Search Advanced

Mathematical Biosciences and Engineering

2015, Volume 12, Issue 5: 917-936. doi: 10.3934/mbe.2015.12.917
Previous Article Next Article

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
  • 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.
  • Reader Comments
  • © 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)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Mathematical Biosciences and Engineering
4.4

Metrics

Article views(3339) PDF downloads(448) Cited by(0)

Preview PDF
Download XML
Export Citation
Article outline

Other Articles By Authors

Related pages

Tools

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog