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Natural Computing
Erschienen in: Natural Computing 4/2009

01.12.2009

Rule-based programming for integrative biological modeling

Application to the modeling of the λ phage genetic switch

verfasst von: Olivier Michel, Antoine Spicher, Jean-Louis Giavitto

Erschienen in: Natural Computing | Ausgabe 4/2009

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Abstract

Systems biology aims at integrating processes at various time and spatial scales into a single and coherent formal description to allow computer modeling. In this context, we focus on rule-based modeling and its integration in the domain-specific language MGS . Through the notions of topological collections and transformations, MGS allows the modeling of biological processes at various levels of description. We validate our approach through the description of various models of the genetic switch of the λ phage, from a very simple biochemical description of the process to an individual-based model on a Delaunay graph topology. This approach is a first step into providing the requirements for the emerging field of spatial systems biology which integrates spatial properties into systems biology.
Vorheriger Artikel A photosynthetic process modelled by a metabolic P system

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Fußnoten
1
The Web site of the project is http://​mgs.​spatial-computing.​org.
 
2
Evaluating the stochastic constants is one of the hardest task in stochastic simulations of biochemical reactions. The interested reader should refer to (De Cock et al. 2003; Zhang et al. 2003) that describe two experiences in that field.
 
3
An even more realistic behavior is obtained by considering models involving gene cII and cIII (Arkin et al. 1998).
 
4
Because of the lack of space, we do not include here the MGS code for this model. Nevertheless, the code of all the examples given in this article is available upon request from the authors.
 
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Metadaten
Titel
Rule-based programming for integrative biological modeling
Application to the modeling of the λ phage genetic switch
verfasst von
Olivier Michel
Antoine Spicher
Jean-Louis Giavitto
Publikationsdatum
01.12.2009
Verlag
Springer Netherlands
Erschienen in
Natural Computing / Ausgabe 4/2009
Print ISSN: 1567-7818
Elektronische ISSN: 1572-9796
DOI
https://doi.org/10.1007/s11047-008-9105-9

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