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

Area of Science:

• Computational Biology
• Bioinformatics
• Scientific Simulation

Background:

• Computational simulation experiments are increasingly vital in biological research.
• Reproducibility, annotation, and sharing of these experiments present significant challenges.
• The Minimum Information About a Simulation Experiment (MIASE) standard addresses these issues by defining essential information for experiment reproduction.

Purpose of the Study:

• To introduce the Simulation Experiment Description Markup Language (SED-ML) as a solution for encoding simulation experiment information.
• To enable the exchange and reproduction of computational simulation experiments across different software tools.

Main Methods:

• Development of SED-ML as a community project with a detailed technical specification and XML schema.
• Encoding of MIASE-required information into a computer-readable exchange format.
• Focus on time course simulations, a common type in the field.

Main Results:

• SED-ML Version 1.1 is presented as a software-independent format for describing simulation experiments.
• SED-ML specifies models, modifications, simulation procedures, and output/presentation of results.
• Demonstrated effective exchange of executable simulation descriptions through growing software support for SED-ML.

Conclusions:

• SED-ML facilitates the exchange of simulation experiment descriptions, enabling validation and reuse across diverse software.
• Authors can share simulation protocols for result reproduction, enhancing scientific transparency.
• SED-ML's model-agnostic nature allows accurate description and combination of experiments from various research fields.