Identifiability of stochastically modelled reaction networks

  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},
  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
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