Key result
A standard using well-annotated CellML models is proposed to define reference descriptions of cellular electrophysiology models in an unambiguous, software-independent, and machine-readable format.
Proposes a standard for machine-readable reference descriptions of cellular electrophysiology models using CellML to improve model curation.
May standardize cardiac model curation; leaves open whether adoption enhances reproducibility or clinical translation.
UNLABELLED: In recent years there has been much development of the fundamental ideas underlying mathematical model curation in regard to models of biology. While much has been achieved in the realms of systems biology and bioinformatics, little progress has been made in relation to cellular electrophysiology modeling. The primary reason for slow progress in this field is the lack of a consistent and machine-readable reference description for a given model. CellML has been widely used to describe mathematical models of cellular electrophysiology in an unambiguous, machine-readable format. Through the use of well-annotated CellML models we propose a standard by which reference descriptions of cellular electrophysiology models can be similarly defined in an unambiguous, software independent, and machine-readable format. Adoption of this standard will provide a consistent technology by which cellular electrophysiology models can be curated. AVAILABILITY: http://www.bioeng.nus.edu.sg/compbiolab/p2/
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Nickerson et al. (2008) studied cellular electrophysiology modeling. CellML standard for reference descriptions was evaluated. A standard using well-annotated CellML models is proposed to define reference descriptions of cellular electrophysiology models in an unambiguous, software-independent, and machine-readable format.
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