Authors:
Michael A. Guravage
and
Roeland M. H. Merks
Affiliation:
Netherlands Consortium for Systems Biology & Netherlands Institute for Systems Biology (NCSB-NISB), Netherlands
Keyword(s):
SED-ML, SBML, MIASE, Simulation, Modeling, Plone, CMS.
Related
Ontology
Subjects/Areas/Topics:
Application Domains
;
Collaboration and e-Services
;
Collaborative Systems
;
Complex Systems Modeling and Simulation
;
e-Business
;
Enterprise Information Systems
;
Formal Methods
;
Life Science Modeling and Simulation
;
Mathematical Simulation
;
Simulation and Modeling
Abstract:
Systems Biology requires increasingly complex simulation models. Effectively interpreting and building upon previous simulation results is both difficult and time consuming. Thus, simulation results often cannot be reproduced exactly; making it difficult for other modellers to validate results and take the next step in a simulation study.
The Simulation Experiment Description Mark-up Language SED-ML, a subset of the Minimum Information About a Simulation Experiment(MIASE) guidelines, promises to solve this problem by prescribing the form and content of the information required to reproduce simulation experiments. SED-ML enable automatic rerunning of simulation experiments.
Here, we present a web-based simulation-experiment repository that lets modellers develop SED-ML compliant simulation-experiment descriptions The system encourages modellers to annotate their experiments with text and images, experimental data and domain meta-information. These informal annotations aid organisati
on and classification of the simulations and provide rich search criteria. They complement SED-ML's formal precision to produce simulation-experiment descriptions that can be understood by both men and machines. The system combines both human-readable and formal machine-readable content, thus ensuring exact reproducibility of the simulation results of a modelling study.
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