Skip to main content

Models of Stochastic Gene Expression and Weyl Algebra

  • Conference paper
Algebraic and Numeric Biology

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6479))

Abstract

This paper presents a symbolic algorithm for computing the ODE systems which describe the evolution of the moments associated to a chemical reaction system, considered from a stochastic point of view. The algorithm, which is formulated in the Weyl algebra, seems more efficient than the corresponding method, based on partial derivatives. In particular, an efficient method for handling conservation laws is presented. The output of the algorithm can be used for a further investigation of the system behaviour, by numerical methods. Relevant examples are carried out.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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.

Similar content being viewed by others

References

  1. Abramov, S.A., Le, H.Q., Li, Z.: OreTools: a computer algebra library for univariate ore polynomial rings. School of Computer Science CS-2003-12, University of Waterloo (2003)

    Google Scholar 

  2. Chyzak, F.: The Ore_algebra library. In: Maple, Maplesoft, Canada. Software

    Google Scholar 

  3. Dixmier, J.: Enveloping Algebras. American Mathematical Society (1996); (Translation of the french edition Algèbres enveloppantes published in 1974 by Bordas)

    Google Scholar 

  4. Érdi, P., Tóth, J.: Mathematical models of chemical reactions. Princeton University Press (1989)

    Google Scholar 

  5. Feller, W.: An introduction to probability theory and its applications, 2nd edn., vol. I. John Wiley and Sons, Inc., New York (1957)

    MATH  Google Scholar 

  6. Gillespie, C.S.: Moment-closure approximations for mass-action models. Systems Biology, IET 3(1), 52–58 (2009)

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  8. Kalinkin, A.V.: Markov branching processes with interaction. Russian Math. Surveys 57, 241–304 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  9. Klamt, S., Stelling, J.: Stoichiometric and Constraint-based Modeling. In: Szallasi, Z., Stelling, J., Periwal, V. (eds.) System Modeling in Cellular Biology: From Concepts to Nuts and Bolts, pp. 73–96. The MIT Press, Cambridge (2006)

    Chapter  Google Scholar 

  10. Leykin, A.: D-modules for macaulay 2. mathematical software. In: Mathematical Software, pp. 169–179. World Sci. Publishing, River Edge (2002)

    Chapter  Google Scholar 

  11. Ozbudak, M., Thattai, M., Kurtser, I., Grossman, A.D.: Regulation of noise in the expression of a single gene. Nature Genetics 31, 69–73 (2002)

    Article  Google Scholar 

  12. Paulsson, J.: Models of stochastic gene expression. Physics of Live Rev. 2, 157–175 (2005)

    Google Scholar 

  13. Paulsson, J., Elf, J.: Stochastic Modeling of Intracellular Kinetics. In: Szallasi, Z., Stelling, J., Periwal, V. (eds.) System Modeling in Cellular Biology: From Concepts to Nuts and Bolts, pp. 149–175. The MIT Press, Cambridge (2006)

    Chapter  Google Scholar 

  14. Reutenauer, C.: Aspects mathématiques des réseaux de Petri. Masson (1989)

    Google Scholar 

  15. Vidal, S.A.: Groupe Modulaire et Cartes Combinatoires. Génération et Comptage. PhD thesis, Université Lille I, France (July 2010)

    Google Scholar 

  16. Singh, A., Hespanha, J.P.: Lognormal moment closures for biochemical reactions. In: Proceedings of the 45th IEEE Conference on Decision and Control, pp. 2063–2068 (2006)

    Google Scholar 

  17. Tadao, M.: Petri nets: properties, analysis and applications. Proceedings of the IEEE 77(4), 541–580 (1989)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Vidal, S., Petitot, M., Boulier, F., Lemaire, F., Kuttler, C. (2012). Models of Stochastic Gene Expression and Weyl Algebra. In: Horimoto, K., Nakatsui, M., Popov, N. (eds) Algebraic and Numeric Biology. Lecture Notes in Computer Science, vol 6479. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28067-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28067-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28066-5

  • Online ISBN: 978-3-642-28067-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics