Parameter Uncertainty Analysis of a Mathematical Ion Channel Model

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In mathematical modeling of cell physiological processes, measurements required for parameter determination are often available only as aggregated data in the literature. Physiological measurements contain relatively large observation errors due to intrinsic variations in physiological processes, and the errors cause uncertainties in parameter values. This paper reports analyses of the uncertainty in parameter estimates of a simple mathematical model of an ion channel from a set of published experimental data. A conventional approach for estimating model parameters from aggregated data is applying the method of least squares to a series of the mean values of measurements. The parameter estimates by the conventional method significantly differed from those by a statistical approach, maximum likelihood estimation considering the standard errors of the means. Exhaustive analyses on the likelihood of parameter values show high parameter uncertainties and wide distribution of parameter values with no significant differences in the likelihood. These results imply the importance of considering variances of observations and uncertainties in parameter estimates.

Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1952-1955
Number of pages4
ISBN (Electronic)9781538613115
DOIs
Publication statusPublished - Jul 2019
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany
Duration: Jul 23 2019Jul 27 2019

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
CountryGermany
CityBerlin
Period7/23/197/27/19

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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  • Cite this

    Shimayoshi, T. (2019). Parameter Uncertainty Analysis of a Mathematical Ion Channel Model. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 (pp. 1952-1955). [8857142] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2019.8857142