Advertisement

Understanding the Immune System by Computer-Aided Modeling

  • Massimo Bernaschi
  • Filippo Castiglione

Abstract

We describe some computer models of the immune system and in particular of its response to the HIV infection. Then we introduce our model and show some results of simulations of the AIDS disease progression.

Keywords

Cellular Automaton Discrete Model Binary String Shape Space Immune Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agur, Z. (1991) Fixed points of majority rule cellular automata with application to plasticity and precision of the immune system. Complex Syst. 5:351-357.Google Scholar
  2. Anachini, A., and Mortarini, R. (1999) Il Controllo della Crescita Neoplastica: Ruoli Dell’Immunitá specifica nella risposta alle metastasi. In: G. Bevilacqua, R. Gavari, and P.L. Lollini (Eds.), Invasione e Metastasi. Pacini Editore, Pisa, pp. 325-340.Google Scholar
  3. Atlan, H., and Cohen, I.R. (1989) Theories of Immune Networks. Springer-Verlag, Berlin.Google Scholar
  4. Bernaschi, M. and Castiglione, F. (2002) Selection of escape mutants from immune recognition during HIV infection. Immunol. Cell Biol. 80:307-313.PubMedCrossRefGoogle Scholar
  5. Bernaschi, M., and Castiglione, F. (2006) HIV-1 strategies of immune evasion. Int. J. Mod. Phys. C 16:1869-1879.Google Scholar
  6. Brass, A., Bancroft, A.J., Clamp, M.E., Grencis, R.K., and Else, K.J. (1994) Dynamical and critical behavior of a simple discrete model of the cellular immune system. Phys. Rev. E 50:1589-1593.CrossRefGoogle Scholar
  7. Burnet, F. (1959) The Clonal Selection Theory of Acquired Immunity. Vanderbilt University, Nashville.Google Scholar
  8. Carbone, A., and Gaidano, G. (2001) Acquired immunodeficiency syndrome-related cancer. A study model for the mechanisms contributing to the genesis of cancer. Eur. J. Cancer 37:1184-1187.PubMedCrossRefGoogle Scholar
  9. Castiglione, F., Poccia, F., D’Offizi, G., and Bernaschi, M. (2004) Mutation, fitness, viral diversity and predictive markers of disease progression in a computational model of HIV-1 infection. AIDS Res. Hum. Retrovir. 20:1314-1323.PubMedCrossRefGoogle Scholar
  10. Celada, F., and Seiden, P.E. (1992) A computer model of cellular interaction in the immune system. Immunol. Today 13(2):56-62.Google Scholar
  11. Celada, F., and Seiden, P.E. (1996) Affinity maturation and hypermutation in a simulation of the humoral immune response. Eur. J. Immunol. 26:1350-1358.PubMedCrossRefGoogle Scholar
  12. Chowdhury, D., Stauffer, D., and Choudary, P.V. (1990) A unified discrete model of immune response. J. Theor. Biol. 145:207-215.PubMedCrossRefGoogle Scholar
  13. Chowdhury, D., and Stauffer, D. (1992) Statistical physics of immune networks. Physica A 186:61-81.CrossRefGoogle Scholar
  14. Chowdhury, D., Deshpande, V., and Stauffer, D. (1994) Modelling immune network through cellular automata: A unified mechanism of immunological memory. Int. J. Mod. Phys. C 5:1049-1072.CrossRefGoogle Scholar
  15. Chowdhury, D. (1998) Immune network: An example of complex adaptive systems. In: D. Dasgupta (Ed.), Artificial Immune Systems and Their Applications. Springer-Verlag, Heidelberg, pp. 84-104. Cohen, I.R., and Atlan, H. (1989) Network regulation of autoimmunity: An automation model. J. Autoimmun. 2:613-625.Google Scholar
  16. Dayan, I., Havlin, S., and Stauffer, D. (1988) Cellular automata generalization of the Weisbuch-Atlan model for immune response. J. Phys. A 21:2473-2476.CrossRefGoogle Scholar
  17. Farmer, J.D., Packard, N., and Perelson, A.S. (1986) The immune system, adaptation and machine learning. Physica D 22:187-204.CrossRefGoogle Scholar
  18. Forrest, S., and Hofmeyr, S.A. (2000) Immunology as information processing. In: L.A. Segel and L. Cohen (Eds.), Design Principles for the Immune System and Other Distributed Autonomous Systems. Santa Fe Institute Studies in the Sciences of Complexity. Oxford University Press, New York, pp. 361-387.Google Scholar
  19. Hershberg, U.R., Louzoun, Y., Atlan, H., and Solomon, S. (2001) HIV time hierarchy: Winning the war while losing all the battles. Physica A 289:178-190.CrossRefGoogle Scholar
  20. Jerne, N.K. (1973) The immune system. Sci. Am. 229:52-60.PubMedCrossRefGoogle Scholar
  21. Jerne, N.K. (1974) Towards a network theory of the immune system. Ann. Immunol. 125C:373-389.Google Scholar
