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Grey-box techniques for the identification of a controlled gene expression model


F. Parise, J. Ruess, J. Lygeros

European Control Conference (ECC), Strasbourg, France

The aim of this paper is to propose a new computationally efficient technique for the identification of stochastic biochemical networks, using distribution measurements of a cell population. To this end, we first apply existing methods, for grey-box model identification, to the system that describes the evolution of mean and variance of the species, in a benchmark gene expression model. Then a new method, based on the computation of the transfer function, is proposed. This method shows, for the model under consideration, superior performance. The discussion developed in the paper is of interest not only for the gene expression model itself but for the general grey-box identification problem.


Type of Publication:


J. Lygeros

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% Autogenerated BibTeX entry
@InProceedings { ParRue:2014:IFA_4740,
    author={F. Parise and J. Ruess and J. Lygeros},
    title={{Grey-box techniques for the identification of a controlled
	  gene expression model}},
    booktitle={European Control Conference (ECC)},
    address={Strasbourg, France},
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