Model annotation and discovery with the Physiome Model Repository

Dewan M Sarwar,Bernard de Bono,John H Gennari,Peter J Hunter,Maxwell L Neal,Brian E Carlson,Reza Kalbasi,David P Nickerson,Koray Atalag

doi:10.1186/s12859-019-2987-y

Abstract

BackgroundMathematics and Phy sics-based simulation models have the potential to help interpret and encapsulate biological phenomena in a computable and reproducible form. Similarly, comprehensive descriptions of such models help to ensure that such models are accessible, discoverable, and reusable. To this end, researchers have developed tools and standards to encode mathematical models of biological systems enabling reproducibility and reuse, tools and guidelines to facilitate semantic description of mathematical models, and repositories in which to archive, share, and discover models. Scientists can leverage these resources to investigate specific questions and hypotheses in a more efficient manner.ResultsWe have comprehensively annotated a cohort of models with biological semantics. These annotated models are freely available in the Physiome Model Repository (PMR). To demonstrate the benefits of this approach, we have developed a web-based tool which enables users to discover models relevant to their work, with a particular focus on epithelial transport. Based on a semantic query, this tool will help users discover relevant models, suggesting similar or alternative models that the user may wish to explore or use.ConclusionThe semantic annotation and the web tool we have developed is a new contribution enabling scientists to discover relevant models in the PMR as candidates for reuse in their own scientific endeavours. This approach demonstrates how semantic web technologies and methodologies can contribute to biomedical and clinical research. The source code and links to the web tool are available at https://github.com/dewancse/model-discovery-tool

Highlights

Mathematics and Phy sics-based simulation models have the potential to help interpret and encapsulate biological phenomena in a computable and reproducible form
We focus on model discovery within the Physiome Model Repository (PMR) [9], but more broadly, our approach could be applied to a variety of model repositories or resources
In this paper we present a web-based tool for model discovery that uses the semantic annotations within PMR

Summary

Introduction

Mathematics and Phy sics-based simulation models have the potential to help interpret and encapsulate biological phenomena in a computable and reproducible form. Comprehensive descriptions of such models help to ensure that such models are accessible, discoverable, and reusable To this end, researchers have developed tools and standards to encode mathematical models of biological systems enabling reproducibility and reuse, tools and guidelines to facilitate semantic description of mathematical models, and repositories in which to archive, share, and discover models. Computational models of human organ systems have been used to support and improve the diagnosis, treatment and prevention of diseases These models help scientists investigate specific research questions and hypotheses which may be ethically inappropriate, expensive to study experimentally, or not practically achievable using human or animal subjects. SemGen combines concepts from a range of ontologies [8]

Methods

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Discussion

Conclusion