Abstract
Computational modeling of biological systems is becoming increasingly important in the endeavors to better understand complex biological behavior. It enables researchers to perform computerized simulations using a systems biology approach, in order to understand the underlying mechanisms of certain biological phenomena. It provides an opportunity to perform experiments that are otherwise impractical or infeasible in vivo/vitro experiments. In our approach we propose to model and simulate the pathogenesis ofMycobacterium marinum using Petri Net formalism based on data obtained from analysis of microscope images and to provide a three dimensional visualization of the whole infection process and granuloma formation. Image analysis will provide an accurate estimation of the infection in a structured database which will be used for the construction of the Petri Net model. The results of the simulation and analysis of the infection behavior will be visualized in 3D.
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References
Alla, H., David, R.: Continuous and hybrid Petri nets. Journal of Circuits Systems and Computers 8, 159–188 (1998)
Barbuti, R., Caravagna, G., Maggiolo–Schettini, A., Milazzo, P., Pardini, G.: The Calculus of Looping Sequences. In: Bernardo, M., Degano, P., Zavattaro, G. (eds.) SFM 2008. LNCS, vol. 5016, pp. 387–423. Springer, Heidelberg (2008)
Bouley, D.M., et al.: Dynamic nature of host-pathogen interactions in Mycobacterium marinum granulomas. Infection and Immunity 69(12), 7820 (2001)
Calzone, L., et al.: BIOCHAM: an environment for modeling biological systems and formalizing experimental knowledge. Bioinformatics 22(14), 1805–1807 (2006)
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)
Chaouiya, C.: Petri net modelling of biological networks. Briefings in Bioinformatics 8(4), 210–219 (2007)
Danos, V., Krivine, J.: Formal Molecular Biology Done in CCS-R. Electronic Notes in Theoretical Computer Science 180(3), 31–49 (2007)
Fisher, J., Henzinger, T.A.: Executable cell biology. Nature Biotechnology 25(11), 1239–1249 (2007)
Hardy, S., Robillard, P.N.: Modeling and simulation of molecular biology systems using Petri nets: modeling goals of various approaches. Journal of Bioinformatics and Computational Biology 2(4), 595–613 (2004)
Heiner, M., et al.: Snoopy-A Tool to Design and Execute Graph-Based Formalisms. Petri Net Newsletter 74, 8–22 (2008)
Hofestädt, R.: A Petri net application to model metabolic processes. Systems Analysis Modelling Simulation 16(2), 113–122 (1994)
Lesley, R., Ramakrishnan, L.: Insights into early mycobacterial pathogenesis from the zebrafish. Current Opinion in Microbiology 11(3), 277–283 (2008)
Liu, F., et al.: Computation of Enabled Transition Instances for Colored Petri Nets. In: Proc. AWPN, pp. 51–65 (2010)
Marino, S., et al.: A multifaceted approach to modeling the immune response in tuberculosis. Wiley Interdisciplinary Reviews. Systems Biology and Medicine 3(4), 479–489 (2011)
Mura, I., Csikász-Nagy, A.: Stochastic Petri Net extension of a yeast cell cycle model. Journal of Theoretical Biology 254(4), 850–860 (2008)
Nezhinsky, A., et al.: Pattern Recognition in Bioinformatics. Springer, Heidelberg (2010)
Pun, G.: A guide to membrane computing. Theoretical Computer Science 287(1), 73–100 (2002)
Reddy, V.N., et al.: Petri net representations in metabolic pathways. In: Proceedings of International Conference on Intelligent Systems for Molecular Biology, ISMB, vol. 1(115), pp. 328–336 (1993)
Regev, A., et al.: Representation and simulation of biochemical processes using the pi-calculus process algebra (2001)
Segovia-Juarez, J.L., et al.: Identifying control mechanisms of granuloma formation during M. tuberculosis infection using an agent-based model. Journal of Theoretical Biology 231(3), 357–376 (2004)
Stinear, T.P., et al.: Insights from the complete genome sequence of Mycobacterium marinum on the evolution of Mycobacterium tuberculosis. Genome Research 18(5), 729–741 (2008)
World Health Organization: Global tuberculosis control: epidemiology, strategy, financing, Geneva (2009)
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Carvalho, R.V., Davids, W., Meijer, A.H., Verbeek, F.J. (2012). Spatio-temporal Modeling and Simulation of Mycobacterium Pathogenesis Using Petri Nets. In: Hart, E., Timmis, J., Mitchell, P., Nakamo, T., Dabiri, F. (eds) Bio-Inspired Models of Networks, Information, and Computing Systems. BIONETICS 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32711-7_23
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DOI: https://doi.org/10.1007/978-3-642-32711-7_23
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