Abstract:Markov jump processes constitute the central class of Chemical Reaction Network models used to account for the intrinsic stochasticity observed in the dynamics of molecular species abundance throughout Molecular Biology. These models are specified in a parametric form, and their identification requires the use of inference procedures, and in particular the estimation of the Fisher Information. Here, a fast and accurate computation method is introduced in the case of partial observations at discrete time points… Show more
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