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Synthetic Biology Open Language Version 2.0
The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. Here we describe the Synthetic Biology Open Language (SBOL), a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-driven, formalized format for exchange between software tools, research groups and commercial service providers. The SBOL Developers Group has implemented SBOL as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. We describe early successes, including a demonstration of the utility of SBOL for information exchange between several different software tools and repositories from both academic and industrial partners. As a community-driven standard, SBOL will be updated as synthetic biology evolves to provide specific capabilities for different aspects of the synthetic biology workflow.*
*(Michal Galdzicki et al. Nature Biotechnology 32, 545-550 (2014))
|Spatial Representation Level||Compartment||Dimensions||Gradients||Spatial Structures|
MathML Support: no
Full MathML Support: no
Link to mathematical models written in other standards
Miriram Support: no
identifiers.org Support: yes
Synthetic Biology Open Language (SBOL)
SBOL is a language to describe synthetic biology constructs.
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Creative Commons Attribution 4.0 International Public License - The BioBricks Foundation
Copyright (C) The BioBricks Foundation and all authors listed on this BBF RFC. This work is made available 2 under the Creative Commons Attribution 4.0 International Public License. To view a copy of this license visit 3 https://creativecommons.org/licenses/by/4.0/. 4 In addition to the listed authors, the following people are specifically recognized as additional contributors sharing 5 in the copyright (alphabetically by institution): Douglas Densmore (Boston University, USA), Jacqueline Quinn 6 (Google, USA), and Guy-Bart Stan (Imperial College London, UK).