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 Probability Surveys > Vol. 16 (2019) open journal systems 

Mathematical models of gene expression

Philippe S. Robert, INRIA de Paris

In this paper we analyze the equilibrium properties of a large class of stochastic processes describing the fundamental biological process within bacterial cells, the production process of proteins. Stochastic models classically used in this context to describe the time evolution of the numbers of mRNAs and proteins are presented and discussed. An extension of these models, which includes elongation phases of mRNAs and proteins, is introduced. A convergence result to equilibrium for the process associated to the number of proteins and mRNAs is proved and a representation of this equilibrium as a functional of a Poisson process in an extended state space is obtained. Explicit expressions for the first two moments of the number of mRNAs and proteins at equilibrium are derived, generalizing some classical formulas. Approximations used in the biological literature for the equilibrium distribution of the number of proteins are discussed and investigated in the light of these results. Several convergence results for the distribution of the number of proteins at equilibrium are in particular obtained under different scaling assumptions.

AMS 2000 subject classifications: Primary 60G55; Secondary 92C40.

Keywords: Stochastic models, gene expression, marked Poisson point processes.

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Robert, Philippe S., Mathematical models of gene expression, Probability Surveys, 16, (2019), 277-332 (electronic). DOI: 10.1214/19-PS332.


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