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Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology. / Krivorotko, O. I.; Andornaya, D. V.; Kabanikhin, S. I.

In: Journal of Applied and Industrial Mathematics, Vol. 14, No. 1, 12, 20.03.2020, p. 115-130.

Research output: Contribution to journal › Article › peer-review

Harvard

Krivorotko, OI, Andornaya, DV & Kabanikhin, SI 2020, 'Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology', Journal of Applied and Industrial Mathematics, vol. 14, no. 1, 12, pp. 115-130. https://doi.org/10.1134/S1990478920010123

APA

Krivorotko, O. I., Andornaya, D. V., & Kabanikhin, S. I. (2020). Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology. Journal of Applied and Industrial Mathematics, 14(1), 115-130. [12]. https://doi.org/10.1134/S1990478920010123

Vancouver

Krivorotko OI, Andornaya DV, Kabanikhin SI. Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology. Journal of Applied and Industrial Mathematics. 2020 Mar 20;14(1):115-130. 12. doi: 10.1134/S1990478920010123

Author

Krivorotko, O. I. ; Andornaya, D. V. ; Kabanikhin, S. I. / Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology. In: Journal of Applied and Industrial Mathematics. 2020 ; Vol. 14, No. 1. pp. 115-130.

BibTeX

@article{a752ace81f7c4c44881eb9c9f3e520d2,
title = "Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology",
abstract = "We study the identifiability of some mathematical models of spreading TB and HIV coinfections in a population and the dynamics of HIV-infection at the cellular level. Sensitivity analysis is carried out using the orthogonal method and the eigenvalue method which are based on studying the properties of the sensitivity matrix and show the effect of the model coefficient change on simulation results. Practical identifiability is investigated which determines the possibility of reconstructing coefficients from the noisy experimental data. The analysis is performed using the correlation matrix and Monte Carlo method, while taking into consideration the Gaussian noise in measurements. The results of numerical calculations are presented on whose basis we obtain the identifiable sets of parameters.",
keywords = "identifiability, inverse problem, method of correlation matrix, Monte Carlo method, ordinary differential equations, sensitivity analysis, sensitivity matrix",
author = "Krivorotko, {O. I.} and Andornaya, {D. V.} and Kabanikhin, {S. I.}",
note = "Криворотько О.И., Андорная Д.В., Кабанихин С.И. Анализ чувствительности и практическая идентифицируемость математических моделей биологии // Сибирский журнал индустриальной математики. – 2020. – Т. 23. – № 1. – С. 107-125.",
year = "2020",
month = mar,
day = "20",
doi = "10.1134/S1990478920010123",
language = "English",
volume = "14",
pages = "115--130",
journal = "Journal of Applied and Industrial Mathematics",
issn = "1990-4789",
publisher = "Maik Nauka-Interperiodica Publishing",
number = "1",

}

RIS

TY - JOUR

T1 - Sensitivity Analysis and Practical Identifiability of Some Mathematical Models in Biology

AU - Krivorotko, O. I.

AU - Andornaya, D. V.

AU - Kabanikhin, S. I.

N1 - Криворотько О.И., Андорная Д.В., Кабанихин С.И. Анализ чувствительности и практическая идентифицируемость математических моделей биологии // Сибирский журнал индустриальной математики. – 2020. – Т. 23. – № 1. – С. 107-125.

PY - 2020/3/20

Y1 - 2020/3/20

N2 - We study the identifiability of some mathematical models of spreading TB and HIV coinfections in a population and the dynamics of HIV-infection at the cellular level. Sensitivity analysis is carried out using the orthogonal method and the eigenvalue method which are based on studying the properties of the sensitivity matrix and show the effect of the model coefficient change on simulation results. Practical identifiability is investigated which determines the possibility of reconstructing coefficients from the noisy experimental data. The analysis is performed using the correlation matrix and Monte Carlo method, while taking into consideration the Gaussian noise in measurements. The results of numerical calculations are presented on whose basis we obtain the identifiable sets of parameters.

AB - We study the identifiability of some mathematical models of spreading TB and HIV coinfections in a population and the dynamics of HIV-infection at the cellular level. Sensitivity analysis is carried out using the orthogonal method and the eigenvalue method which are based on studying the properties of the sensitivity matrix and show the effect of the model coefficient change on simulation results. Practical identifiability is investigated which determines the possibility of reconstructing coefficients from the noisy experimental data. The analysis is performed using the correlation matrix and Monte Carlo method, while taking into consideration the Gaussian noise in measurements. The results of numerical calculations are presented on whose basis we obtain the identifiable sets of parameters.

KW - identifiability

KW - inverse problem

KW - method of correlation matrix

KW - Monte Carlo method

KW - ordinary differential equations

KW - sensitivity analysis

KW - sensitivity matrix

UR - http://www.scopus.com/inward/record.url?scp=85082390445&partnerID=8YFLogxK

UR - https://elibrary.ru/item.asp?id=43256965

U2 - 10.1134/S1990478920010123

DO - 10.1134/S1990478920010123

M3 - Article

AN - SCOPUS:85082390445

VL - 14

SP - 115

EP - 130

JO - Journal of Applied and Industrial Mathematics

JF - Journal of Applied and Industrial Mathematics

SN - 1990-4789

IS - 1

M1 - 12

ER -

ID: 23893011