title: Reproducible computational biology experiments with SED-ML--the Simulation Experiment Description Markup Language.
abstract: 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.
authors.affiliation: Department of Systems Biology & Bioinformatics, Institute of Computer Science, University of Rostock, D-18051 Rostock, Germany.
authors.forename: Dagmar
authors.initials: D
authors.lastname: Waltemath
authors.forename: Richard
authors.initials: R
authors.lastname: Adams
authors.forename: Frank T
authors.initials: FT
authors.lastname: Bergmann
authors.forename: Michael
authors.initials: M
authors.lastname: Hucka
authors.forename: Fedor
authors.initials: F
authors.lastname: Kolpakov
authors.forename: Andrew K
authors.initials: AK
authors.lastname: Miller
authors.forename: Ion I
authors.initials: II
authors.lastname: Moraru
authors.forename: David
authors.initials: D
authors.lastname: Nickerson
authors.forename: Sven
authors.initials: S
authors.lastname: Sahle
authors.forename: Jacky L
authors.initials: JL
authors.lastname: Snoep
authors.forename: Nicolas
authors.initials: N
authors.lastname: Le Novère
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D011381:Programming Languages; D015203:Reproducibility of Results; D012984:Software