Specifications of standards in systems and synthetic biology: status and developments in 2021

AbstractThe creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment.

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

Journal of Integrative Bioinformatics ◽

10.1515/jib-2015-262 ◽

2015 ◽

Vol 12 (2) ◽

pp. 119-212 ◽

Cited By ~ 9

Author(s):

Frank T. Bergmann ◽

Jonathan Cooper ◽

Nicolas Le Novère ◽

David Nickerson ◽

Dagmar Waltemath

Keyword(s):

Computational Models ◽

Simulation Experiment ◽

Extensible Markup Language ◽

Markup Language ◽

Minimum Information ◽

Extensible Markup ◽

Experiment Description ◽

Simulation Results ◽

Level 1 ◽

Readable Format

Summary The number, size and complexity of computational models of biological systems are growing at an ever increasing pace. It is imperative to build on existing studies by reusing and adapting existing models and parts thereof. The description of the structure of models is not sufficient to enable the reproduction of simulation results. One also needs to describe the procedures the models are subjected to, as recommended by the Minimum Information About a Simulation Experiment (MIASE) guidelines.This document presents Level 1 Version 2 of the Simulation Experiment Description Markup Language (SED-ML), a computer-readable format for encoding simulation and analysis experiments to apply to computational models. SED-ML files are encoded in the Extensible Markup Language (XML) and can be used in conjunction with any XML-based model encoding format, such as CellML or SBML. A SED-ML file includes details of which models to use, how to modify them prior to executing a simulation, which simulation and analysis procedures to apply, which results to extract and how to present them. Level 1 Version 2 extends the format by allowing the encoding of repeated and chained procedures.

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

Nature Precedings ◽

10.1038/npre.2011.5846.1 ◽

2011 ◽

Cited By ~ 2

Author(s):

Dagmar Waltemath ◽

Frank Bergmann ◽

Richard Adams ◽

Nicolas Le Novere

Keyword(s):

Simulation Experiment ◽

Markup Language ◽

Experiment Description ◽

Level 1

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SED-ML Web Tools: Generate, modify and export standard-compliant simulation studies

10.7287/peerj.preprints.2515v1 ◽

2016 ◽

Author(s):

Frank T Bergmann ◽

David Nickerson ◽

Dagmar Waltemath ◽

Martin Scharm

Keyword(s):

Simulation Experiment ◽

Software Tools ◽

Markup Language ◽

Simulation Studies ◽

Online Application ◽

Web Tools ◽

Experiment Description ◽

Level 1

The Simulation Experiment Description Markup Language (SED-ML) is a standardized format for exchanging simulation studies independently of software tools. We present the SED-ML Web Tools, a software that supports SED-ML Level 1 Version 2, including complex modifications and co-simulation of SBML and CellML models. This online application allows for creating, editing, simulating and validating SED-ML documents. It lowers the bar on working with SED-ML documents and helps users create valid simulation descriptions for models in CellML and SBML formats. Availability and Implementation: sysbioapps.dyndns.org/SED-ML_Web_Tools.

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SED-ML Web Tools: Generate, modify and export standard-compliant simulation studies

10.7287/peerj.preprints.2515 ◽

2016 ◽

Author(s):

Frank T Bergmann ◽

David Nickerson ◽

Dagmar Waltemath ◽

Martin Scharm

Keyword(s):

Simulation Experiment ◽

Software Tools ◽

Markup Language ◽

Simulation Studies ◽

Online Application ◽

Web Tools ◽

Experiment Description ◽

Level 1

The Simulation Experiment Description Markup Language (SED-ML) is a standardized format for exchanging simulation studies independently of software tools. We present the SED-ML Web Tools, a software that supports SED-ML Level 1 Version 2, including complex modifications and co-simulation of SBML and CellML models. This online application allows for creating, editing, simulating and validating SED-ML documents. It lowers the bar on working with SED-ML documents and helps users create valid simulation descriptions for models in CellML and SBML formats. Availability and Implementation: sysbioapps.dyndns.org/SED-ML_Web_Tools.

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A standard-enabled workflow for synthetic biology

Biochemical Society Transactions ◽

10.1042/bst20160347 ◽

2017 ◽

Vol 45 (3) ◽

pp. 793-803 ◽

Cited By ~ 24

Author(s):

Chris J. Myers ◽

Jacob Beal ◽

Thomas E. Gorochowski ◽

Hiroyuki Kuwahara ◽

Curtis Madsen ◽

...

Keyword(s):

Systems Biology ◽

Synthetic Biology ◽

Markup Language ◽

Design Tools ◽

Data Standards ◽

Data Repositories ◽

Simulation Tools ◽

Systems Biology Markup Language ◽

Visualization Tools ◽

Synthetic Biology Open Language

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications.

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Simulation Experiment Description Markup Language (SED-ML)

Encyclopedia of Computational Neuroscience ◽

10.1007/978-1-4614-6675-8_377 ◽

2015 ◽

pp. 2708-2710

Author(s):

Dagmar Waltemath ◽

Nicolas Le Novère

Keyword(s):

Simulation Experiment ◽

Markup Language ◽

Experiment Description

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Simulation Experiment Description Markup Language (SED-ML)

Encyclopedia of Computational Neuroscience ◽

10.1007/978-1-4614-7320-6_377-6 ◽

2013 ◽

pp. 1-4 ◽

Cited By ~ 4

Author(s):

Dagmar Waltemath ◽

Nicolas Le Novère

Keyword(s):

Simulation Experiment ◽

Markup Language ◽

Experiment Description

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Synthetic Biology Open Language (SBOL) Version 2.1.0

Journal of Integrative Bioinformatics ◽

10.1515/jib-2016-291 ◽

2016 ◽

Vol 13 (3) ◽

Cited By ~ 9

Author(s):

Jacob Beal ◽

Robert Sidney Cox ◽

Raik Grünberg ◽

James McLaughlin ◽

Tramy Nguyen ◽

...

Keyword(s):

Metabolic Engineering ◽

Synthetic Biology ◽

Molecular Biology ◽

Best Practices ◽

Basic Sequence ◽

Special Issue ◽

Biological Design ◽

Version 2.0 ◽

Topology Information ◽

Synthetic Biology Open Language

SummarySynthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.1 of SBOL that builds upon version 2.0 published in last year’s JIB special issue. In particular, SBOL 2.1 includes improved rules for what constitutes a valid SBOL document, new role fields to simplify the expression of sequence features and how components are used in context, and new best practices descriptions to improve the exchange of basic sequence topology information and the description of genetic design provenance, as well as miscellaneous other minor improvements.

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