Abstract
Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific model classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a Modeling and Analysis Generic Platform with Integrated Evaluation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de.
Highlights
The development and use of computational models is gaining more and more importance in the era of biological and big data, there is a distinct gap between the development of computational models by theoreticians and their application by end users in experimental research or clinical practice [1,2,3]
MAGPIE has been designed as a software platform for both, publishing and executing computational models
New models and analysis tools can be registered to MAGPIE within the browser to make them available to other users
Summary
The development and use of computational models is gaining more and more importance in the era of biological and big data, there is a distinct gap between the development of computational models by theoreticians and their application by end users in experimental research or clinical practice [1,2,3]. The main objective of MAGPIE is to provide a user-friendly system to publish, version, access and execute models in an environment that is accessible for different end users. The central layers of MAGPIE are a repository of models and analysis tools, a project-oriented access to the models that allows changing parameter configurations and data input, program execution, visualization of results, as well as a twitter-like hashtag system to simplify the sharing of results increasing the visibility of individual researchers.
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