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Structure estimation for unate Boolean models of gene regulation networks

Christian Breindl 1 Madalena Chaves 2 Jean-Luc Gouzé 2 Frank Allgöwer 1 
2 BIOCORE - Biological control of artificial ecosystems
LOV - Laboratoire d'océanographie de Villefranche, CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique
Abstract : This paper deals with the reconstruction of the interaction structure of a gene regulation network from qualitative data in a Boolean framework. The problem in this setup is to find update functions which are in agreement with the data. As the search space grows exponentially with the system size but data are rare, large uncertainties remain in the reconstructed networks. In order to attenuate this problem, we propose to restrict the search space to the biologically meaningful class of unate functions. Using sign-representations, the problem of exploring this reduced search space is transformed into a linear feasibility problem. The sign-representation furthermore allows to incorporate robustness considerations and gives rise to a new measure which can be used to further reduce the uncertainties. The proposed methodology is demonstrated with a Boolean apoptosis signaling model.
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Contributor : Jean-Luc Gouzé Connect in order to contact the contributor
Submitted on : Friday, July 26, 2013 - 10:30:39 AM
Last modification on : Monday, May 16, 2022 - 3:33:56 AM

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Christian Breindl, Madalena Chaves, Jean-Luc Gouzé, Frank Allgöwer. Structure estimation for unate Boolean models of gene regulation networks. Proc. 16th IFAC Symposium on System Identification, 2012, Brussels, Belgium. pp.1725-1730, ⟨10.3182/20120711-3-BE-2027.00278⟩. ⟨hal-00848397⟩



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