Abstract
We first establish the potential usefulness of simulation in immunological research, and then explore some of the problems that are preventing its widespread use. We suggest solutions for each of these problems, and illustrate both problems and solutions with an example from our own research – an experiment that tests a novel theory of immunological memory, in which our simulation effectively closed the experiment-theorise loop.
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References
1. E. Ahmed and A. H. Hashish, On modelling of immune memory mechanisms (sic), Theory Biosci. 122 (2003), 339–342.
2. R. Antia, V. V. Ganusov, and R. Ahmed, The role of models in understanding CD8 + t-cell memory, Nature Review of Immunology 5 (2005), 101–111.
3. N. L. Bernasconi, E. Traggiai, and A. Lanzavecchia, Maintenance of serological memory by polyclonal activation of human memory b-cells, Science 298 (2002), 2199–2202.
4. F. M. Burnet, The clonal selection theory of acquired immunity, Cambridge University Press, 1959.
5. F. Castiglione, V Selitser, and Z. Agur, The effect of drug schedule on hypersensitive reactions: a study with a cellular automata model of the immune system, Cancer Modelling and Simulation (Luigi Preziosi, ed.), CRC Press, LLC, (UK), 2003.
6. J.D. Farmer, N. Packard, and A. Perelson, The immune system, adaptation and machine learning, Physica D 22 (1986), 187–204.
7. S. M. Garrett, A paratope is not an epitope: Implications for immune networks and clonal selection, 2nd International Conference in Arti.cial Immune Systems (Edinburgh), Springer-Verlag, September 1–3 2003, pp. 217–228.
8. C. Jacob, J. Litorco, and L. Lee, Immunity through swarms: Agent-based simulations of the human immune system, 3rd International Conference in Arti- ficial Immune Systems (ICARIS-2004) (Catania, Italy), September 1–3 2004, pp. 477–489.
9. R.D King, S.M. Garrett, and G.M. Coghill, On the use of qualitative reasoning to simulate and identify metabolic pathways, Bioinformatics 21 (2005), 2017– 2026.
10. S. H. Kleinstein, Y. Louzoun, and M. J. Shlomchik, Estimating hypermutation rates from clonal tree data, The Journal of Immunology 171 (2003), no. 9, 4639–4649.
11. S. H. Kleinstein and P. E. Seiden, Simulating the immune system, Computing in Science and Engineering (2000), 69–77.
12. M. Meier-Schellersheim and G. Mack, Simmune, a tool for simulating and analyzing immune system behavior., 1999, http://www-library.desy.de/s.
13. A. Perelson, Modelling viral and immune system dynamics, Nature 2 (2002), 28–36.
14. M. Robbins and S. M. Garrett, Evaluating theories of immunological memory using large-scale simulations, 4th International Conference in Artificial Immune Systems (ICARIS-2005) (Ban., Calgary, Canada), August 14–17 2005, pp. 136– 146.
15. D. J. Smith, S. Forrest, D. H. Ackley, and A. S. Perelson, Variable efficacy of repeated annual influenza vaccination, PNAS 96 (1999), 14001–14006.
16. W. Wilson and S. M. Garrett, Modelling immune memory for prediction and computation, 3rd International Conference on Artificial Immune Systems (ICARIS-04), Springer-Verlag, 2004, pp. 343–352.
17. S. Wolfram, A new kind of science, Wolfram Media Incorporated, 2002.
18. A. Yates, C.C.W Chan, R.E. Callard, A.J.T. George, and J. Stark, An approach to modelling in immunology, Briefings in Bioinformatics 2 (2001), 245–257.
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Garrett, S., Robbins, M. (2006). How Can We Simulate Something As Complex As the Immune System?. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33521-8_50
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DOI: https://doi.org/10.1007/3-540-33521-8_50
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