Abstract
The Gillespie stochastic simulation algorithm represents one of the main physical abstractions exploited for the simulation of biological systems modeled by means of concurrent calculi. While the faithful modelling of bio-systems often requires multi-compartment semantics, the original Gillespie algorithm considers only one fixed-size volume. In this paper we introduce an extended formalisation of the above algorithm which preserves the original model but allows the stochastic simulation in presence of multiple compartments with dynamical structure and variable sizes. The presented algorithm can be then used as basis for simulating systems expressed in an extended version of the stochastic π-Calculus, the Sπ@ language, obtained by means of polyadic synchronisation. Despite of its conservativeness, Sπ@ is showed to allow flexible modelling of multiple compartments with dynamical structure and to provide increased biological faithfulness.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Regev, A., Silverman, W., Shapiro, E.Y.: Representation and simulation of biochemical processes using the pi-calculus process algebra. In: Pacific Symposium on Biocomputing, pp. 459–470 (2001)
Priami, C., Regev, A., Shapiro, E.Y., Silverman, W.: Application of a stochastic name-passing calculus to representation and simulation of molecular processes. Inf. Process. Lett. 80(1), 25–31 (2001)
Regev, A., Panina, E.M., Silverman, W., Cardelli, L., Shapiro, E.Y.: Bioambients: an abstraction for biological compartments. Theor. Comput. Sci. 325(1), 141–167 (2004)
Phillips, A., Cardelli, L.: A correct abstract machine for the stochastic pi-calculus. In: Bioconcur 2004, ENTCS (2004)
Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81(25), 2340–2361 (1977)
Cardelli, L.: Brane calculi. In: Danos, V., Schachter, V. (eds.) CMSB 2004. LNCS (LNBI), vol. 3082, pp. 257–278. Springer, Heidelberg (2005)
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)
Cazzaniga, P., Pescini, D., Romero-Campero, F.J., Besozzi, D., Mauri, G.: Stochastic approaches in P systems for simulating biological systems. In: Gutiérrez-Naranjo, M.A., Paun, G., Riscos-Núñez, A., Romero-Campero, F.J. (eds.) Fourth Brainstorming Week on Membrane Computing, Sevilla, Fénix Editora, January 30 - February 3, 2006, vol. I, pp. 145–164 (2006)
Versari, C.: A core calculus for a comparative analysis of bio-inspired calculi (2007), http://www.cs.unibo.it/~versari/files/cversari-esop07.pdf
Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes, i. Inf. Comput. 100(1), 1–40 (1992)
Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes, ii. Inf. Comput. 100(1), 41–77 (1992)
Milner, R.: Communicating and mobile systems: the π-calculus. Cambridge University Press, New York, NY, USA (1999)
Carbone, M., Maffeis, S.: On the expressive power of polyadic synchronisation in pi-calculus. Nord. J. Comput. 10(2), 70–98 (2003)
Cleaveland, R., Lüttgen, G., Natarajan, V.: Priority in process algebra. In: Bergstra, J., Ponse, A., Smolka, S. (eds.) Handbook of Process Algebra, pp. 711–765. Elsevier Science Publishers, Amsterdam (2001)
Lodish, H., Berk, A., Matsudaira, P., Kaiser, C.A., Krieger, M., Scott, M.P., Zipursky, L., Darnell, J.: Molecular Cell Biology. W. H. Freeman, New York (2004)
Lu, T., Volfson, D., Tsimring, L., Hasty, J.: Cellular growth and division in the gillespie algorithm. In: Systems Biology, IEE Proceedings, pp. 121–128 (2004)
Lecca, P.: A time-dependent extension of gillespie algorithm for biochemical stochastic π-calculus. In: SAC 2006. Proceedings of the 2006 ACM symposium on Applied computing, New York, NY, USA, pp. 137–144. ACM Press, New York (2006)
Elf, J., Ehrenberg, M.: Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases. Systems Biology 1(2), 230–236 (2004)
Phillips, A., Cardelli, L., Castagna, G.: A graphical representation for biological processes in the stochastic pi-calculus, vol. 4230, pp. 123–152 (2006)
Cazzaniga, P., Pescini, D., Besozzi, D., Mauri, G.: Tau leaping stochastic simulation method in p systems. In: Hoogeboom, H.J., Păun, G., Rozenberg, G., Salomaa, A. (eds.) WMC 2006. LNCS, vol. 4361, pp. 298–313. Springer, Heidelberg (2006)
Cao, Y., Gillespie, D.T., Petzold, L.R.: Efficient step size selection for the tau-leaping simulation method. Journal of Chemical Physics 124(4) (2006)
Danos, V., Schachter, V. (eds.): CMSB 2004. LNCS (LNBI), vol. 3082, pp. 26–28. Springer, Heidelberg (2005)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Versari, C., Busi, N. (2007). Stochastic Simulation of Biological Systems with Dynamical Compartment Structure. In: Calder, M., Gilmore, S. (eds) Computational Methods in Systems Biology. CMSB 2007. Lecture Notes in Computer Science(), vol 4695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75140-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-75140-3_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75139-7
Online ISBN: 978-3-540-75140-3
eBook Packages: Computer ScienceComputer Science (R0)