Abstract
Normal structure and function in epithelial tissues is an emergent property of the interaction of the cells which comprise the tissue, so a cell-centred approach to the modelling of tissue behaviour is a logical approach. Epithelial tissues have the advantage, as a starting point, that they are relatively simple, but also have significant clinical problems - wound healing and the development of malignancy in particular - but also many other problems because of their barrier function. Exemplar biological systems are skin and urothelium. An individual-based modelling approach is adopted, with a 1:1 correspondence between living cells in biological (in vitro) models and the software agents used to represent the cells. The software agents are a formal entity (a communicating stream X-machine); the models are described using a mark-up language; and a formal framework and associated tools have been developed for model execution. ODE and PDE models of any complexity (e.g., biochemical models of signalling pathways) can be called as functions within the individual agents, and the physical environment of the cells can be modelled either globally or as a physical model of interaction with neighbouring cells that is embedded within each agent. The realisation is inherently parallel, and is also being used to model cell signalling, the behaviour of social insects, and macro-economic behaviour.
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An interactive computer program for Continuum Mechanics, Image analysis, Signal processing and System identification (CMISS), http://www.cmiss.org.
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References
S. Adra, T. Sun, S. MacNeil, M. Holcombe, and R. Smallwood. Development of a three dimensional multiscale computational model of the human epidermis. PLoS ONE, 5(1):e8511, 2010.
D. Boal. Mechanics of the Cell. Cambridge University Press, Cambridge, 2002.
K. Burrage, T. Tian, and P. Burrage. A multi-scaled approach for simulating chemical reaction systems. Progress in Biophysics and Molecular Biology, 85: 217–234, 2004.
S. Eilenberg. Automata, Languages and Machines, Vol. A. Academic, London, 1974.
D. J. W. Evans, P. V. Lawford, J. Gunn, D. C. Walker, D. R. Hose, R. H. Smallwood, B. Chopard, M. Krafczyk, J. Bernsdorf, and A. Hoekstra. The application of multiscale modelling to the process of development and prevention of stenosis in a stented coronary artery. Philosophical Transactions of the Royal Society A, 366: 3343–3360, 2008.
E. Feytmans, D. Noble, and M. Peitsch. Genome size and numbers of biological functions. Transactions on Computational Systems Biology, 1: 44–49, 2005.
V. Grimm. A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198: 115–126, 2006.
V. Grimm. Ten years of individual-based modelling in ecology: What have we learned and what could we learn in the future? Ecological Modelling, 115: 129–148, 1999.
A. Hoekstra, E. Lorenz, J. Falcone, and B. Chopard. Towards a complex automata framework for multi-scale modeling: Formalism and the scale separation map. In ICCS 2007, Part I, Lecture Notes in Computer Science, Springer, volume 4487, pages 922–930, 2007.
P. Kefalas, G. Eleftherakis, and E. Kehris. Communicating X-machines: from theory to practice. In Advances in Informatics, Lecture Notes in Computer Science (ed. Y. Manolopoulos, S. Evripidou, and A. Kakas.), Springer, volume 2563, pages 316–335, 2003.
P. Kohl and D. Noble. 97 (2008) 159-162 editorial life and mechanosensitivity. Progress in Biophysics and Molecular Biology, 97: 159–162, 2008.
S. Marino, I. B. Hogue, C. J. Ray, and D. E. Kirschner. A methodology for performing global uncertainty and sensitivity analysis in systems biology. Journal of Theoretical Biology, 254: 178–196, 2008.
D. E. Nelson, A. E. C. Ihekwaba, M. Elliott, J. R. Johnson, C. A. Gibney, B. E. Foreman, G. Nelson, V. See, C. A. Horton, D. G. Spiller, S. W. Edwards, H. P. McDowell, J. F. Unitt, E. Sullivan, R. Grimley, N. Benson, D. Broomhead, D. B. Kell, and M. R. H. White. Oscillations in NF-kB Signaling Control the Dynamics of Gene Expression. Science, 306: 704–708, 2004.
M. Pogson, R. Smallwood, E. Qwarnstrom, and M. Holcombe. Formal agent-based modelling of intracellular chemical interactions. Biosystems, 85: 37–45, 2006.
M. Pogson, M. Holcombe, R. H. Smallwood, and E. Qwarnstrom. Introducing spatial information into predictive nf-kb modelling – an agent-based approach. PLoS ONE 3(6): e2367. doi:10.1371/journal.pone.0002367, 3 (6), 2008.
R. H. Smallwood. Computational modelling of epithelial tissues. Wiley Interdisciplinary Reviews Systems Biology, URL http://www3.interscience.wiley.com/journal/122305009/abstract, 2009.
D. Sornette, A. B. Davis, K. Ide, K. R. Vixle, V. Pisarenko, and J. R. Kamm. Algorithm for model validation: Theory and applications. PNAS, 104: 6562–6567, 2007.
M. Stannett. Theory of x-machines. http://x-machines.com/, 2005. URL http://x-machines.com/.
T. Sun, P. McMinn, S. Coakley, M. Holcombe, R. H. Smallwood, and S. MacNeil. An integrated systems biology approach to understanding the rules of keratinocyte colony formation. Journal of the Royal Society Interface, 4: 1077–1092, 2007.
T. Sun, P. McMinn, M. Holcombe, R. Smallwood, and S. Macneil. Agent-based modeling helps in understanding the rules by which fibroblasts support keratinocyte colony formation. PLoS ONE, 3, 2008. doi: e2129doi:10.1371/journal.pone.0002129.
T. Sun, S. Adra, R. Smallwood, M. Holcombe, and S. Macneil. Exploring the hypotheses of the actions of TGF-β1 in epidermal wound healing using a 3D computational multiscale model of the human epidermis. PLoS ONE, 4(12):e8515, 2010.
D. C. Walker, J. S. Southgate, G. Hill, M. Holcombe, D. R. Hose, S. M. Wood, S. MacNeil, and R. H. Smallwood. The Epitheliome: modelling the social behavior of cells. BioSystems, 76: 89–100, 2004a.
D. C. Walker, G. Hill, S. M. Wood, R. H. Smallwood, and J. S. Southgate. Agent-based modelling of wounded epithelial cell monolayers. IEEE Transactions on Nanobioscience, 3: 153–163, 2004b.
D. C. Walker, S. Wood, J. S. Southgate, M. Holcombe, and R. H. Smallwood. An integrated agent-mathematical model of the effect of intercellular signaling via the epidermal growth factor receptor on cell proliferation. Journal of Theoretical Biology, 242: 774–789, 2006a.
D. C. Walker, T. Sun, S. MacNeil, and R. H. Smallwood. Modeling the effect of exogenous calcium on keratinocyte and HaCat cell proliferation and differentiation using an agent-based computational paradigm. Tissue Engineering, 12: 2301–2309, 2006b.
Acknowledgements
The opinions expressed are my own, but have benefitted from discussions with and work by Jenny Southgate, Mike Holcombe, Sheila Mac Neil, Dawn Walker, Simon Coakley, Mark Pogson, Sun Tao, Nik Georgopoulos, Phil McMinn, Salem Adra, Des Ryan, Goodarz Kodabakshi, Rod Hose and Pat Lawford, all of whom I wish to acknowledge and thank.
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Smallwood, R. (2011). Cell-Centred Modeling of Tissue Behaviour. In: Dubitzky, W., Southgate, J., Fuß, H. (eds) Understanding the Dynamics of Biological Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7964-3_9
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