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


Milias-Argeitis, Andreas; Porreca, Riccardo; Summers, Sean; Lygeros, John (2010). Bayesian model selection for the yeast GATA-factor network: a comparison of computational approaches. In: 49th IEEE Conference on Decision and Control, Atlanta, GA, 15 December 2010 - 17 December 2010, 3379-84.

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.

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.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > YeastX
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:17 December 2010
Deposited On:04 Jul 2013 09:57
Last Modified:30 Sep 2018 07:17
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/CDC.2010.5717307

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