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Simulating an HIV Infection In Vivo

  • W. David Wick
  • Otto O. Yang
Chapter

Abstract

When the HIV and CTL models are combined, we have gone beyond familiar textbook examples of biological modeling. Although mathematics provides insights into the predictions of the model (described in subsequent chapters), to some extent we must rely on computer simulation.

Keywords

Ghostly Particle Switch Method Human Lifespan Subsequent Chapter Simulation Routine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Bibliography

  1. [312]
    Wick D, Self SG (2004) On simulating strongly-interacting biological populations. Math Biosci 187:1–20PubMedCrossRefGoogle Scholar
  2. [313]
    Wick D, Self SG (2004) On simulating strongly-interacting biological populations. II. Many-compartment models. Math Biosci 190:127–143PubMedCrossRefGoogle Scholar
  3. [316]
    Wick WD, Gilbert PB, Self SG (2006) On modeling HIV and T cells in vivo: assessing casual estimators in vaccine trials. PLoS Comput Biol 2(6). dx.doi.org/10.1371/journal.pcbi.0020064Google Scholar
  4. [319]
    Wick WD, Yang OO, Corey L, Self SG (2005) How many HIV-1 infected target cells can a cytotoxic T-lymphocyte kill? J Virol 79:1379–1386CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • W. David Wick
    • 1
  • Otto O. Yang
    • 2
  1. 1.SeattleUSA
  2. 2.Geffen School of Medicine, Department of MedicineUCLA Medical CenterLos AngelesUSA

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