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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
biochemistry, genetics and molecular biology
Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language
BMC Systems Biology, Volume 5, Article 198, Year 2011
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Description
Background: The increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum Information About a Simulation Experiment (MIASE) proposes a minimal set of information that should be provided to allow the reproduction of simulation experiments among users and software tools.Results: In this article, we present the Simulation Experiment Description Markup Language (SED-ML). SED-ML encodes in a computer-readable exchange format the information required by MIASE to enable reproduction of simulation experiments. It has been developed as a community project and it is defined in a detailed technical specification and additionally provides an XML schema. The version of SED-ML described in this publication is Level 1 Version 1. It covers the description of the most frequent type of simulation experiments in the area, namely time course simulations. SED-ML documents specify which models to use in an experiment, modifications to apply on the models before using them, which simulation procedures to run on each model, what analysis results to output, and how the results should be presented. These descriptions are independent of the underlying model implementation. SED-ML is a software-independent format for encoding the description of simulation experiments; it is not specific to particular simulation tools. Here, we demonstrate that with the growing software support for SED-ML we can effectively exchange executable simulation descriptions.Conclusions: With SED-ML, software can exchange simulation experiment descriptions, enabling the validation and reuse of simulation experiments in different tools. Authors of papers reporting simulation experiments can make their simulation protocols available for other scientists to reproduce the results. Because SED-ML is agnostic about exact modeling language(s) used, experiments covering models from different fields of research can be accurately described and combined. © 2011 Waltemath et al; licensee BioMed Central Ltd.
Available Materials
https://efashare.b-cdn.net/share/pmc/articles/PMC3292844/bin/1752-0509-5-198-S1.XML
Authors & Co-Authors
Waltemath, Dagmar
Germany, Rostock
Universität Rostock
Adams, Richard
United Kingdom, Edinburgh
The University of Edinburgh
Bergmann, Frank T.
United States, Pasadena
California Institute of Technology
Hucka, Michael
United States, Pasadena
California Institute of Technology
Kolpakov, Fedor A.
Russian Federation, Novosibirsk
Institute of Systems Biology, Ltd
Miller, Andrew K.
New Zealand, Auckland
Auckland Bioengineering Institute
Moraru, Ion I.
United States, Farmington
Uconn Health
Nickerson, David
New Zealand, Auckland
Auckland Bioengineering Institute
Sahle, Sven
Germany, Heidelberg
Universität Heidelberg
Snoep, Jacky L.
South Africa, Stellenbosch
Stellenbosch University
United Kingdom, Manchester
The University of Manchester
Netherlands, Amsterdam
Vrije Universiteit Amsterdam
Le Novère, Nicolas Le
United Kingdom, London
Wellcome Trust
Statistics
Citations: 11
Authors: 11
Affiliations: 11
Identifiers
Doi:
10.1186/1752-0509-5-198
e-ISSN:
17520509
Study Approach
Quantitative