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Parameter Estimation and Model Selection

  • Gennady BocharovEmail author
  • Vitaly Volpert
  • Burkhard Ludewig
  • Andreas Meyerhans
Chapter

Abstract

In this chapter, we illustrate a data-driven methodology to formulation and calibration of mathematical models of immune responses. The maximum likelihood approach to parameter estimation, Tikhonov regularization method and information-theoretic criteria for model ranking and selection are presented for models formulated with ODEs, DDEs and PDEs. Experimental data on CFSE-based proliferation analysis of T cells and LCMV–CTL dynamics in a low dose experimental infection of mice are used.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Gennady Bocharov
    • 1
    Email author
  • Vitaly Volpert
    • 2
    • 3
  • Burkhard Ludewig
    • 4
  • Andreas Meyerhans
    • 5
  1. 1.Marchuk Institute of Numerical MathematicsRussian Academy of SciencesMoscowRussia
  2. 2.Institut Camille Jordan, UMR 5208 CNRSCentre National de la Recherche Scientifique (CNRS)VilleurbanneFrance
  3. 3.RUDN UniversityMoscowRussia
  4. 4.Institute of ImmunobiologyKantonsspital St. GallenSt. GallenSwitzerland
  5. 5.Parc de Recerca Biomedica BarcelonaICREA and Universitat Pompeu FabraBarcelonaSpain

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