Publication: Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review
Issued Date
2016-02-01
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ISSN
17576334
02197200
02197200
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2-s2.0-84959319386
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Mahidol University
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SCOPUS
Bibliographic Citation
Journal of Bioinformatics and Computational Biology. Vol.14, No.1 (2016)
Suggested Citation
Monamorn Precharattana Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review. Journal of Bioinformatics and Computational Biology. Vol.14, No.1 (2016). doi:10.1142/S021972001630001X Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/43030
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Title
Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review
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Abstract
© 2016 Imperial College Press. 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.