Article

Biophysical annotation and representation of CellML models.

Auckland Bioengineering Institute, The University of Auckland, 70 Symonds Street, Auckland, New Zealand.
Bioinformatics (Impact Factor: 4.62). 07/2009; 25(17):2263-70. DOI: 10.1093/bioinformatics/btp391
Source: PubMed

ABSTRACT MOTIVATION: CellML is an implementation-independent model description language for specifying and exchanging biological processes. The focus of CellML is the representation of mathematical formulations of biological processes. The language captures the mathematical and model building constructs well, but does not lend itself to capturing the biology these models represent. RESULTS: This article describes the development of an ontological framework for annotating CellML models with biophysical concepts. We demonstrate that, by using these ontological mappings, in combination with a set of graph reduction rules, it is possible to represent the underlying biological process described in a CellML model.

1 Bookmark
 · 
85 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: CellML is a model exchange format designed to greatly facilitate the communication of models. Here we provide a primer on modelling mass-action kinetics with CellML and discuss some of the language features for structuring models. We illustrate these with examples of simple reactions, from which we build a basic biochemical system. We explore some best practices for structuring the models to greatly aid model reusability, as well as communication, and provide information on interacting with the CellML research community. CellML source code for the models in this chapter can be found online at the CellML model Repository (Lloyd et al. 2008), at http://models.cellml.org/workspace/modularmassactionprimer. KeywordsMass-action kinetics-Mathematical modelling-Systems biology-CellML-Modularity
    12/2009: pages 721-750;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Chaste is an open-source C++ library for computational biology that has well-developed cardiac electrophysiology tissue simulation support. In this paper, we introduce the features available for performing cardiac electrophysiology action potential simulations using a wide range of models from the Physiome repository. The mathematics of the models are described in CellML, with units for all quantities. The primary idea is that the model is defined in one place (the CellML file), and all model code is auto-generated at compile or run time; it never has to be manually edited. We use ontological annotation to identify model variables describing certain biological quantities (membrane voltage, capacitance, etc.) to allow us to import any relevant CellML models into the Chaste framework in consistent units and to interact with them via consistent interfaces. This approach provides a great deal of flexibility for analysing different models of the same system. Chaste provides a wide choice of numerical methods for solving the ordinary differential equations that describe the models. Fixed-timestep explicit and implicit solvers are provided, as discussed in previous work. Here we introduce the Rush–Larsen and Generalized Rush–Larsen integration techniques, made available via symbolic manipulation of the model equations, which are automatically rearranged into the forms required by these approaches. We have also integrated the CVODE solvers, a ‘gold standard’ for stiff systems, and we have developed support for symbolic computation of the Jacobian matrix, yielding further increases in the performance and accuracy of CVODE. We discuss some of the technical details of this work and compare the performance of the available numerical methods. Finally, we discuss how this is generalized in our functional curation framework, which uses a domain-specific language for defining complex experiments as a basis for comparison of model behavior.
    Frontiers in Physiology 01/2015; 5:511.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cardiac rhythms arise from electrical activity generated by precisely timed opening and closing of ion channels in individual cardiac myocytes. These impulses spread throughout the cardiac muscle to manifest as electrical waves in the whole heart. Regularity of electrical waves is critically important since they signal the heart muscle to contract, driving the primary function of the heart to act as a pump and deliver blood to the brain and vital organs. When electrical activity goes awry during a cardiac arrhythmia, the pump does not function, the brain does not receive oxygenated blood, and death ensues. For more than 50 years, mathematically based models of cardiac electrical activity have been used to improve understanding of basic mechanisms of normal and abnormal cardiac electrical function. Computer-based modeling approaches to understand cardiac activity are uniquely helpful because they allow for distillation of complex emergent behaviors into the key contributing components underlying them. Here we review the latest advances and novel concepts in the field as they relate to understanding the complex interplay between electrical, mechanical, structural, and genetic mechanisms during arrhythmia development at the level of ion channels, cells, and tissues. We also discuss the latest computational approaches to guiding arrhythmia therapy.
    AJP Heart and Circulatory Physiology 08/2012; 303(7):H766-83. · 4.01 Impact Factor