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Learning the structure of genetic network dynamics: A geometric approach

Author(s):

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

IFAC World Congress, Milano, pp. 11654-11659
Abstract:

Genetic networks govern the behavior of living cells in response to changes in the environment, and determine growth, replication, and death of cells. They are composed of genes, i.e. pieces of the DNA strand, that regulate the expression of each other. As a result, protein synthesis is orchestrated by complex biochemical interactions among genes and their products. Modern technologies for the time-course measurement of gene expression, such as gene reporter systems, allow one to step from pure topological modelling of gene networks to the modelling of the interaction dynamics. However, this requires setting up a dynamical model whose structure and parameters are typically unknown or uncertain. Databased identi cation of an accurate model is challenging due to the size of the family of possible model alternatives. Yet, a priori biological knowledge may be exploited so as to ameliorate the complexity of the problem.

Year:

2011
Type of Publication:

(01)Article
Supervisor:

J. Lygeros

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% Autogenerated BibTeX entry
@InProceedings { PorEtal:2011:IFA_3942,
    author={R. Porreca and E. Cinquemani and J. Lygeros and G. Ferrari-Trecate},
    title={{Learning the structure of genetic network dynamics: A
	  geometric approach}},
    booktitle={IFAC World Congress},
    pages={11654--11659},
    year={2011},
    address={Milano},
    month=aug,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=3942}
}
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