standards > model/format > DOI:10.25504/FAIRsharing.6f7m6j
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ready Simulation Experiment Description Markup Language

Abbreviation: SED-ML

General Information
SED-ML is an XML-based format for encoding simulation setups, to ensure exchangeability and reproducibility of simulation experiments. It follows the requirements defined in the MIASE guidelines. 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.


Countries that developed this resource Worldwide

Created in 2008

Taxonomic range

How to cite this record SED-ML; Simulation Experiment Description Markup Language; DOI:; Last edited: June 23, 2021, 1:09 p.m.; Last accessed: Jan 17 2022 3:50 a.m.

This record is maintained by dwaltemath  ORCID

Record updated: June 23, 2021, 11:32 a.m. by The FAIRsharing Team.

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Additional Information

TeSS training resources 

BioSimulators tutorial and help



Access / Retrieve Data

Conditions of Use

Data Release


Reproducible computational biology experiments with SED-ML--the Simulation Experiment Description Markup Language.

Waltemath D,Adams R,Bergmann FT,Hucka M,Kolpakov F,Miller AK,Moraru II,Nickerson D,Sahle S,Snoep JL,Le Novere N
BMC Syst Biol 2011

View Paper (PubMed) View Publication

Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 2.

Bergmann FT,Cooper J,Le Novere N,Nickerson D,Waltemath D
J Integr Bioinform 2015

View Paper (PubMed) View Publication

Related Databases (6)
BioModels is a repository of computational models of biological processes. It allows users to search and retrieve mathematical models published in the literature. Many models are manually curated (to ensure reproducibility) and extensively cross-linked to publicly available reference information.

WholeCellSimDB is a database of whole-cell model simulations designed to make it easy for researchers to explore and analyze whole-cell model predictions including predicted: - Metabolite concentrations, - DNA, RNA and protein expression, - DNA-bound protein positions, - DNA modification positions, and - Ribome positions.

Physiome Model Repository
The Physiome Model Repository (PMR) is the main online repository for the IUPS Physiome Project, providing version and access controlled repositories, called workspaces, for users to store their data. PMR also provides a mechanism to create persistent access to specific revisions of a workspace, termed exposures. Exposure plugins are available for specific types of data (e.g., CellML or FieldML documents) which enable customizable views of the data when browsing the repository via a web browser, or an application accessing the repository’s content via web services.

JWS Online
JWS Online is a Systems Biology tool for the construction, modification and simulation of kinetic models and for the storage of curated models.

BioSimulators is a registry of containerized biosimulation tools that provide consistent command-line interfaces. The BioSimulations web application helps investigators browse this registry to find simulation tools that have the capabilities (supported modeling frameworks, simulation algorithms, and modeling formats) needed for specific modeling projects.

BioSimulations is a web application for sharing and re-using biomodels, simulations, and visualizations of simulations results. BioSimulations supports a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g., COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers discover published models that might be useful for their research and quickly try them via a simple web-based interface.

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Grant Number(s)

  • 031 6194 (Bundesministerium fur Bildung und Forschung (BMBF), Germany)

  • BB/D019621/1 (Biotechnology and Biological Sciences Research Council (BBSRC), UK)

  • DFG Research Training Group 1387/1 (Deutsche Forschungsgemeinschaft (DFG))

  • GM070923 (National Institute of General Medical Sciences (NIGMS), Bethesda, MD, USA)

  • GM081070 (National Institute of General Medical Sciences (NIGMS), Bethesda, MD, USA)

  • P41-RR013186 (U.S. National Library of Medicine)

  • U54-RR022232 (U.S. National Library of Medicine)