Identifiability of stochastically modelled reaction networks

@article{Enciso2021IdentifiabilityOS,
  title={Identifiability of stochastically modelled reaction networks},
  author={Germ{\'a}n A. Enciso and Radek Erban and Jinsu Kim},
  journal={European Journal of Applied Mathematics},
  year={2021},
  volume={32},
  pages={865 - 887}
}
Chemical reaction networks describe interactions between biochemical species. Once an underlying reaction network is given for a biochemical system, the system dynamics can be modelled with various mathematical frameworks such as continuous-time Markov processes. In this manuscript, the identifiability of the underlying network structure with a given stochastic system dynamics is studied. It is shown that some data types related to the associated stochastic dynamics can uniquely identify the… 
2 Citations
Identifiability analysis for stochastic differential equation models in systems biology
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This work provides an accessible introduction to identifiability analysis and demonstrates how existing ideas for analysis of ODE models can be applied to stochastic differential equation (SDE) models through four practical case studies.

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