Solving stochastic gene expression models using queueing theory: a tutorial review

J. Szavits-Nossan, Ramon Grima

Research output: Contribution to journalReview articlepeer-review

Abstract / Description of output

Stochastic models of gene expression are typically formulated using the chemical master equation, which can be solved exactly or approximately using a repertoire of analytical methods. Here, we provide a tutorial review of an alternative approach based on queueing theory that has rarely been used in the literature of gene expression. We discuss the interpretation of six types of infinite-server queues from the angle of stochastic single-cell biology and provide analytical expressions for the stationary and nonstationary distributions and/or moments of mRNA/protein numbers and bounds on the Fano factor. This approach may enable the solution of complex models that have hitherto evaded analytical solution.

Original languageEnglish
Pages (from-to)1034-1057
Number of pages29
JournalBiophysical Journal
Volume123
Issue number9
Early online date9 Apr 2024
DOIs
Publication statusPublished - 7 May 2024

Keywords / Materials (for Non-textual outputs)

  • Gene expression
  • Queueing theory
  • Stochastic Processes

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