On the Implementation of Quantitative Model Refinement

Bogdan Iancu, Diana-Elena Gratie, Sepinoud Azimi Rashti, Ion Petre

    Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

    5 Citations (Scopus)


    The iterative process of adding details to a model while preserving its numerical behavior is calledquantitative model refinement, and it has been previously discussed for ODE-based models and forkappa-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.
    Original languageUndefined/Unknown
    Title of host publicationAlgorithms for Computational Biology
    EditorsA Dediu, C Vide, B Truthe
    ISBN (Electronic)978-3-319-07953-0
    ISBN (Print)978-3-319-07952-3
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    Eventconference; 2014-07-01; 2014-07-03 - Tarragona, Spain
    Duration: 1 Jul 20143 Jul 2014


    Conferenceconference; 2014-07-01; 2014-07-03

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