title: Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review.
abstract: Recently, the description of immune response by discrete models has emerged to play an important role to study the problems in the area of human immunodeficiency virus type 1 (HIV-1) infection, leading to AIDS. As infection of target immune cells by HIV-1 mainly takes place in the lymphoid tissue, cellular automata (CA) models thus represent a significant step in understanding when the infected population is dispersed. Motivated by these, the studies of the dynamics of HIV-1 infection using CA in memory have been presented to recognize how CA have been developed for HIV-1 dynamics, which issues have been studied already and which issues still are objectives in future studies.
authors.affiliation: 1 Institute for Innovative Learning, Mahidol University, 999 Salaya, Phutthamonthon District Nakhon Pathom 73170, Thailand.
authors.forename: Monamorn
authors.initials: M
authors.lastname: Precharattana
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000209:etiology; D015496:CD4-Positive T-Lymphocytes / Q000821:virology; D015658:HIV Infections / Q000188:drug therapy* / Q000209:etiology* / Q000473:pathology; D015497:HIV-1 / Q000472:pathogenicity; D006801:Humans; D008954:Models, Biological; D013269:Stochastic Processes
keywords: Cellular automaton; discrete model; infectious disease