Semantics-based Model Discovery and Composition for Renal Transport

Abstract

In this thesis we present a knowledge management system capable of constructing a novel epithelial model for scientists to investigate their specific research questions and hypotheses. This system comprises a web-based software platform leveraging several community standards, tools and technologies. We have developed this platform that will enable scientists to discover and explore mathematical models, at the cellular and sub-cellular level, from the Physiome Model Repository (PMR). The parameters of such models used in our research are comprehensively annotated with biological information utilising domain ontologies and tooling and then deposited in the PMR. The end result of the model discovery approach is to visualise discovered models in the platform for graphical editing and model assembly. The graphical editing finds similar models based on the annotated information in the PMR and the model assembly constructs the novel epithelial model. In addition, we have performed the software verification of the Platform to compare and predict simulation results between the models in the PMR and the assembled epithelial model.