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Erschienen in: Natural Computing 2/2011

01.06.2011

Petri net representation of multi-valued logical regulatory graphs

verfasst von: C. Chaouiya, A. Naldi, E. Remy, D. Thieffry

Erschienen in: Natural Computing | Ausgabe 2/2011

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Abstract

Relying on a convenient logical representation of regulatory networks, we propose a generic method to qualitatively model regulatory interactions in the standard elementary and coloured Petri net frameworks. Logical functions governing the behaviours of the components of logical regulatory graphs are efficiently represented by Multivalued Decision Diagrams, which are also at the basis of the translation of logical models in terms of Petri nets. We further delineate a simple strategy to sort trajectories through the introduction of priority classes (in the logical framework) or priority functions (in the Petri net framework). We also focus on qualitative behaviours such as multistationarity or sustained oscillations, identified as specific structures in state transition graphs (for logical models) or in marking graphs (in Petri nets). Regulatory circuits are known to be at the origin of such properties. In this respect, we present a method that allows to determine the functionality contexts of regulatory circuits, i.e. constraints on external regulator states enabling the corresponding dynamical properties. Finally, this approach is illustrated through an application to the modelling of a regulatory network controlling T lymphocyte activation and differentiation.

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Fußnoten
1
Multigraphs are also called pseudographs.
 
2
\({{\mathbb{N}}}^*\) is the set of non-zero natural numbers.
 
3
For \(x\in{\mathbb{Z}}, sign(x)=+1\) if x > 0, − 1 if x < 0, 0 otherwise.
 
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Metadaten
Titel
Petri net representation of multi-valued logical regulatory graphs
verfasst von
C. Chaouiya
A. Naldi
E. Remy
D. Thieffry
Publikationsdatum
01.06.2011
Verlag
Springer Netherlands
Erschienen in
Natural Computing / Ausgabe 2/2011
Print ISSN: 1567-7818
Elektronische ISSN: 1572-9796
DOI
https://doi.org/10.1007/s11047-010-9178-0

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