Type-dependent irreversible stochastic spin models for biochemical reaction networks
نویسندگان
چکیده
We describe an approach to model biochemical reaction networks at the level of promotion-inhibition circuitry through a class of stochastic spin models that depart from the usual chemical kinetics setup and includes spatial and temporal density fluctuations in a most natural way. A particular but otherwise generally applicable choice for the microscopic transition rates of the models also makes them of independent interest. To illustrate the formalism, we investigate some stationary state properties of the repressilator, a synthetic three-gene network of transcriptional regulators that possesses a rich dynamical behaviour.
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