Modelling HIV infection: model identification and global sensitivity analysis

Author:

Zheltkova V.V,Zheltkov D.A.,Bocharov G.A.

Abstract

Mathematical modelling can be very useful in studying complex objects in modern systems immunology. In this work we studied the problem of modelling immune cell population dynamics for HIV infection through the set of models with different levels of complexity, which include several characteristics of HIV infection dynamics (antigen presenting, cell and humoral immune reactions, the effect of regulatory T-lymphocytes). We formulated and solved the parameter estimation problem using maximal likelihood approach, for two variants of modelling error quantifying. The global sensitivity analysis was implemented with LHS-PRCC method. Models were compared by the residual functional values and using the information-theoretical framework. We present the extended Marchuk-Petrov model for HIV infection with delays. For solving the parameter estimation problem for this model we compared a number of numerical optimization methods.

Publisher

Institute of Mathematical Problems of Biology of RAS (IMPB RAS)

Subject

Applied Mathematics,Biomedical Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MATHEMATICAL MODELLING OF IMMUNE PROCESSES AND ITS APPLICATION;Biotechnologia Acta;2020-10

2. Global optimization based on TT-decomposition;Russian Journal of Numerical Analysis and Mathematical Modelling;2020-08-26

3. Numerical steady state analysis of the Marchuk–Petrov model of antiviral immune response;Russian Journal of Numerical Analysis and Mathematical Modelling;2020-04-28

4. Application of the Global Optimization Methods for Solving the Parameter Estimation Problem in Mathematical Immunology;Large-Scale Scientific Computing;2020

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