Using CellML with OpenCMISS to simulate multi-scale physiology

被引:18
|
作者
Nickerson, David P. [1 ]
Ladd, David [1 ]
Hussan, Jagir R. [1 ]
Safaei, Soroush [1 ]
Suresh, Vinod [2 ]
Hunter, Peter J. [1 ]
Bradley, Christopher P. [1 ]
机构
[1] Univ Auckland, Auckland Bioengn Inst, Private Bag 92019,Auckland Mail Ctr, Auckland 1142, New Zealand
[2] Univ Auckland, Dept Engn Sci, Auckland, New Zealand
关键词
CellML; OpenCMISS; physiome project; virtual physiological human; multi-scale physiological model;
D O I
10.3389/fbioe.2014.00079
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
OpenCMISS is an open-source modeling environment aimed, in particular, at the solution of bioengineering problems. OpenCMISS consists of two main parts: a computational library (OpenCMISS-Iron) and a field manipulation and visualization library (OpenCMISS-Zinc). OpenCMISS is designed for the solution of coupled multi-scale, multi-physics problems in a general-purpose parallel environment. CellML is an XML format designed to encode biophysically based systems of ordinary differential equations and both linear and non-linear algebraic equations. A primary design goal of CellML is to allow mathematical models to be encoded in a modular and reusable format to aid reproducibility and interoperability of modeling studies. In OpenCMISS, we make use of CellML models to enable users to configure various aspects of their multi-scale physiological models. This avoids the need for users to be familiar with the OpenCMISS internal code in order to perform customized computational experiments. Examples of this are: cellular electrophysiology models embedded in tissue electrical propagation models; material constitutive relationships for mechanical growth and deformation simulations; time-varying boundary conditions for various problem domains; and fluid constitutive relationships and lumped-parameter models. In this paper, we provide implementation details describing how CellML models are integrated into multi-scale physiological models in OpenCMISS. The external interface OpenCMISS presents to users is also described, including specific examples exemplifying the extensibility and usability these tools provide the physiological modeling and simulation community. We conclude with some thoughts on future extension of OpenCMISS to make use of other community developed information standards, such as FieldML, SED-ML, and BioSignalML. Plans for the integration of accelerator code (graphical processing unit and field programmable gate array) generated from CellML models is also discussed.
引用
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页数:10
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