A cellular automata model considering diversity associated with HIV infection

Hiroshi Ueda, Yukio Iwaya, Toru Abe, Tetsuo Kinoshita

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The diversity of human immunodeficiency virus (HIV) in vivo has been reported. In this article, we propose a cellular automata (CA) model describing the interactions between the immune system and HIV, and examine the effect of the diversity of these interactions. The novel aspects of our CA model are that it not only considers four states (HIV, virgin, dead, infect) but also the diversity exhibited by both HIV and T cells. We simulated maximum diversities for these states by simulating CA on a computer. The model revealed that increased diversity had the effect of increasing the HIV population and simulation steps. In addition, we observed that the CA model accurately reflects the occurrence of infection, incubation period, and the development of AIDS. The CA model demonstrated that the diversity of the virus is the major factor affecting the success rate of the escape of HIV from the immune response.

Original languageEnglish
Pages (from-to)73-76
Number of pages4
JournalArtificial Life and Robotics
Volume10
Issue number1
DOIs
Publication statusPublished - 2006 Jul 1

Keywords

  • Cellular automata
  • HIV
  • Immune system

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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