Skip to main content

On the Hybrid Composition and Simulation of Heterogeneous Biochemical Models

  • Conference paper
Book cover Computational Methods in Systems Biology (CMSB 2013)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8130))

Included in the following conference series:

  • 1593 Accesses

Abstract

Models of biochemical systems presented as a set of formal reaction rules with kinetic expressions can be interpreted with different semantics: as either deterministic Ordinary Differential Equations, stochastic continuous-time Markov Chains, Petri nets or Boolean transition systems. While the formal composition of reaction models can be syntactically defined as the (multiset) union of the reactions, the hybrid composition of models in different formalisms is a largely open issue. In this paper, we show that the combination of reaction rules with conditional events, as the ones already present in SBML, does provide the expressive power of hybrid automata and can be used in a non standard way to give meaning to the hybrid composition of heterogeneous models of biochemical processes. In particular, we show how hybrid differential-stochastic and hybrid differential-Boolean models can be compiled and simulated in this framework, through the specification of a high-level interface for composing heterogeneous models. This is illustrated by a hybrid stochastic-differential model of bacteriophage T7 infection, and by a reconstruction of the hybrid model of the mammalian cell cycle regulation of Singhania et al. as the composition of a Boolean model of cell cycle phase transitions and a differential model of cyclin activation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ahmad, J., Bernot, G., Comet, J.-P., Lime, D., Roux, O.: Hybrid modelling and dynamical analysis of gene regulatory networks with delays. ComplexUs 3, 231–251 (2006)

    Article  Google Scholar 

  2. Ahmad, J., Roux, O., Bernot, G., Comet, J.-P., Richard, A.: Analysing formal models of genetic regulatory networks with delays. International Journal of Bioinformatics Research and Applications 4(3), 240–262 (2008)

    Article  Google Scholar 

  3. Alfonsi, A., Cancès, E., Turinici, G., di Ventura, B., Huisinga, W.: Adaptive simulation of hybrid stochastic and deterministic models for biochemical systems. ESAIM: Proc. 14, 1–13 (2005)

    MATH  Google Scholar 

  4. Alur, R., Belta, C., Ivančić, F., Kumar, V., Mintz, M., Pappas, G.J., Rubin, H., Schug, J.: Hybrid Modeling and Simulation of Biomolecular Networks. In: Di Benedetto, M.D., Sangiovanni-Vincentelli, A.L. (eds.) HSCC 2001. LNCS, vol. 2034, pp. 19–32. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  5. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.: Gene ontology: tool for the unification of biology. Nature Genetics 25, 25–29 (2000)

    Article  Google Scholar 

  6. Bockmayr, A., Courtois, A.: Using hybrid concurrent constraint programming to model dynamic biological systems. In: Stuckey, P.J. (ed.) ICLP 2002. LNCS, vol. 2401, pp. 85–99. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  7. Calzone, L., Fages, F., Soliman, S.: BIOCHAM: An environment for modeling biological systems and formalizing experimental knowledge. Bioinformatics 22(14), 1805–1807 (2006)

    Article  Google Scholar 

  8. Chaouiya, C., Remy, E., Thieffry, D.: Petri net modelling of biological regulatory networks. Journal of Discrete Algorithms 6(2), 165–177 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  9. Egerstedt, M., Mishra, B. (eds.): HSCC 2008. LNCS, vol. 4981. Springer, Heidelberg (2008)

    Google Scholar 

  10. Fages, F., Gay, S., Jovanovska, D., Rizk, A., Soliman, S.: BIOCHAM v3.4 Reference Manual. INRIA (2012)

    Google Scholar 

  11. Fages, F., Soliman, S.: Abstract interpretation and types for systems biology. Theoretical Computer Science 403(1), 52–70 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  12. Feinberg, M.: Mathematical aspects of mass action kinetics. In: Lapidus, L., Amundson, N.R. (eds.) Chemical Reactor Theory: A Review, ch. 1, pp. 1–78. Prentice-Hall (1977)

    Google Scholar 

  13. Ghosh, R., Tomlin, C.J.: Lateral inhibition through delta-notch signaling: A piecewise affine hybrid model. In: Di Benedetto, M.D., Sangiovanni-Vincentelli, A.L. (eds.) HSCC 2001. LNCS, vol. 2034, pp. 232–246. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  14. Gilbert, D., Heiner, M., Lehrack, S.: A unifying framework for modelling and analysing biochemical pathways using petri nets. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 200–216. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  15. Gillespie, D.T.: General method for numerically simulating stochastic time evolution of coupled chemical-reactions. Journal of Computational Physics 22, 403–434 (1976)

