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J Integr Bioinform. 2018 Mar 19;15(1). pii: /j/jib.2018.15.issue-1/jib-2017-0074/jib-2017-0074.xml. doi: 10.1515/jib-2017-0074.

Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0.

Author information

1
Kobe University, Kobe, Japan.
2
Boston University, Boston, MA, USA.
3
Newcastle University, Newcastle, United Kingdom of Great Britain and Northern Ireland.
4
University of Utah, Salt Lake City, UT, USA.
5
Raytheon BBN Technologies, Cambridge, MA, USA.
6
University of Washington, Seattle, WA, USA.
7
Amyris, Inc., Emeryville, CA, USA.
8
Thermo Fisher Scientific, San Diego, CA, USA.
9
University of Bristol, Bristol, United Kingdom of Great Britain and Northern Ireland.
10
King Abdullah University of Science and Technology (KAUST), BESE, Thuwal 23955 - 6900, Saudi Arabia.
11
Harvard Medical School, Boston, MA, USA.
12
Babraham Institute, Cambridge, Cambridgeshire, United Kingdom of Great Britain and Northern Ireland.
13
Turing Ate My Hamster, Ltd., Newcastle, United Kingdom of Great Britain and Northern Ireland.
14
Rice University, Houston, TX, USA.
15
Imperial College, London, United Kingdom of Great Britain and Northern Ireland.
16
Massachusetts Institute of Technology, Cambridge, MA, USA.

Abstract

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.0 of SBOL Visual, which builds on the prior SBOL Visual 1.0 standard by expanding diagram syntax to include functional interactions and molecular species, making the relationship between diagrams and the SBOL data model explicit, supporting families of symbol variants, clarifying a number of requirements and best practices, and significantly expanding the collection of diagram glyphs.

KEYWORDS:

Diagrams; SBOL Visual; Standards

PMID:
29549707
DOI:
10.1515/jib-2017-0074
[Indexed for MEDLINE]
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