area we refer to as Cybergenetics. The main
modeling paradigm is that of stochastic reaction networks, whose applicability
goes beyond biology, as these networks can represent any population dynamics
system, including ecological, epidemiological, and opinion dynamics networks.
We review different ways to mathematically represent these systems, and we
notably argue that the concept of ergodicity presents a particularly suitable
way to characterize their stability. We then discuss noise-induced properties
and show that noise can be both an asset and a nuisance in this setting.
Finally, we discuss recent results on (stochastic) Cybergenetics and explore
their relationships to noise. Along the way, we detail the different technical
and biological constraints that need to be respected when designing synthetic
biological circuits. Finally, we discuss the concepts, problems, and solutions
exposed in the article; raise criticisms and concerns about current ideas and
approaches; suggest current (open) problems with potential solutions; and
provide some ideas for future research directions.
