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Related Experiment Video

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Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology
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Parameter identifiability of cardiac ionic models using a novel CellML least squares optimization tool.

Ben B B Hui1, Socrates Dokos, Nigel H Lovell

  • 1Graduate School of Biomedical Engineering, University of New South Wales, Sydney 2052, Australia. b.hui@student.unsw.edu.au

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 16, 2007
PubMed
Summary

This study introduces a Java tool for analyzing cardiac cell models in CellML format. The software improves parameter identifiability by using compensatory membrane current and additional stimuli during fitting.

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Area of Science:

  • Computational biology
  • Biophysics
  • Cardiac electrophysiology

Background:

  • Published models of excitable cells are crucial for understanding action potential dynamics.
  • CellML is a standard for model exchange, but lacks dedicated parameter analysis software.
  • Analyzing ionic cardiac cell models is essential for accurate physiological simulations.

Purpose of the Study:

  • To introduce a novel Java-based utility for CellML model analysis.
  • To enable simulation, identifiability analysis, and parameter optimization of cardiac cell models.
  • To address the current gap in software for CellML parameter analysis.

Main Methods:

  • Development of a Java-based utility for CellML model analysis.
  • Application of the utility to seven different CellML ionic cardiac cell models.
  • Performance of identifiability analysis using compensatory membrane current and membrane voltage as residuals.
  • Inclusion of an additional stimulus set in the parameter fitting process.

Main Results:

  • The developed utility successfully performed simulation, identifiability analysis, and parameter optimization.
  • Parameter identifiability was consistently enhanced when using compensatory membrane current as the residual.
  • The introduction of an additional stimulus set further improved parameter identifiability.
  • The software provides a robust platform for analyzing complex cardiac electrophysiology models.

Conclusions:

  • The new Java utility effectively supports the analysis of CellML-based ionic cardiac cell models.
  • Using compensatory membrane current and multiple stimuli are effective strategies for improving parameter identifiability.
  • This work facilitates more accurate and reliable computational modeling in cardiac electrophysiology.