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Man–Machine Interactions 4 pp 195–204Cite as

Parameter Estimation in Systems Biology Models by Using Extended Kalman Filter

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 391))

Abstract

Models in systems biology, which reflect complex dynamic biological phenomena are most often described as ordinary differential equations (ODE). Characteristic properties of these differential equations is nonlinearity and large size (number of state variables). These models also contain large numbers of unknown parameters. So the main challenge in developing models in systems biology is estimation of numerous unknown parameters in nonlinear differential equations. There are already numerous approaches to parameter estimation in systems biology models. However, main difficulties speed of convergence and multiple minima (multiple solutions) are still obstacles in achieving solutions of sufficient efficiency. In this chapter we propose a new approach based on combination of extended Kalman filtering dynamical optimization with spline approximation of solutions to ODE, for parameter estimation in systems biology models. We present the main idea and we show comparisons to some published results.

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Acknowledgments

This chapter was partially financially supported by the NCN Opus grant UMO-2011/01/B/ST6/06868 to AP. Computations were performed with the use of the infrastructure provided by the NCBIR POIG.02.03.01-24-099/13 grant: GCONiI—Upper-Silesian Center for Scientific Computations.

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Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Michal Capinski & Andrzej Polanski

Authors
  1. Michal Capinski
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  2. Andrzej Polanski
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Corresponding author

Correspondence to Michal Capinski .

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Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Brachman

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

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Capinski, M., Polanski, A. (2016). Parameter Estimation in Systems Biology Models by Using Extended Kalman Filter. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_16

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  • DOI: https://doi.org/10.1007/978-3-319-23437-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23436-6

  • Online ISBN: 978-3-319-23437-3

  • eBook Packages: EngineeringEngineering (R0)

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