Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit
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Abstract
The COMBINE archive is a digital container format for files related to a virtual experiment in computational biology. It eases the management of numerous files related to a simulation study, fosters collaboration, and ultimately enables the exchange of reproducible research results. The CombineArchive Toolkit is a software for creating, exploring, modifying, and sharing COMBINE archives. Open model repositories such as BioModels Database are a valuable resource of models and associated simulation descriptions. However, so far no tool exists to export COMBINE archives for a given simulation study from such databases. Here we demonstrate how the CombineArchiveToolkit can be used to extract reproducible simulation studies from model repositories. We use the example of Masymos, a graph database with a sophisticated link concept to connect model-related files on the storage layer.
Cite this as
2015. Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit. PeerJ PrePrints 3:e792v1 https://doi.org/10.7287/peerj.preprints.792v1note This preprint is not peer-reviewed. You may wish to reference the subsequent peer-reviewed version of this article.
Author comment
This article is submitted for the Workshop on Data Management for Life Sciences (DMforLS) 2015 at BTW 2015, Hamburg, Germany.
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Competing Interests
The authors declare they have no competing interests.
Author Contributions
Martin Scharm conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Dagmar Waltemath conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Funding
MS and DW are funded by the German Federal Ministry of Education and Research (e:Bio program SEMS, FKZ 031 6194). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
