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Matematicheskaya Biologiya i Bioinformatika, 2019, Volume 14, Issue 1, Pages 19–33
DOI: https://doi.org/10.17537/2019.14.19
(Mi mbb370)
 

This article is cited in 4 scientific papers (total in 4 papers)

Mathematical Modeling

Modelling HIV infection: model identification and global sensitivity analysis

V. V. Zheltkovaa, D. A. Zheltkovb, G. A. Bocharovb

a Lomonosov Moscow State University
b Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences, Moscow, Russia
Full-text PDF (755 kB) Citations (4)
References:
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.
Funding agency Grant number
Russian Foundation for Basic Research 18-31-00356
17-01-00636
Received 28.12.2018, Published 06.02.2019
Document Type: Article
UDC: 51.76
Language: Russian
Citation: V. V. Zheltkova, D. A. Zheltkov, G. A. Bocharov, “Modelling HIV infection: model identification and global sensitivity analysis”, Mat. Biolog. Bioinform., 14:1 (2019), 19–33
Citation in format AMSBIB
\Bibitem{ZheZheBoc19}
\by V.~V.~Zheltkova, D.~A.~Zheltkov, G.~A.~Bocharov
\paper Modelling HIV infection: model identification and global sensitivity analysis
\jour Mat. Biolog. Bioinform.
\yr 2019
\vol 14
\issue 1
\pages 19--33
\mathnet{http://mi.mathnet.ru/mbb370}
\crossref{https://doi.org/10.17537/2019.14.19}
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  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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