Investigation of a Biological Repair Scheme

  • Vincent Danos
  • Jérôme Féret
  • Walter Fontana
  • Russell Harmer
  • Jean Krivine
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5391)


This note details an interaction pattern for the allocation of a scarce biological resource where and when it is needed. It is entirely based on a mass action stochastic dynamics. Domain-domain binding plays a crucial role in the design of the pattern which we therefore present using a rule-based approach where binding is an explicit primitive. We also a use a series of refinements, starting from a very simple interaction set, which we feel gives an interesting and intuitive rationale for the working of the final repair scheme.


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  1. 1.
    Goldbeter, A., Koshland, D.: An Amplified Sensitivity Arising from Covalent Modification in Biological Systems. Proceedings of the National Academy of Sciences 78(11), 6840–6844 (1981)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Lisman, J.E.: A mechanism for memory storage insensitive to molecular turnover: a bistable autophosphorylating kinase. Proc. Natl. Acad. Sci. U S A 82(9), 3055–3057 (1985)CrossRefGoogle Scholar
  3. 3.
    Alon, U.: Network motifs: theory and experimental approaches. Nat. Rev. Genet. 8(6), 450–461 (2007)CrossRefGoogle Scholar
  4. 4.
    Wall, M.E., Dunlop, M.J., Hlavacek, W.S.: Multiple functions of a feed-forward-loop gene circuit. J. Mol. Biol. 349(3), 501–514 (2005)CrossRefGoogle Scholar
  5. 5.
    Mazurie, A., Bottani, S., Vergassola, M.: An evolutionary and functional assessment of regulatory network motifs. Genome Biol. 6(4), R35 (2005)CrossRefGoogle Scholar
  6. 6.
    Yeates, T.O., Beeby, M.: Proteins in a small world. Science 314(5807), 1882–1883 (2006)CrossRefGoogle Scholar
  7. 7.
    Danos, V., Feret, J., Fontana, W., Harmer, R., Krivine, J.: Rule-based modelling of cellular signalling. In: Caires, L., Vasconcelos, V.T. (eds.) CONCUR 2007. LNCS, vol. 4703, pp. 17–41. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Blinov, M.L., Faeder, J.R., Goldstein, B., Hlavacek, W.S.: A network model of early events in epidermal growth factor receptor signaling that accounts for combinatorial complexity. BioSystems 83, 136–151 (2006)CrossRefGoogle Scholar
  9. 9.
    Priami, C., Regev, A., Shapiro, E., Silverman, W.: Application of a stochastic name-passing calculus to representation and simulation of molecular processes. Information Processing Letters (2001)Google Scholar
  10. 10.
    Danos, V., Feret, J., Fontana, W., Harmer, R., Krivine, J.: Rule-based modelling, symmetries, refinements. In: Fisher, J. (ed.) FMSB 2008. LNCS (LNBI), vol. 5054, pp. 103–122. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  11. 11.
    Danos, V.: Agile Modelling of Cellular Signalling. Computation in Modern Science and Engineering 2, Part A 963, 611–614 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Vincent Danos
    • 1
  • Jérôme Féret
    • 2
  • Walter Fontana
    • 3
  • Russell Harmer
    • 4
  • Jean Krivine
    • 3
  1. 1.University of EdinburghUK
  2. 2.INRIA, CNRS, École Normale SupérieureFrance
  3. 3.Harvard Medical SchoolUSA
  4. 4.CNRS, Université Paris-DiderotFrance

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