Dynamics of the HIV infection under antiretroviral therapy: a cellular automata approach
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Publication:1673233
DOI10.1016/j.physa.2013.05.056zbMath1395.92093OpenAlexW2023734936MaRDI QIDQ1673233
Ramón E. R. González, Rita Maria Zorzenon dos Santos, Pedro Hugo de Figueirêdo, Sérgio Coutinho
Publication date: 11 September 2018
Published in: Physica A (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.physa.2013.05.056
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Cites Work
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- Distinct effects of protease and reverse transcriptase inhibition in an immunological model of HIV-1 infection with impulsive drug effects
- A mathematical model of HIV infection: Simulating T4, T8 macrophages, antibody, and virus via specific anti-HIV response in the presence of adaptation and tropism
- A dynamical study of a cellular automata model of the spread of HIV in a lymph node
- Modeling long-term longitudinal HIV dynamics with application to an AIDS clinical study
- Asymmetric division of activated latently infected cells may explain the decay kinetics of the HIV-1 latent reservoir and intermittent viral blips
- Understanding drug resistance for monotherapy treatment of HIV infection
- A viral load-based cellular automata approach to modeling HIV dynamics and drug treatment
- Dynamics of HIV infection of CD4\(^ +\) T cells
- Dynamics of HIV infection on 2D cellular automata
- Optimal drug treatment regimens for HIV depend on adherence
- Mathematical Analysis of HIV-1 Dynamics in Vivo
- Population HIV‐1 Dynamics In Vivo: Applicable Models and Inferential Tools for Virological Data from AIDS Clinical Trials
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