Modeling sequence evolution in acute HIV-1 infection

DOI10.1016/j.jtbi.2009.07.038zbMath1403.92296OpenAlexW2013914180WikidataQ37384535 ScholiaQ37384535MaRDI QIDQ1628892

Beatrice H. Hahn, Bette T. Korber, Michael S. Saag, Eric L. Delwart, Brandon F. Keele, Alan S. Perelson, Kimmy T. Pham, Ha Youn Lee, Tanmoy Bhattacharya, J. Michael Kilby, Michael P. Busch, Gayathri S. Athreya, Jesus F. Salazar-Gonzalez, Brian Gaschen, Paul A. Goepfert, George M. Shaw, Elena Edi Giorgi

Publication date: 11 December 2018

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2760689

zbMATH Keywords

population dynamicsHIV-1viral evolution

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Monte Carlo methods (65C05) Medical epidemiology (92C60) Research exposition (monographs, survey articles) pertaining to biology (92-02)

Related Items (6)

Estimating the approximate analytical solution of HIV viral dynamic model by using homotopy analysis method ⋮ Modeling sequence evolution in HIV-1 infection with recombination ⋮ Time distribution for persistent viral infection ⋮ An accurate approximation for the expected site frequency spectrum in a Galton-Watson process under an infinite sites mutation model ⋮ Modelling the impact of acute infection dynamics on the accumulation of HIV-1 mutations ⋮ Inference of fitness values and putative appearance time points for evolvable self-replicating molecules from time series of occurrence frequencies in an evolution reactor

Uses Software

• BEAST

Cites Work

• Monte Carlo estimates of natural variation in HIV infection
• Stochastic modeling of the dynamics of \(CD4^ +\) \(T\)-cell infection by HIV and some Monte Carlo studies
• Viral load and stochastic mutation in a Monte Carlo simulation of HIV
• Two‐Sample Tests for Comparing Intra‐Individual Genetic Sequence Diversity between Populations
• A stochastic modeling of early HIV-1 population dynamics
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