Skip to main content
SpringerLink
Log in

One Modelling Formalism & Simulator Is Not Enough! A Perspective for Computational Biology Based on James II

  • Conference paper
Formal Methods in Systems Biology (FMSB 2008)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5054))

Included in the following conference series:

Abstract

Diverse modelling formalisms are applied in Computational Biology. Some describe the biological system in a continuous manner, others focus on discrete-event systems, or on a combination of continuous and discrete descriptions. Similarly, there are many simulators that support different formalisms and execution types (e.g. sequential, parallel-distributed) of one and the same model. The latter is often done to increase efficiency, sometimes at the cost of accuracy and level of detail. James II has been developed to support different modelling formalisms and different simulators and their combinations. It is based on a plug-in concept which enables developers to integrate spatial and non-spatial modelling formalisms (e.g. stochastic π calculus, Beta binders, Devs, space- π), simulation algorithms (e.g. variants of Gillespie’s algorithms (including Tau Leaping and Next Subvolume Method),space- π simulator, parallel Beta binders simulator) and supporting technologies (e.g. partitioning algorithms, data collection mechanisms, data structures, random number generators) into an existing framework. This eases method development and result evaluation in applied modelling and simulation as well as in modelling and simulation research.

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

Access this chapter

Log in via an institution
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. Broderick, G., Rubin, E.: The realistic modeling of biological systems: A workshop synopsis. ComPlexUs Modeling in Systems Biology, Social Cognitive and Information Science 3(4), 217–230 (2006)

    Google Scholar 

  2. Cardelli, L.: Membrane interactions. In: BioConcur 2003, Workshop on Concurrent Models in Molecular Biology (2003)

    Google Scholar 

  3. Cao, Y., Gillespie, D.T., Petzold, L.R.: Efficient step size selection for the tau-leaping simulation method. J. Chem. Phys. 124, 044109 (2006)

    Article  Google Scholar 

  4. Cao, Y., Li, H., Petzold, L.: Efficient formulation of the stochastic simulation algorithm for chemically reacting systems. The Journal of Chemical Physics 121(9), 4059–4067 (2004)

    Article  Google Scholar 

  5. Elf, J., Ehrenberg, M.: Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases. Syst. Biol (Stevenage) 1(2), 230–236 (2004)

    Article  Google Scholar 

  6. Ewald, R., Himmelspach, J., Uhrmacher, A.M.: Embedding a non-fragmenting partitioning algorithm for hierarchical models into the partitioning layer of James II. In: WSC 2006: Proceedings of the 38th conference on Winter simulation (2006)

    Google Scholar 

  7. Ewald, R., Himmelspach, J., Uhrmacher, A.M.: An algorithm selection approach for simulation systems. In: Proceedings of the 22nd ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation (PADS 2008) (to appear, 2008)

    Google Scholar 

  8. Ewald, R., Maus, C., Rolfs, A., Uhrmacher, A.M.: Discrete event modelling and simulation in systems biology. Journal of Simulation 1(2), 81–96 (2007)

    Article  Google Scholar 

  9. Fisher, J., Piterman, N., Hubbard, J., Stern, M., Harel, D.: Computational insights into C. elegans vulval development. PNAS 102(5), 1951–1956 (2005)

    Article  Google Scholar 

  10. Gardiner, C.W.: Handbook of Stochastic Methods: For Physics, Chemistry and the Natural Sciences (Springer Series in Synergetics). Springer, Heidelberg (1996)

    Google Scholar 

  11. Gibson, M.A., Bruck, J.: Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels. J. Chem. Physics 104, 1876–1889 (2000)

    Google Scholar 

  12. Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns: elements of reusable object-oriented software. Addison-Wesley, Reading (1995)

    Google Scholar 

  13. Guerriero, M.L., Heath, J.K., Priami, C.: An automated translation from a narrative language for biological modelling into process algebra. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 136–151. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  14. Gillespie, D.T.: Exact Stochastic Simulation of Coupled Chemical Reactions. The Journal of Physical Chemistry B 81(25), 2340–2361 (1977)

