International Conference on Computational Methods in Systems Biology

CMSB 2015: Computational Methods in Systems Biology pp 239-250

Modeling of Resilience Properties in Oscillatory Biological Systems Using Parametric Time Petri Nets

  • Alexander Andreychenko
  • Morgan Magnin
  • Katsumi Inoue
Conference paper

DOI: 10.1007/978-3-319-23401-4_20

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9308)
Cite this paper as:
Andreychenko A., Magnin M., Inoue K. (2015) Modeling of Resilience Properties in Oscillatory Biological Systems Using Parametric Time Petri Nets. In: Roux O., Bourdon J. (eds) Computational Methods in Systems Biology. CMSB 2015. Lecture Notes in Computer Science, vol 9308. Springer, Cham


Automated verification of living organism models allows us to gain previously unknown knowledge about underlying biological processes. In this paper, we show the benefits to use parametric time Petri nets in order to analyze precisely the dynamic behavior of biological oscillatory systems. In particular, we focus on the resilience properties of such systems. This notion is crucial to understand the behavior of biological systems (e.g. the mammalian circadian rhythm) that are reactive and adaptive enough to endorse major changes in their environment (e.g. jet-lags, day-night alternating work-time). We formalize these properties through parametric TCTL and demonstrate how changes of the environmental conditions can be tackled to guarantee the resilience of living organisms. In particular, we are able to discuss the influence of various perturbations, e.g. artificial jet-lag or components knock-out, with regard to quantitative delays. This analysis is crucial when it comes to model elicitation for dynamic biological systems. We demonstrate the applicability of this technique using a simplified model of circadian clock.


Parametric time Petri net Resilience Biological oscillators Model checking 

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Alexander Andreychenko
    • 1
  • Morgan Magnin
    • 2
    • 3
  • Katsumi Inoue
    • 2
  1. 1.Saarland UniversitySaarbruckenGermany
  2. 2.National Institute of InformaticsChiyoda-ku, TokyoJapan
  3. 3.IRCCyN UMR CNRS 6597 (Institut de Recherche en Communications et Cybernétique de Nantes)LUNAM Université, École Centrale de NantesNantes Cedex 3France

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