Journal article
Proposed Data Model for the Next Version of the Synthetic Biology Open Language
ACS synthetic biology, Vol.4(1), pp.57-71
01/16/2015
DOI: 10.1021/sb500176h
PMID: 24896221
Abstract
While the first version of the Synthetic Biology Open Language (SBOL) has been adopted by several academic and commercial genetic design automation (GDA) software tools, it only covers a limited number of the requirements for a standardized exchange format for synthetic biology. In particular, SBOL Version 1.1 is capable of representing DNA components and their hierarchical composition via sequence annotations. This proposal revises SBOL Version 1.1, enabling the representation of a wider range of components with and without sequences, including RNA components, protein components, small molecules, and molecular complexes. It also introduces modules to instantiate groups of components on the basis of their shared function and assert molecular interactions between components. By increasing the range of structural and functional descriptions in SBOL and allowing for their composition, the proposed improvements enable SBOL to represent and facilitate the exchange of a broader class of genetic designs.
Details
- Title: Subtitle
- Proposed Data Model for the Next Version of the Synthetic Biology Open Language
- Creators
- Nicholas Roehner - University of UtahErnst Oberortner - Boston UniversityMatthew Pocock - Newcastle UniversityJacob Beal - RTXKevin Clancy - Life Technol, Carlsbad, CA USACurtis Madsen - University of Newcastle AustraliaGoksel Misirli - Newcastle UniversityAnil Wipat - Newcastle UniversityHerbert Sauro - University of WashingtonChris J. Myers - University of Utah
- Resource Type
- Journal article
- Publication Details
- ACS synthetic biology, Vol.4(1), pp.57-71
- Publisher
- Amer Chemical Soc
- DOI
- 10.1021/sb500176h
- PMID
- 24896221
- ISSN
- 2161-5063
- eISSN
- 2161-5063
- Number of pages
- 15
- Grant note
- CCF-1218095 / National Science Foundation; National Science Foundation (NSF)
- Language
- English
- Date published
- 01/16/2015
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984627287802771
Metrics
4 Record Views