2000/08/08 by Yoram Louzoun, Louzoun, Yoram, Sorin Solomon +5
Biochemistry, Genetics and Molecular Biology · Engineering · Physics and Astronomy · #Artificial Immune Systems Applications #FOS: Biological sciences #FOS: Physical sciences #Gene Regulatory Network Analysis #Quantitative Biology (q-bio) #Statistical Mechanics (cond-mat.stat-mech) #cond-mat.stat-mech #q-bio
paper · pdf · doi:10.48550/arxiv.cond-mat/0008133
arxiv created 2000/08/08 · openalex publication_date 2000/08/08 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.