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Modeling complexity in biology

Author

Listed:
  • Louzoun, Yoram
  • Solomon, Sorin
  • Atlan, Henri
  • Cohen, Irun.R.

Abstract

Biological systems, unlike physical or chemical systems, are characterized by the very inhomogeneous distribution of their components. The immune system, in particular, is notable for self-organizing its structure. Classically, the dynamics of natural systems have been described using differential equations. But, differential equation models fail to account for the emergence of large-scale inhomogeneities and for the influence of inhomogeneity on the overall dynamics of biological systems. Here, we show that a microscopic simulation methodology enables us to model the emergence of large-scale objects and to extend the scope of mathematical modeling in biology. We take a simple example from immunology and illustrate that the methods of classical differential equations and microscopic simulation generate contradictory results. Microscopic simulations generate a more faithful approximation of the reality of the immune system.

Suggested Citation

  • Louzoun, Yoram & Solomon, Sorin & Atlan, Henri & Cohen, Irun.R., 2001. "Modeling complexity in biology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 297(1), pages 242-252.
    • Handle: RePEc:eee:phsmap:v:297:y:2001:i:1:p:242-252
    DOI: 10.1016/S0378-4371(01)00201-1
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    Cited by:

    1. V. L. Stass, 2021. "A Model of Growth Trajectory Bifurcation in Animals Ontogeny," International Journal of Biology, Canadian Center of Science and Education, vol. 12(1), pages 1-20, December.
    2. Indranil Mukherjee & Amitava Sarkar, 2011. "Complexity, Financial Markets and their Scaling Laws," DEGIT Conference Papers c016_008, DEGIT, Dynamics, Economic Growth, and International Trade.

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