Journal article
Specifying Combinatorial Designs with the Synthetic Biology Open Language (SBOL)
ACS synthetic biology, Vol.8(7), pp.1519-1523
07/19/2019
DOI: 10.1021/acssynbio.9b00092
PMID: 31260271
Abstract
As improvements in DNA synthesis technology and assembly methods make combinatorial assembly of genetic constructs increasingly accessible, methods for representing genetic constructs likewise need to improve to handle the exponential growth of combinatorial design space. To this end, we present a community accepted extension of the SBOL data standard that allows for the efficient and flexible encoding of combinatorial designs. This extension includes data structures for representing genetic designs with variable components that can be implemented by choosing one of many linked designs for existing genetic parts or constructs. We demonstrate the representational power of the SBOL combinatorial design extension through case studies on metabolic pathway design and genetic circuit design, and we report the expansion of the SBOLDesigner software tool to support users in creating and modifying combinatorial designs in SBOL
Details
- Title: Subtitle
- Specifying Combinatorial Designs with the Synthetic Biology Open Language (SBOL)
- Creators
- Nicholas Roehner - RTXBryan Bartley - RTXJacob Beal - RTXJames McLaughlin - Newcastle UniversityMatthew Pocock - Turing InstituteMichael Zhang - University of UtahZach Zundel - University of UtahChris J. Myers - University of Utah
- Resource Type
- Journal article
- Publication Details
- ACS synthetic biology, Vol.8(7), pp.1519-1523
- Publisher
- Amer Chemical Soc
- DOI
- 10.1021/acssynbio.9b00092
- PMID
- 31260271
- ISSN
- 2161-5063
- eISSN
- 2161-5063
- Number of pages
- 9
- Grant note
- CCF-1748200; DBI-1356041; 1522074 / National Science Foundation; National Science Foundation (NSF) HR0011-15-C-0084; FA8750-17-C-0229 / DARPA award; United States Department of Defense 1522074 / Direct For Computer & Info Scie & Enginr; Division of Computing and Communication Foundations; National Science Foundation (NSF); NSF - Directorate for Computer & Information Science & Engineering (CISE)
- Language
- English
- Date published
- 07/19/2019
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984627342802771
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