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Bayesian model selection for the yeast GATA-factor network: a comparison of computational approaches

Author(s):

A. Milias, R. Porreca, S. Summers, J. Lygeros
Conference/Journal:

IEEE Conference on Decision and Control, Atlanta, Georgia, USA
Abstract:

A common situation in System Biology is to use several alternative models of a given biochemical system, each with a different structure reflecting different biological hypotheses. These models then have to be ranked according to their ability to reproduce experimental data. In this paper, we use Bayesian model selection to test four alternative models of the yeast GATA-factor genetic network. We employ three different computational methods to calculate the necessary probabilities and evaluate their performance for medium-scale biochemical systems.

Year:

2010
Type of Publication:

(01)Article
Supervisor:



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% Autogenerated BibTeX entry
@InProceedings { MilEtal:2010:IFA_3640,
    author={A. Milias and R. Porreca and S. Summers and J. Lygeros},
    title={{Bayesian model selection for the yeast GATA-factor network:
	  a comparison of computational approaches}},
    booktitle={IEEE Conference on Decision and Control},
    pages={},
    year={2010},
    address={Atlanta, Georgia, USA},
    month=dec,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=3640}
}
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