Skip to main content
Book cover

International Conference on Algorithms for Computational Biology

AlCoB 2014: Algorithms for Computational Biology pp 95–106Cite as

On the Implementation of Quantitative Model Refinement

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNBI,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

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-07953-0_8
  • Chapter length: 12 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   44.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-07953-0
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   59.99
Price excludes VAT (USA)
Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Back, R., Ishdorj, T., Petre, I.: A petri net formalization of heat shock response model. In: Petre, I., Rozenberg, G. (eds.) Workshop on Natural Computing and Graph Transformations, pp. 19–28 (2008)

    Google Scholar 

  2. Blinov, M.L., Yang, J., Faeder, J.R., Hlavacek, W.S.: Graph theory for of biochemical networks. In: Priami, C., Ingólfsdóttir, A., Mishra, B., Riis Nielson, H. (eds.) Transactions on Computational Systems Biology VII. LNB, vol. 4230, pp. 89–106. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  3. Czeizler, E., Rogojin, V., Petre, I.: The phosphorylation of the heat shock factor as a modulator for the heat shock response. In: Proceedings of the 9th International Conference on Computational Methods in Systems Biology, pp. 9–23. ACM (2011)

    Google Scholar 

  4. Danos, V., Feret, J., Fontana, W., Harmer, R., Krivine, J.: Rule-based modelling and model perturbation. In: Priami, C., Back, R.-J., Petre, I. (eds.) Transactions on Computational Systems Biology XI. LNCS, vol. 5750, pp. 116–137. Springer, Heidelberg (2009)

    CrossRef  Google Scholar 

  5. Faeder, J., Blinov, M., Goldstein, B., Hlavacek, W.: Rule-based modeling of biochemical networks. Complexity 10(4), 22–41 (2005)

    CrossRef  Google Scholar 

  6. Gratie, D., Iancu, B., Azimi, S., Petre, I.: Quantitative model refinement in four different frameworks, with applications to the heat shock response. Tech. Rep. 1067, TUCS (2013)

    Google Scholar 

  7. Harmer, R.: Rule-based modelling and tunable resolution. EPTCS 9, 65–72 (2009)

    Google Scholar 

  8. Heath, J.K., Kwiatkowska, M., Norman, G., Parker, D., Tymchyshyn, O.: Probabilistic model checking of complex biological pathways. In: Priami, C. (ed.) CMSB 2006. LNB, vol. 4210, pp. 32–47. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  9. Hinton, A., Kwiatkowska, M., Norman, G., Parker, D.: Prism: A tool for automatic verification of probabilistic systems. In: Hermanns, H., Palsberg, J. (eds.) TACAS 2006. LNCS, vol. 3920, pp. 441–444. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  10. Iancu, B., Czeizler, E., Czeizler, E., Petre, I.: Quantitative refinement of reaction models. IJUC 8(5-6), 529–550 (2012)

    Google Scholar 

  11. Iancu, B., Gratie, D., Azimi, S., Petre, I.: Computational modeling of the eukaryotic heat shock response: The bionetgen implementation, the petri net implementation and the prism implementation (2013), http://combio.abo.fi/research/computational-modeling-of-the-eukaryotic-heat-shock-response/

  12. Kitano, H.: Systems biology: a brief overview. Science 295(5560), 1662–1664 (2002)

    CrossRef  Google Scholar 

  13. Kline, M., Morimoto, R.: Repression of the heat shock factor 1 transcriptional activation domain is modulated by constitutive phosphorylation. Molecular and cellular biology 17(4), 2107–2115 (1997)

    Google Scholar 

  14. Klipp, E., Herwig, R., Kowald, A., Wierling, C., Lehrach, H.: Systems biology in practice: Concepts, implementation and application. Wiley-Vch (2005)

    Google Scholar 

  15. Kwiatkowska, M., Norman, G., Parker, D.: Quantitative analysis with the probabilistic model checker prism. Electronic Notes in Theoretical Computer Science 153(2), 5–31 (2006)

    CrossRef  Google Scholar 

  16. Kwiatkowska, M., Norman, G., Parker, D.: PRISM 4.0: Verification of probabilistic real-time systems. In: Gopalakrishnan, G., Qadeer, S. (eds.) CAV 2011. LNCS, vol. 6806, pp. 585–591. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  17. Liu, F., Heiner, M., Yang, M.: An efficient method for unfolding colored petri nets. In: Laroque, C., Himmelspach, J., Pasupathy, R., Rose, O., Uhrmacher, A. (eds.) Proceedings of the Winter Simulation Conference, vol. 295. Winter Simulation Conference (2012)

    Google Scholar 

  18. Mizera, A., Czeizler, E., Petre, I.: Self-assembly models of variable resolution. In: Priami, C., Petre, I., de Vink, E. (eds.) Transactions on Computational Systems Biology XIV. LNCS, vol. 7625, pp. 181–203. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  19. Murphy, E., Danos, V., Feret, J., Krivine, J., Harmer, R.: Rule Based Modelling and Model Refinement. In: Elements of Computational Systems Biology, pp. 83–114. Wiley Book Series on Bioinformatics, John Wiley & Sons, Inc. (2010)

    Google Scholar 

  20. Petre, I., Mizera, A., Hyder, C., Meinander, A., Mikhailov, A., Morimoto, R., Sistonen, L., Eriksson, J., Back, R.: A simple mass-action model for the eukaryotic heat shock response and its mathematical validation. Natural Computing 10(1), 595–612 (2011)

    CrossRef  MathSciNet  Google Scholar 

  21. Raman, K., Chandra, N.: Systems biology. Resonance 15(2), 131–153 (2010)

    Google Scholar 

  22. Rieger, T., Morimoto, R., Hatzimanikatis, V.: Mathematical modeling of the eukaryotic heat-shock response: Dynamics of the hsp70 promoter. Biophysical Journal 88(3), 1646–1658 (2005)

    CrossRef  Google Scholar 

  23. Shi, Y., Mosser, D., Morimoto, R.: Molecular chaperones as hsf1-specific transcriptional repressors. Genes & Development 12(5), 654–666 (1998)

    CrossRef  Google Scholar 

  24. Westerheide, S., Anckar, J., Stevens Jr., S., Sistonen, L., Morimoto, R.: Stress-inducible regulation of heat shock factor 1 by the deacetylase sirt1. Science Signalling 323(5917), 1063–1066 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computational Biomodeling Laboratory, Finland

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

  2. Turku Centre for Computer Science, Finland

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

  3. Department of IT, Åbo Akademi University, Joukahainengatan 3-5, 20520, Åbo, Finland

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

Authors
  1. Bogdan Iancu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diana-Elena Gratie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sepinoud Azimi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ion Petre
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Research Group on Mathematical Linguistics, Rovira i Virgili University, Avinguda Catalunya, 35, 43002, Tarragona, Spain

    Adrian-Horia Dediu & Carlos Martín-Vide & 

  2. Fachbereich 07, Institut für Informatik, Justus-Liebig-Universität, Arndtstraße 2, 35392, Gießen, Germany

    Bianca Truthe

Rights and permissions

Reprints and Permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Iancu, B., Gratie, DE., Azimi, S., Petre, I. (2014). On the Implementation of Quantitative Model Refinement. In: Dediu, AH., Martín-Vide, C., Truthe, B. (eds) Algorithms for Computational Biology. AlCoB 2014. Lecture Notes in Computer Science(), vol 8542. Springer, Cham. https://doi.org/10.1007/978-3-319-07953-0_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-07953-0_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07952-3

  • Online ISBN: 978-3-319-07953-0

  • eBook Packages: Computer ScienceComputer Science (R0)