Approximation and inference methods for stochastic biochemical kinetics — a tutorial review

@inproceedings{Constantino2017ApproximationAI,
  title={Approximation and inference methods for stochastic biochemical kinetics — a tutorial review},
  author={Pedro H. Constantino and Michail Vlysidis and Christian Fleck and Chris Sherlock and Andrew Golightly and Colin S. Gillespie and Rui Zhu and Elijah Roberts},
  year={2017}
}
Stochastic fluctuations of molecule numbers are ubiquitous in biological systems. Important examples include gene expression and enzymatic processes in living cells. Such systems are typically modelled as chemical reaction networks whose dynamics are governed by the chemical master equation. Despite its simple structure, no analytic solutions to the chemical master equation are known for most systems. Moreover, stochastic simulations are computationally expensive, making systematic analysis… CONTINUE READING

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