Abstract

Computational simulation experiments increasingly inform modern biological research, and bring with them the need to provide ways to annotate, archive, share and reproduce the experiments performed. These simulations increasingly require extensive collaboration among modelers, experimentalists, and engineers. The Minimum Information About a Simulation Experiment (MIASE) guidelines outline the information needed to share simulation experiments. SED-ML is a computer-readable format for the information outlined by MIASE, created as a community project and supported by many investigators and software tools. The first versions of SED-ML focused on deterministic and stochastic simulations of models. Level 1 Version 4 of SED-ML substantially expands these capabilities to cover additional types of models, model languages, parameter estimations, simulations and analyses of models, and analyses and visualizations of simulation results. To facilitate consistent practices across the community, Level 1 Version 4 also more clearly describes the use of SED-ML constructs, and includes numerous concrete validation rules. SED-ML is supported by a growing ecosystem of investigators, model languages, and software tools, including eight languages for constraint-based, kinetic, qualitative, rule-based, and spatial models, over 20 simulation tools, visual editors, model repositories, and validators. Additional information about SED-ML is available at https://sed-ml.org/.

Highlights

  • The efforts to standardize the representation of computational models in various areas of biology, such as the Systems Biology Markup Language (SBML) [16], CellML [9] or NeuroML [13], resulted in an increase of the exchange and re-use of models

  • Simulation Experiment Description Markup Language (SED-ML) can capture the information in the Minimum Information About a Simulation Experiment (MIASE) [22] guidelines

  • models to use (Model) languages can choose to use XPath to identify abstract concepts implied by models that are not defined in XML files, such as ‘the current value of the object corresponding to an XML element within the state of a simulation run’

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Summary

Introduction

The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format for describing simulation experiments, including model changes, calibrations, simulations, analyses, and computations and visualizations of simulation results. The efforts to standardize the representation of computational models in various areas of biology, such as the Systems Biology Markup Language (SBML) [16], CellML [9] or NeuroML [13], resulted in an increase of the exchange and re-use of models. The increasing use of computational simulation experiments to inform modern biological research creates new challenges to reproduce, annotate, archive, and share such experiments. ˆ We use a red color in text and a dark blue color in figures to indicate changes between this version of the specification, namely SED-ML Level 1 Version 4, and the most recent previous release of the specification (which, for the present case, is SED-ML Level 1 Version 3). When viewed in electronic form, clicking on blue-colored text will cause a jump to the section, figure, table or page to which the link refers

SED-ML overview
Example simulation experiment
Time-course simulation
Applying pre-processing
Applying post-processing
SED-ML technical specification
Primitive data types
Type ID
Type SId
Type SIdRef
Type TargetType
Type XPath
Type URN
Type NuMLSId
2.1.1.10 Type NuMLSIdRef
2.1.1.11 Type CurveType
2.1.1.12 Type SurfaceType
2.1.1.13 Type LineType
2.1.1.14 Type SedColor
2.1.1.15 Type MarkerType
2.1.1.16 Type MappingType
2.1.1.17 Type ExperimentType
2.1.1.18 Type AxisType
2.1.1.19 Type ScaleType
SEDBase
Annotation
Parameter
Variable
A Variable may be used in one of the following ways:
AppliedDimension
Calculation
General attributes and elements
2.1.10 Reference relations
SED-ML top level element
DataDescription
DimensionDescription
DataSource
Change
NewXML
AddXML
ChangeXML
RemoveXML
ChangeAttribute
ComputeChange
Simulation
UniformTimeCourse
OneStep
SteadyState
Analysis
Algorithm
AlgorithmParameter
AbstractTask
Repeated Task
SubTask
SetValue
VectorRange
FunctionalRange
DataRange
2.2.10 ParameterEstimationTask
Objective
2.2.10.4 Bounds
2.2.10.5 ExperimentReference
2.2.10.7 FitMapping
2.2.11 DataGenerator
2.2.12 Output
2.2.12.2 Plot2D
2.2.12.3 Plot3D
2.2.13 Report
2.2.13.1 DataSet
2.2.14 ParameterEstimationReport
2.2.15 Figure
2.2.15.1 SubPlot
2.2.16 ParameterEstimationResultPlot
2.2.17 WaterfallPlot
2.2.18.2 Marker
MathML
MathML elements
MathML symbols
MathML csymbols for dimensional input
MathML Distribution Functions
Model references
Data references
Symbols
Annotation Scheme
Language references
Data format references
COMBINE archive
Examples
Simulation experiments with dataDescriptions
Simulation experiments with repeatedTasks
Simulation experiments with different model languages
Reproducing publication results
Validation and consistency rules
Full Text
Published version (Free)

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