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Understanding and Modeling the Complexity of the Immune System

  • Véronique Thomas-VaslinEmail author
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

The immune system is a complex biological micro-ecosystem, adaptive, highly diversified, self-organized and cognitive network of cells, and molecular entities with degeneracy properties. The adaptive immune system has evolved into a complex system of billions of highly diversified lymphocytes all interacting as a connective dynamic multi-scale organized and distributed system, in order to collectively insure body identity and integrity. This complex system insures species preservation of symbiotic and polygenomic organisms. The immune system is characterized by complexity at many different levels; network organization during the development, through fluid cell populations with inter- and intra-cell signalling, an extraordinary lymphocyte somatic receptor diversity, lymphocyte clonotype selection and competition at cell level, migration and interaction inside the immunological tissues and fluid dissemination through the organism, homeostatic regulation, while rapid adaptation to a changing environment. Lymphocytes are the key actors of the immune system of vertebrates, in the middle of a multi-scale biological organization “from molecule to organism,” and at the confluence with other different biological systems and the environment. The perception of antigens induces a network of immuno-receptors that could be viewed as an internal representation of antigens. Fluctuations, variability, and diversity are key factor for the immune system to adapt perturbations and aging and to be or not resilient. Theoretical approaches of this complex system and multi-scale dynamic modeling are a challenge in the domain of complex systems. Theoretical, mathematics, and computer models developed to improve our understanding of the multi-scale complexity of the immune system should be developed.

Keywords

Immune system Perception Antigens Environmental complexity Learning Internal representation Repertoire diversity Memory Ecological system Identity Integrity Circular complex system Dynamics Computer modeling Cognitive network 

Notes

Acknowledgments

This material is based upon work supported by the Complex Systems Institute of Paris Île-de-France (ISC-PIF) and DIM Ile de France; RNSC and support to the ImmunoComplexiT network; CNRS Programme Interdisciplinaire Longévité & Vieillissement, ATC Vieillissement INSERM; Emergence-UPMC program; PHC Tournesol EGIDE, CNRS PEPS BMI; and Investissements d’Avenir program (ANR-11-IDEX-0004-02), LabEx Transimmunom.

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Sorbonne Universités, UPMC Univ Paris 06, INSERM, UMRS959, CNRS, FRE3632, Immunology-Immunopathology-Immunotherapy (I3)ParisFrance

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