    Article  Google Scholar 

  15. Gillespie, D.T.: Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics (2001)

    Google Scholar 

  16. Harel, D.: Statecharts: A Visual Formalism for Complex Systems. Science of Computer Programming 8(3), 231–274 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  17. Himmelspach, J., Lecca, P., Prandi, D., Priami, C., Quaglia, P., Uhrmacher, A.M.: Developing an hierarchical simulator for beta-binders. In: 20th Workshop on Principles of Advanced and Distributed Simulation (PADS 2006), pp. 92–102. IEEE Computer Society, Los Alamitos (2006)

    Chapter  Google Scholar 

  18. Jirstrand, M., Schmidt, H.: Systems biology toolbox for matlab: A computational platform for research in systems biology. Bioinformatics (2005)

    Google Scholar 

  19. Himmelspach, J., Uhrmacher, A.M.: A component-based simulation layer for james. In: ACM Press (ed.): PADS 2004: Proceedings of the eighteenth workshop on Parallel and distributed simulation, pp. 115–122. IEEE Computer Society, Los Alamitos (2004)

    Chapter  Google Scholar 

  20. Himmelspach, J., Uhrmacher, A.M.: The event queue problem and pdevs. In: Proceedings of the SpringSim 2007, DEVS Integrative M&S Symposium, pp. 257–264. SCS (2007)

    Google Scholar 

  21. Himmelspach, J., Uhrmacher, A.M.: Plug’n simulate. In: Proceedings of the Spring Simulation Multiconference, pp. 137–143. IEEE Computer Society, Los Alamitos (2007)

    Google Scholar 

  22. Jeschke, M., Ewald, R., Park, A., Fujimoto, R., Uhrmacher, A.M.: Parallel and distributed spatial simulation of chemical reactions. In: Proceedings of the 22nd ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation (PADS 2008) (to appear, 2008)

    Google Scholar 

  23. John, M., Ewald, R., Uhrmacher, A.M.: A spatial extension to the pi calculus. In: Proc. of the 1st Workshop From Biology To Concurrency and back (FBTC 2007). Electronic Notes in Theoretical Computer Science, vol. 194, pp. 133–148 (2008)

    Google Scholar 

  24. Kholodenko, B.N.: Cell-signalling dynamics in time and space. Nature Reviews Molecular Cell Biology 7(3), 165–176 (2006)

    Article  Google Scholar 

  25. Karypis, G., Kumar, V.: MeTis: A Software Package for Partitioning Unstructured Graphs, Partitioning Meshes, and Computing Fill-Reducing Orderings of Sparse Matrices (Version 4.0) (September 1998)

    Google Scholar 

  26. Korn, G.A., Wait, J.V.: Digital continuous-system simulation. Prentice-Hall, Englewood Cliffs (1978)

    Google Scholar 

  27. Leye, S., Priami, C., Uhrmacher, A.M.: A parallel beta-binders simulator. Technical Report 17/2007, The Microsoft Research - University of Trento Centre for Computational and Systems Biology (2007)

    Google Scholar 

  28. Minsky, M.: Models, minds, machines. In: Proc. IFIP Congress, pp. 45–49 (1965)

    Google Scholar 

  29. Maus, C., John, M., Uhrmacher, A.M.: A multi-level and multi-formalism approach for model composition in systems biology. In: Conference on Computational Methods in Systems Biology, Edinburgh, Poster (2007)

    Google Scholar 

  30. Murata, T.: Petri Nets: Properties, Analysis and Applications. Proceedings of the IEEE 77(4), 541–574 (1989)

    Article  Google Scholar 

  31. Nicollin, X., Sifakis, J.: An Overview and Synthesis on Timed Process Algebras. In: Larsen, K.G., Skou, A. (eds.) CAV 1991. LNCS, vol. 575, pp. 376–398. Springer, Heidelberg (1992)

    Google Scholar 

  32. OMG. UML superstructure specification version 2.0 (document formal/05-07-04) (July 2005), http://www.omg.org/cgi-bin/doc?formal/05-07-04

