[Show abstract][Hide abstract] ABSTRACT: CellML is an XML based language for representing mathematical models, in a machine-independent form which is suitable for their exchange between different authors, and for archival in a model repository. Allowing for the exchange and archival of models in a computer readable form is a key strategic goal in bioinformatics, because of the associated improvements in scientific record accuracy, the faster iterative process of scientific development, and the ability to combine models into large integrative models.However, for CellML models to be useful, tools which can process them correctly are needed. Due to some of the more complex features present in CellML models, such as imports, developing code ab initio to correctly process models can be an onerous task. For this reason, there is a clear and pressing need for an application programming interface (API), and a good implementation of that API, upon which tools can base their support for CellML.
We developed an API which allows the information in CellML models to be retrieved and/or modified. We also developed a series of optional extension APIs, for tasks such as simplifying the handling of connections between variables, dealing with physical units, validating models, and translating models into different procedural languages.We have also provided a Free/Open Source implementation of this application programming interface, optimised to achieve good performance.
Tools have been developed using the API which are mature enough for widespread use. The API has the potential to accelerate the development of additional tools capable of processing CellML, and ultimately lead to an increased level of sharing of mathematical model descriptions.
[Show abstract][Hide abstract] ABSTRACT: The development of standards for encoding mathematical models is an important component of model building and model sharing among scientists interested in understanding multi-scale physiological processes. CellML provides such a standard, particularly for models based on biophysical mechanisms, and a substantial number of models are now available in the CellML Model Repository. However, there is an urgent need to extend the current CellML metadata standard to provide biological and biophysical annotation of the models in order to facilitate model sharing, automated model reduction and connection to biological databases. This paper gives a broad overview of a number of new developments on CellML metadata and provides links to further methodological details available from the CellML website.
Full-text · Article · Jun 2009 · Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences
[Show abstract][Hide abstract] ABSTRACT: To facilitate model reuse among European researchers in a new Network of Excellence (NoE) for the EuroPhysiome or "Virtual Physiological Human" (VPH) project, two XML markup languages for encoding biological models, CellML (www.cellml.org) & FieldML (www.fieldml.org), are being further developed. CellML deals with models of so-called ‘lumped parameter’ systems, where spatial effects are averaged, and typically involves systems of ordinary differential equations and algebraic equations. FieldML addresses the spatial variations in cell or tissue properties where the models typically rely on partial differential equations. The two standards can be used together. These languages, which define the structure of a model, the mathematical equations and the associated metadata, enable (i) automated checking to ensure consistency of physical units used in the model equations, (ii) models developed by different groups to be combined using commonly agreed ontological terms within the metadata, (iii) models to be modularized and used in libraries to make it easier to create complex models by importing simpler ones. Model repositories based on these standards and implementing a wide variety of models from peer-reviewed publications have been developed (www.cellml.org/models) and open source software tools for creating, visualizing and executing these models are currently available (www.cellml.org/tools) and under continuous development. This talk will describe the new VPH NoE, new developments in CellML and also briefly describe recent progress on FieldML.