  22. Kaufman, M., Urbain, J., and Thomas, R. (1985) Towards a logical analysis of the immune response. J. Theor. Biol. 114:527-561.PubMedCrossRefGoogle Scholar
  23. Kitano, H. (2001) System biology: Toward system-level understanding of biological system. In: H. Kitano (Ed.), Foundations of System Biology. MIT Press, Cambridge, MA, pp. 1-36.Google Scholar
  24. Melief, C.J., Toes, R.E., Medema, J.P., Van der Burg, S.H., Ossendorp, F., and Offringa, R. (2000) Strategies for immunotherapy of cancer. Adv. Immunol. 75:235-282.Morpurgo, D., Serenthà, R., Seiden, P.E., and Celada, F. (1995) Modelling thymic functions in a cellular automaton. Int. Immunol. 7:505-516.Google Scholar
  25. Mosier, D., and Sieburg, H.B. (1994) Macrophage-tropic HIV: Critical for AIDS pathogenesis? Immunol. Today 15:332-339.PubMedCrossRefGoogle Scholar
  26. Pandey, R.B., and Stauffer, D. (1989) Immune response via interacting three dimensional network of cellular automata. J. Phys. (Paris) 50:1-12.Pandey, R.B., and Stauffer, D. (1990) Metastability with probabilistic cellular automata in an HIV infection. J. Stat. Phys. 61:235-240.Google Scholar
  27. Pandey, R.B. (1991) Cellular automata approach to interacting cellular network models for the dynamics of cell population in an early HIV infection. Physica A 179:442-470.CrossRefGoogle Scholar
  28. Pantaleo, G., Graziosi, C., and Fauci, A.S. (1993) New concepts in the immunopathogenesis of human immunodeficiency virus infection. N. Engl. J. Med. 328:327-335.PubMedCrossRefGoogle Scholar
  29. Perelson, A.S., and Oster, G.F. (1979) Theoretical studies on clonal selection: Minimal antibody repertoire size and reliability of self-nonself discrimination. J. Theor. Biol. 81:645-670.PubMedCrossRefGoogle Scholar
  30. Perelson, A.S. (Ed.) (1988a) Theoretical Immunology, Part II. Addison Wesley, Redwood City.Google Scholar
  31. Perelson, A.S. (Ed.) (1988b) Theoretical Immunology, Part I. Addison Wesley, Redwood City.Google Scholar
  32. Perelson, A.S., and Weisbuch, G.I. (1997) Immunology for physicists. Rev. Mod.Phys. 69:1219-1267.CrossRefGoogle Scholar
  33. Perelson, A.S., and Nelson, P.W. (1999) Mathematical analysis of HIV-1 dynamics in vivo. SIAM Rev. 41:3-44. Preziosi, L. (Ed.) (2003) Cancer Modelling and Simulation. CRC Press , London.Google Scholar
  34. Ruskin, H.J., Pandey, R.B., and Liu, Y. (2002) Viral load and stochastic mutation in a Monte Carlo simulation of HIV. Physica A 311:213-220.CrossRefGoogle Scholar
  35. Segel, L.A., and Perelson, A.S. (1991) Exploiting the diversity of time scales in the immune system: A B-cell antibody model. J. Stat. Phys. 63:1113-1131.CrossRefGoogle Scholar
  36. Sieburg, H.B., McCutchan, J.A., Clay, O., Caballero, L., Ostlund, and James, J. (1990) Simulation of HIV-infection in artificial immune systems. Physica D 45:208-227.CrossRefGoogle Scholar
  37. Stauffer, D. (1989) Immunologically motivated cellular automata. In: A. Pires, D.P. Landau, and H.J. Herrmann (Eds.), Computational Physics and Cellular Automata. World Scientific, Singapore, pp. 89-97.Google Scholar
  38. Thomè, T., and Drugowich de Felício, J.R. (1996) Probabilistic cellular automaton describing a biological immune system. Phys. Rev. E 53:3976-3981.CrossRefGoogle Scholar
  39. Varthakavi, V., Smith, R.M., Deng, H., Sun, R., and Spearman, P. (2002) Human immunodeficiency virus type-1 activates lytic cycle replication of Kaposi’s sarcoma-associated herpesvirus through induction of KSHV Rta. Virology 297:270-280.PubMedCrossRefGoogle Scholar
  40. Weisbuch, G.I., and Atlan, H. (1988) Control of the immune response J. Phys. A 21:189-192.CrossRefGoogle Scholar
  41. Zorzenon dos Santos, R.M. (1999) Immune responses: Getting close to experimental results with cellular automata models. In: D. Stauffer (Ed.), Annual Review of Computational Physics VI. World Scientific, Singapore, pp. 159-202.Google Scholar
  42. Zorzenon dos Santos, R.M., and Coutinho, S.C. (2001) The dynamics of the HIV infection: Acellular automata approach. Phys. Rev. Lett. 87:168102-168114.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2008

Authors and Affiliations

  • Massimo Bernaschi
    • 1
  • Filippo Castiglione
    • 1
  1. 1.Institute for Computing Applications (IAC), National Research Council (CNR)Viale del Policlinico 137Italy

Personalised recommendations