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Epithelial Modelling Platform: A Tool for Investigating Hypotheses through Discovery and Assembly of Computational Models of Epithelial Transport

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posted on 19.03.2019 by Dewan Sarwar, Koray Atalag, Peter Hunter, David Nickerson
David Nickerson presented this poster at the HARMONY 2019 meeting in California, March 2019, and at the Experimental Biology meeting 2019 in Florida, April 2019.


Scientists often leverage computational models of biological systems to investigate hypotheses which are difficult or prohibitively expensive to achieve experimentally. Such investigations are best achieved by utilizing suitable computational models, reusing existing validated models where possible and creating novel models consistently as needed. This requires tools which enable the discovery and exploration of existing models matched with assistance in constructing and testing new models. Enabling scientists or clinicians to use such a tool by describing their requirements in a manner familiar to themselves greatly improves the accessibility of the tool.

We have developed a web-based tool, the Epithelial Modelling Platform, for scientists and clinicians to discover relevant models and then assemble these into a novel model customized for investigating their hypotheses. While our tool specifically focuses on epithelial transport, by utilizing relevant community standards and publicly accessible knowledge repositories, it is extensible to other areas of application. The platform abstracts underlying mathematics of the computational models and provides a visual environment which mimics biological phenomena of an epithelial cell.

Beyond the mathematical models, we have implemented a feature to discover existing simulation experiments which match the features of the novel models users create. By executing these simulation experiments with the novel models and comparing to previous model predictions and/or experimental or clinical observations we are able to provide the user with some measure of verification that their model matches, or doesn’t match, existing knowledge captured in the various repositories utilized.


Aotearoa Foundation; MedTech CoRE