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Mathematical Biosciences and Engineering

2015, Volume 12, Issue 5: 917-936. doi: 10.3934/mbe.2015.12.917
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Parameters identification for a model of T cell homeostasis

  • 1.
    IMB UMR CNRS 5251, Bordeaux University, 3 Place de la Victoire, 33076 Bordeaux Cedex
  • 2.
    INSERM U897, ISPED, Bordeaux University, Bordeaux
  • Received: 01 November 2014 Accepted: 29 June 2018 Published: 01 June 2015

  • MSC : Primary: 92B05, 58J45; Secondary: 93B30.

  • In this study, we consider a model of T cell homeostasis based on the Smith-Martin model. This nonlinear model is structured by age and CD44 expression. First, we establish the mathematical well-posedness of the model system. Next, we prove the theoretical identifiability regarding the up-regulation of CD44, the proliferation time phase and the rate of entry into division, by using the experimental data. Finally, we compare two versions of the Smith-Martin model and we identify which model fits the experimental data best.

    Citation: Houssein Ayoub, Bedreddine Ainseba, Michel Langlais, Rodolphe Thiébaut. Parameters identification for a model of T cell homeostasis[J]. Mathematical Biosciences and Engineering, 2015, 12(5): 917-936. doi: 10.3934/mbe.2015.12.917

    Related Papers:

  • In this study, we consider a model of T cell homeostasis based on the Smith-Martin model. This nonlinear model is structured by age and CD44 expression. First, we establish the mathematical well-posedness of the model system. Next, we prove the theoretical identifiability regarding the up-regulation of CD44, the proliferation time phase and the rate of entry into division, by using the experimental data. Finally, we compare two versions of the Smith-Martin model and we identify which model fits the experimental data best.


    加载中
    [1] Mathematical biosciences, 251 (2014), 63-71.
    [2] Biophysical Journal, 84 (2003), 3414-3424.
    [3] Bulletin of Mathematical Biology, 68 (2006), 1011-1031.
    [4] Cell Proliferation, 3 (1970), 321-334.
    [5] 1932.
    [6] Microbes and Infection, 4 (2002), 529-530.
    [7] Annual Review of Immunology, 18 (2000), 83-111.
    [8] The Journal of Immunology, 179 (2007), 950-957.
    [9] Journal of Immunological Methods, 298 (2005), 183-200.
    [10] Proceedings of the National Academy of Sciences of the United States of America, 101 (2004), 16885-16890.
    [11] Nat Immunol, 7 (2006), 475-481.
    [12] The Journal of Immunology, 190 (2013), 3985-3993.
    [13] Seminars in Immunology, 17 (2005), 231-237.
    [14] Nature Reviews Immunology, 2 (2002), 547-556.
    [15] Bulletin of Mathematical Biology, 71 (2009), 1649-1670.
    [16] Bulletin of Mathematical Biology, 70 (2008), 21-44.
    [17] Journal of Theoretical Biology, 225 (2003), 275-283.
    [18] Immunol Cell Biol, 77 (1999), 499-508.
    [19] Proceedings of the National Academy of Sciences, 70 (1973), 1263-1267.
    [20] Science, 276 (1997), 2057-2762.
    [21] Visual Numerics, 1996.
    [22] The Journal of Immunology, 180 (2008), 1414-1422.
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  • © 2015 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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