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Application of Adjoint Sensitivity Analysis to Parameter Estimation of Age-Structured Model of Cell Cycle

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Information Technologies in Medicine (ITiB 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 472))

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Abstract

Age-structured models describe heterogeneous populations of individuals. Life of the individual consist of a finite number of phases, which differ in properties such as the ability to reproduce. This approach allows more realistic modelling of the population growth than using models assuming homogeneity of the population, which is especially important for complex organisms with long reproduction time. The aim of this study was to develop a methodology to estimate parameters of the age-structured model of cell cycle using adjoint sensitivity analysis. Results were obtained for artificially generated input data.

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Acknowledgments

The presented work was supported by the Polish National Science Center (NCN) under grants: DEC-2013/11/B/ST7/01713 (MJ) and DEC-2012/05/B/ST6/03472 (KF).

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Authors and Affiliations

  1. Faculty of Automatic Control, Electronics and Computer Science, Institute of Automatic Control, Silesian University of Technology, Akademicka 16, Gliwice, Poland

    Michał Jakubczak & Krzysztof Fujarewicz

Authors
  1. Michał Jakubczak
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  2. Krzysztof Fujarewicz
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Corresponding author

Correspondence to Michał Jakubczak .

Editor information

Editors and Affiliations

  1. Fac of Biomed Engg, ul. Roosevelta 40, Silesian University of Technology, Gliwice, Poland

    Ewa Piętka

  2. Fac of Biomed Engg, ul. Roosevelta 40, Silesian University of Technology, Gliwice, Poland

    Pawel Badura

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Jacek Kawa

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Wojciech Wieclawek

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Jakubczak, M., Fujarewicz, K. (2016). Application of Adjoint Sensitivity Analysis to Parameter Estimation of Age-Structured Model of Cell Cycle. In: Piętka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technologies in Medicine. ITiB 2016. Advances in Intelligent Systems and Computing, vol 472. Springer, Cham. https://doi.org/10.1007/978-3-319-39904-1_11

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  • DOI: https://doi.org/10.1007/978-3-319-39904-1_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39903-4

  • Online ISBN: 978-3-319-39904-1

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