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Parameter identification for stochastic hybrid models of biological interaction networks

Author(s):

E. Cinquemani, R. Porreca, G. Ferrari-Trecate, J. Lygeros
Conference/Journal:

IEEE Conference on Decision and Control
Abstract:

Based on a model of subtilin production by Bacillus subtilis, in this paper we discuss the parameter identification of stochastic hybrid dynamics that are typically found in biological regulatory networks. In accordance with the structure of the model, identification is split in two subproblems: estimation of the genetic network regulating subtilin production from gene expression data, and estimation of population dynamics based on nutrient and population profiles. Techniques for parameter estimation from sparse and irregularly sampled observations are developed and applied to simulated data. Numerical results are provided to show the effectiveness of our methods.

Year:

2007
Type of Publication:

(01)Article
Supervisor:



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% Autogenerated BibTeX entry
@InProceedings { CinEtal:2007:IFA_2868,
    author={E. Cinquemani and R. Porreca and G. Ferrari-Trecate and J. Lygeros},
    title={{Parameter identification for stochastic hybrid models of
	  biological interaction networks}},
    booktitle={IEEE Conference on Decision and Control},
    pages={},
    year={2007},
    address={},
    month=dec,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=2868}
}
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