    Article  MathSciNet  Google Scholar 

  16. Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry 81(25), 2340–2361 (1977)

    Article  Google Scholar 

  17. Gillespie, D.T.: Approximate accelerated stochastic simulation of chemically reacting systems. Journal of Chemical Physics 115(4), 1716–1733 (2001)

    Article  Google Scholar 

  18. Gillespie, D.T.: Deterministic limit of stochastic chemical kinetics. The Journal of Physical Chemistry B 113(6), 1640–1644 (2009)

    Article  Google Scholar 

  19. Hellander, A., Lotstedt, P.: Hybrid method for the chemical master equation. Journal of Computational Physics 227(1), 100–122 (2007)

    Article  MATH  Google Scholar 

  20. Henzinger, T.A.: The theory of hybrid automata. In: Proceedings of the 11th Annual Symposium on Logic in Computer Science (LICS), pp. 278–292. IEEE Computer Society Press (1996), An extended version appeared in Verification of Digital and Hybrid Systems

    Google Scholar 

  21. Henzinger, T.A., Ho, P.-H., Wong-Toi, H.: HYTECH: A model checker for hybrid systems. In: Grumberg, O. (ed.) CAV 1997. LNCS, vol. 1254, pp. 460–463. Springer, Heidelberg (1997)

    Chapter  Google Scholar 

  22. Henzinger, T.A., Mikeev, L., Mateescu, M., Wolf, V.: Hybrid numerical solution of the chemical master equation. In: Proceedings of the 8th International Conference on Computational Methods in Systems Biology, CMSB 2010, pp. 55–65. ACM, New York (2010)

    Google Scholar 

  23. Hucka, M., et al.: The systems biology markup language (SBML): A medium for representation and exchange of biochemical network models. Bioinformatics 19(4), 524–531 (2003)

    Article  Google Scholar 

  24. Ideker, T., Galitski, T., Hood, L.: A new approach to decoding life: Systems biology. Annual Review of Genomics and Human Genetics 2, 343–372 (2001)

    Article  Google Scholar 

  25. Kanehisa, M., Goto, S.: KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research 28(1), 27–30 (2000)

    Article  Google Scholar 

  26. Kiehl, T.R., Mattheyses, R.M., Simmons, M.K.: Hybrid simulation of cellular behavior. Bioinformatics 20(3), 316–322 (2004)

    Article  Google Scholar 

  27. Kwiatkowska, M., Norman, G., Parker, D.: Using probabilistic model checking in systems biology. SIGMETRICS Performance Evaluation Review 35(4), 14–21 (2008)

    Article  Google Scholar 

  28. Maler, O., Batt, G.: Approximating continuous systems by timed automata. In: Fisher, J. (ed.) FMSB 2008. LNCS (LNBI), vol. 5054, pp. 77–89. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  29. Matsuno, H., Doi, A., Nagasaki, M., Miyano, S.: Hybrid petri net representation of gene regulatory network. In: Proceedings of the 5th Pacific Symposium on Biocomputing, pp. 338–349 (2000)

    Google Scholar 

  30. Noël, V.: Modèles réduits et hybrides de réseaux de réactions biochimiques – Applications à la modélisation du cycle cellulaire. PhD thesis, Université de Rennes 1 (2012)

    Google Scholar 

  31. Salis, H., Kaznessis, Y.N.: Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions. The Journal of Chemical Physics 122(5), 54103 (2005)

    Article  Google Scholar 

  32. Salis, H., Sotiropoulos, V., Kaznessis, Y.N.: Multiscale hy3s: Hybrid stochastic simulation for supercomputers. BMC Bioinformatics 7(1), 93 (2006)

    Article  Google Scholar 

  33. Singania, R., Sramkoski, R.M., Jacooberger, J.W., Tyson, J.J.: A hybrid model of mammalian cell cycle regulation. PLOS Computational Biology 7(2) (February 2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chiang, K., Fages, F., Jiang, JH., Soliman, S. (2013). On the Hybrid Composition and Simulation of Heterogeneous Biochemical Models. In: Gupta, A., Henzinger, T.A. (eds) Computational Methods in Systems Biology. CMSB 2013. Lecture Notes in Computer Science(), vol 8130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40708-6_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40708-6_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40707-9

  • Online ISBN: 978-3-642-40708-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics