Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language
1 Department of Systems Biology & Bioinformatics, Institute of Computer Science, University of Rostock, D-18051 Rostock, Germany
2 Centre for Systems Biology Edinburgh, CHWaddington Building, University of Edinburgh, Edinburgh EH9 3JD, UK
3 California Institute of Technology, 1200 East California Blvd., Pasadena, CA 91125, USA
4 Institute of Systems Biology Ltd., Detskiy proezd 15, Novosibirsk, 630090, Russia
5 Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
6 Center for Cell Analysis and Modeling, University of Connecticut Health Center, Farmington, CT 06030, USA
7 BIOQUANT, University of Heidelberg, Im Neuenheimer Feld 267, Heidelberg, Germany
8 Department of Biochemistry, Stellenbosch University, Privatebag X1, Matieland 7602, South Africa
9 Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, the University of Manchester, 131 Princess Street Manchester, M1 7DN, UK
10 Molecular Cell Physiology, VU University, Amsterdam, The Netherlands
11 EBI, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
BMC Systems Biology 2011, 5:198 doi:10.1186/1752-0509-5-198Published: 15 December 2011
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.
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.
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.