• DocumentCode
    2291538
  • Title

    Modeling immune cognition

  • Author

    Celada, Franco ; Seiden, Philip

  • Author_Institution
    Genoa Univ., Italy
  • Volume
    4
  • fYear
    1998
  • fDate
    11-14 Oct 1998
  • Firstpage
    3787
  • Abstract
    We believe that organism´s defences have gradually evolved into a real cognitive system after cell membrane receptors underwent diversification in early fish, some 300 million years ago. The somatic repertoires grow by combinatorial power, as receptors are assembled from germ line information, by an aleatory and error prone process. There is no doubt that a cellular automaton is well suited as the vehicle for modeling these aspects of the immune response. In its simplest form, the model consists of a 15×15 bidimensional grid, containing different cell types, each expressing receptors in a form of 8-bit binary strings. Antigens and antibodies interact if they meet within a site and if the respective bits are complementary. The rules and cell programs are drawn with a keen eye to current biological consensus, and the model behaves like an immune system. We review the principle and the achievements of the IMMSIM model and present preliminary results of the combined cellular and humoral responses to a viral infection
  • Keywords
    cellular automata; cognitive systems; evolution (biological); physiological models; antibodies; antigens; binary strings; cell membrane receptors; cellular automaton; cognitive system; immune response; immune system; organism defence; physiological model; viral infection; Assembly; Automata; Biological system modeling; Biomembranes; Cells (biology); Cognition; Immune system; Marine animals; Power system modeling; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4778-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1998.726677
  • Filename
    726677