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Using CellML with OpenCMISS to Simulate Multi-Scale Physiology.

David P Nickerson1, David Ladd1, Jagir R Hussan1

  • 1Auckland Bioengineering Institute, University of Auckland , Auckland , New Zealand.

Frontiers in Bioengineering and Biotechnology
|January 21, 2015
PubMed
Summary
This summary is machine-generated.

OpenCMISS integrates CellML models for customizable bioengineering simulations, enhancing multi-scale physiological modeling. This approach simplifies complex computational experiments for researchers, improving reproducibility and interoperability.

Keywords:
CellMLOpenCMISSmulti-scale physiological modelphysiome projectvirtual physiological human

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Area of Science:

  • Bioengineering
  • Computational Biology
  • Multiscale Modeling

Background:

  • OpenCMISS is an open-source environment for bioengineering problems.
  • It comprises computational (OpenCMISS-Iron) and visualization (OpenCMISS-Zinc) libraries.
  • Designed for coupled multi-scale, multi-physics problems in parallel environments.

Purpose of the Study:

  • To detail the integration of CellML models within OpenCMISS for multi-scale physiological modeling.
  • To describe the user interface and demonstrate the extensibility and usability of OpenCMISS.
  • To facilitate customized computational experiments without requiring deep knowledge of OpenCMISS internals.

Main Methods:

  • Utilizing CellML, an XML format for biophysical models, within OpenCMISS.
  • Implementing CellML for configuring cellular electrophysiology, material properties, and boundary conditions.
  • Describing the external interface and providing specific examples of model integration.

Main Results:

  • Successful integration of CellML models into OpenCMISS for diverse bioengineering applications.
  • Demonstrated extensibility and usability for the physiological modeling community.
  • Enabled users to configure complex multi-scale models through a simplified interface.

Conclusions:

  • OpenCMISS effectively leverages CellML to enhance multi-scale physiological modeling.
  • Future extensions include integrating other standards like FieldML, SED-ML, and BioSignalML.
  • Exploration of integrating accelerator code (GPU, FPGA) generated from CellML models is planned.