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Membrane Computing as a Modeling Framework. Cellular Systems Case Studies

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Formal Methods for Computational Systems Biology (SFM 2008)

Abstract

Membrane computing is a branch of natural computing aiming to abstract computing models from the structure and functioning of the living cell, and from the way cells cooperate in tissues, organs, or other populations of cells. This research area developed very fast, both at the theoretical level and in what concerns the applications. After a very short description of the domain, we mention here the main areas where membrane computing was used as a framework for devising models (biology and bio-medicine, linguistics, economics, computer science, etc.), then we discuss in a certain detail the possibility of using membrane computing as a high level computational modeling framework for addressing structural and dynamical aspects of cellular systems. We close with a comprehensive bibliography of membrane computing applications.

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References

  1. Andrei, O., Ciobanu, G., Lucanu, D.: Executable specification of P systems. In: Mauri, G., et al. (eds.) WMC 2004. LNCS, vol. 3365, pp. 126–145. Springer, Heidelberg (2005)

    Google Scholar 

  2. Ardelean, I.I., Cavaliere, M.: Modelling biological processes by using a probabilistic P system software. Natural Computing 2(2), 173–197 (2003)

    Article  MATH  Google Scholar 

  3. Besozzi, D., Ciobanu, G.: A P systems description of the sodium-potassium pump. In: Mauri, G., et al. (eds.) WMC 2004. LNCS, vol. 3365, pp. 210–223. Springer, Heidelberg (2005)

    Google Scholar 

  4. Bianco, L., Fontana, F., Manca, V.: P systems with reaction maps. International Journal of Foundations of Computer Science 17(1), 27–48 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  5. Cardelli, L.: Brane calculi: Interactions of biological membranes. In: Danos, V., Schachter, V. (eds.) CMSB 2004. LNCS (LNBI), vol. 3082, pp. 257–278. Springer, Heidelberg (2005)

    Google Scholar 

  6. Cheruku, S., Paun, A., Romero-Campero, F.J., Pérez-Jiménez, M.J., Ibarra, O.H.: Simulating fas-induced apoptosis by using P systems. Progress in Natural Science 17(4), 424–431 (2007)

    Article  MathSciNet  Google Scholar 

  7. Ciobanu, G., Pan, L., Păun, G.: P systems with minimal parallelism. Theoretical Computer Science 378(1), 117–130 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  8. Fontana, F., Bianco, L., Manca, V.: P systems and the modelling of biochemical oscillations. In: Freund, R., Păun, G., Rozenberg, G., Salomaa, A. (eds.) WMC 2005. LNCS, vol. 3850, pp. 199–208. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  9. Fontana, F., Manca, V.: Discrete solutions to differential equations by metabolic P systems. Theoretical Computer Science 372(2-3), 165–182 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  10. Freund, R.: P systems working in the sequential mode on arrays and strings. International Journal of Foundations of Computer Science 16(4), 663–682 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  11. Gillespie, D.T.: Stochastic simulation of chemical kinetics. Annu. Rev. Phys. Chem. 58, 35–55 (2007)

    Article  Google Scholar 

  12. Goss, P.J., Peccoud, J.: Quantitative modelling of stochastic system in molecular biology by using stochastic petri nets. Proc. Natl. Acad. Sci. USA 95, 6750–6755 (1998)

    Article  Google Scholar 

  13. Heath, J., Kwiatkowska, M.Z., Norman, G., Parker, D., Tymchyshyn, O.: Probabilistic model checking of complex biological pathways. Theoretical Computer Science 391(3), 239–257 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  14. Kwiatkowska, M., Norman, G., Parker, D.: Stochastic model checking. In: Bernardo, M., Hillston, J. (eds.) SFM 2007. LNCS, vol. 4486, pp. 220–270. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  15. Li, C., Dang, Z., Ibarra, O.H., Yen, H.-C.: Signaling p systems and verification problems. In: Caires, L., Italiano, G.F., Monteiro, L., Palamidessi, C., Yung, M. (eds.) ICALP 2005. LNCS, vol. 3580, pp. 1462–1473. Springer, Heidelberg (2005)

    Google Scholar 

  16. Milner, R.: Communication and Mobile Systems: The π-calculus. Cambridge University Press, Cambridge (1999)

    Google Scholar 

  17. Pérez-Jiménez, M.J., Romero-Campero, F.J.: P systems, a new computational modelling tool for systems biology. In: Transactions on Computational Systems Biology VI, pp. 176–197 (2006)

    Google Scholar 

  18. Pescini, D., Besozzi, D., Mauri, G., Zandron, C.: Dynamical probabilistic p systems. International Journal of Foundations of Computer Science 17(1), 183–195 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  19. Ptashne, M., Gann, A.: Genes and Signals. Cold Spring Harbor Laboratory Press (2002)

    Google Scholar 

  20. Reddy, V., Liebman, M., Maverovouniotis, M.: Qualitative analysis of biochemical reaction systems. Computers in Biology and Medicine 26(1), 9–24 (1996)

    Article  Google Scholar 

  21. Regev, A., Panina, E., Silvermann, W., Cardelli, L., Shapiro, E.: Bioambients: an abstraction for biological compartments. Theoretical Computer Science 325, 141–167 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  22. Regev, A., Shapiro, E.: The π-calculus as an abstraction for biomolecular systems. In: Modelling in Molecular Biology, pp. 1–50. Springer, Berlin (2004)

    Google Scholar 

  23. Romero-Campero, F.J., Pérez-Jiménez, M.J.: A model of the quorum sensing system in vibrio fischeri using P systems. Artificial Life 14(1), 95–109 (2008)

    Article  Google Scholar 

  24. Romero-Campero, F.J., Pérez-Jiménez, M.J.: Modelling gene expression control using P systems: The lac operon, a case study. BioSystems 91(3), 438–457 (2008)

    Article  Google Scholar 

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Marco Bernardo Pierpaolo Degano Gianluigi Zavattaro

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Păun, G., Romero-Campero, F.J. (2008). Membrane Computing as a Modeling Framework. Cellular Systems Case Studies. In: Bernardo, M., Degano, P., Zavattaro, G. (eds) Formal Methods for Computational Systems Biology. SFM 2008. Lecture Notes in Computer Science, vol 5016. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68894-5_6

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  • DOI: https://doi.org/10.1007/978-3-540-68894-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68892-1

  • Online ISBN: 978-3-540-68894-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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