On the Implementation of Quantitative Model Refinement

  • Bogdan Iancu
  • Diana-Elena Gratie
  • Sepinoud Azimi
  • Ion Petre
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8542)

Abstract

The iterative process of adding details to a model while preserving its numerical behavior is called quantitative model refinement, and it has been previously discussed for ODE-based models and for kappa-based models. In this paper, we investigate and compare this approach in three different modeling frameworks: rule-based modeling, Petri nets and guarded command languages. As case study we use a model for the eukaryotic heat shock response that we refine to include the acetylation of the heat shock factor. We discuss how to perform the refinement in each of these frameworks in order to avoid the combinatorial state explosion of the refined model. We conclude that Bionetgen (and rule-based modeling in general) is well-suited for a compact representation of the refined model, Petri nets offer a good solution through the use of colors, while the PRISM refined model may be much larger than the basic model.

Keywords

Quantitative model refinement heat shock response acetylation rule-based modeling Petri nets model checking 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Bogdan Iancu
    • 1
    • 2
    • 3
  • Diana-Elena Gratie
    • 1
    • 2
    • 3
  • Sepinoud Azimi
    • 1
    • 2
    • 3
  • Ion Petre
    • 1
    • 2
    • 3
  1. 1.Computational Biomodeling LaboratoryFinland
  2. 2.Turku Centre for Computer ScienceFinland
  3. 3.Department of ITÅbo Akademi UniversityÅboFinland

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