  33. Priami, C., Quaglia, P.: Beta binders for biological interactions. In: Danos, V., Schachter, V. (eds.) CMSB 2004. LNCS (LNBI), vol. 3082, pp. 20–33. Springer, Heidelberg (2005)

    Google Scholar 

  34. Priami, C.: Stochastic π-calculus. The Computer Journal 38(6), 578–589 (1995)

    Article  Google Scholar 

  35. Priami, C., Regev, A., Shapiro, E., Silvermann, W.: Application of a stochastic name-passing calculus to representation and simulation of molecular processes. Information Processing Letters 80, 25–31 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  36. Röhl, M., Morgenstern, S.: Composing simulation models using interface definitions based on web service descriptions. In: WSC 2007, pp. 815–822 (2007)

    Google Scholar 

  37. Ramsey, S., Orrell, D., Bolouri, H.: Dizzy: Stochastic simulation of large scale genetic regulatory networks. Journal of Bioinformatics and Computational Biology 01(13), 415–436 (2005)

    Article  Google Scholar 

  38. Regev, A., Panina, E.M., Silverman, W., Cardelli, L., Shapiro, E.: BioAmbients: an abstraction for biological compartments. Theor. Comput. Sci. 325(1), 141–167 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  39. Röhl, M., Uhrmacher, A.M.: Composing simulations from xml-specified model components. In: Proceedings of the Winter Simulation Conference 2006, pp. 1083–1090. ACM, New York (2006)

    Chapter  Google Scholar 

  40. Tian, T., Burrage, K.: Binomial leap methods for simulating stochastic chemical kinetics. The Journal of Chemical Physics 121(10356), 10356–10364 (2004)

    Article  Google Scholar 

  41. Takahashi, K., Kaizu, K., Hu, B., Tomita, M.: A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics 20, 538–546 (2004)

    Article  Google Scholar 

  42. Takahashi, K., Nanda, S., Arjunan, V., Tomita, M.: Space in systems biology of signaling pathways: towards intracellular molecular crowding in silico. FEBS letters 579(8), 1783–1788 (2005)

    Article  Google Scholar 

  43. Uhrmacher, A.M., Ewald, R., John, M., Maus, C., Jeschke, M., Biermann, S.: Combining micro and macro-modeling in devs for computational biology. In: Proc. of the 2007 Winter Simulation Conference, pp. 871–880 (2007)

    Google Scholar 

  44. Uhrmacher, A.M.: Dynamic structures in modeling and simulation - a reflective approach. ACM Transactions on Modeling and Simulation 11(2), 206–232 (2001)

    Article  Google Scholar 

  45. Uhrmacher, A.M., Himmelspach, J., Röhl, M., Ewald, R.: Introducing variable ports and multi-couplings for cell biological modeling in devs. In: Proc. of the 2006 Winter Simulation Conference, pp. 832–840 (2006)

    Google Scholar 

  46. van Gunsteren, W.F., Berendsen, H.J.: Computer simulation of molecular dynamics: Methodology, applications, and perspectives in chemistry. Angewandte Chemie International Edition in English 29(9), 992–1023 (1990)

    Article  Google Scholar 

  47. Zeigler, B.P., Praehofer, H., Kim, T.G.: Theory of Modeling and Simulation. Academic Press, London (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Rostock, Rostock, Germany, Albert-Einstein-Str. 21, D-18059

    Adelinde M. Uhrmacher, Jan Himmelspach, Matthias Jeschke, Mathias John, Stefan Leye, Carsten Maus, Mathias Röhl & Roland Ewald

Authors
  1. Adelinde M. Uhrmacher
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jan Himmelspach
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matthias Jeschke
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mathias John
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Stefan Leye
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Carsten Maus
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mathias Röhl
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Roland Ewald
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Jasmin Fisher

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Uhrmacher, A.M. et al. (2008). One Modelling Formalism & Simulator Is Not Enough! A Perspective for Computational Biology Based on James II . In: Fisher, J. (eds) Formal Methods in Systems Biology. FMSB 2008. Lecture Notes in Computer Science(), vol 5054. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68413-8_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-68413-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68410-7

  • Online ISBN: 978-3-540-68413-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation