scholarly journals The Synthetic Biology Open Language (SBOL) Version 3: Simplified Data Exchange for Bioengineering

2020 ◽  
Vol 8 ◽  
Author(s):  
James Alastair McLaughlin ◽  
Jacob Beal ◽  
Göksel Mısırlı ◽  
Raik Grünberg ◽  
Bryan A. Bartley ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Data Exchange ◽  
Synthetic Biology Open Language

scholarly journals A standard-enabled workflow for synthetic biology

2017 ◽  
Vol 45 (3) ◽  
pp. 793-803 ◽  
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.

A Validator and Converter for the Synthetic Biology Open Language

2017 ◽  
Vol 6 (7) ◽  
pp. 1161-1168 ◽  
Author(s):  
Zach Zundel ◽  
Meher Samineni ◽  
Zhen Zhang ◽  
Chris J. Myers
Keyword(s):  
Synthetic Biology ◽  
Synthetic Biology Open Language

scholarly journals SBOL Visual 2 Ontology

2020 ◽  
Author(s):  
Göksel Misirli ◽  
Jacob Beal ◽  
Thomas E. Gorochowski ◽  
Guy-Bart Stan ◽  
Anil Wipat ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Web Service ◽  
Visual Representation ◽  
Biological Ontologies ◽  
Visualization Tools ◽  
Synthetic Biology Open Language

AbstractStandardising the visual representation of genetic parts and circuits is vital for unambiguously creating and interpreting genetic designs. To this end, an increasing number of tools are adopting well-defined glyphs from the Synthetic Biology Open Language (SBOL) Visual standard to represent various genetic parts and their relationships. However, the implementation and maintenance of the relationships between biological elements or concepts and their associated glyphs has to now been left up to tool developers. We address this need with the SBOL Visual 2 Ontology, a machine-accessible resource that provides rules for mapping from genetic parts, molecules, and interactions between them, to agreed SBOL Visual glyphs. This resource, together with a web service, can be used as a library to simplify the development of visualization tools, as a stand-alone resource to computationally search for suitable glyphs, and to help facilitate integration with existing biological ontologies and standards in synthetic biology.Graphical TOC Entry

scholarly journals Synthetic Biology Open Language Visual (SBOL Visual) Version 2.1

2019 ◽  
Vol 16 (2) ◽  
Author(s):  
Curtis Madsen ◽  
Angel Goni Moreno ◽  
Zachary Palchick ◽  
Umesh P ◽  
Nicholas Roehner ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Synthetic Biology ◽  
Molecular Species ◽  
Chemical Process ◽  
Structure And Function ◽  
Genomic Context ◽  
Functional Relationships ◽  
Synthetic Biology Open Language ◽  
And Function ◽  
Biological Organisms

AbstractPeople 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 2.1 of SBOL Visual, which builds on the prior SBOL Visual 2.0 standard by expanding diagram syntax to include methods for showing modular structure and mappings between elements of a system, interactions arrows that can split or join (with the glyph at the split or join indicating either superposition or a chemical process), and adding new glyphs for indicating genomic context (e.g., integration into a plasmid or genome) and for stop codons.

Specifying Combinatorial Designs with the Synthetic Biology Open Language (SBOL)

2019 ◽  
Vol 8 (7) ◽  
pp. 1519-1523
Author(s):  
Nicholas Roehner ◽  
Bryan Bartley ◽  
Jacob Beal ◽  
James McLaughlin ◽  
Matthew Pocock ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Combinatorial Designs ◽  
Synthetic Biology Open Language

scholarly journals SEVA 3.0: an update of the Standard European Vector Architecture for enabling portability of genetic constructs among diverse bacterial hosts

2019 ◽  
Vol 48 (D1) ◽  
pp. D1164-D1170 ◽  
Author(s):  
Esteban Martínez-García ◽  
Angel Goñi-Moreno ◽  
Bryan Bartley ◽  
James McLaughlin ◽  
Lucas Sánchez-Sampedro ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Bacterial Species ◽  
Web Based ◽  
Genomic Engineering ◽  
Bioinformatic Tools ◽  
Synthetic Biology Open Language ◽  
User Friendly ◽  
Machine Readable ◽  
Genetic Constructs

Abstract The Standard European Vector Architecture 3.0 database (SEVA-DB 3.0, http://seva.cnb.csic.es) is the update of the platform launched in 2013 both as a web-based resource and as a material repository of formatted genetic tools (mostly plasmids) for analysis, construction and deployment of complex bacterial phenotypes. The period between the first version of SEVA-DB and the present time has witnessed several technical, computational and conceptual advances in genetic/genomic engineering of prokaryotes that have enabled upgrading of the utilities of the updated database. Novelties include not only a more user-friendly web interface and many more plasmid vectors, but also new links of the plasmids to advanced bioinformatic tools. These provide an intuitive visualization of the constructs at stake and a range of virtual manipulations of DNA segments that were not possible before. Finally, the list of canonical SEVA plasmids is available in machine-readable SBOL (Synthetic Biology Open Language) format. This ensures interoperability with other platforms and affords simulations of their behaviour under different in vivo conditions. We argue that the SEVA-DB will remain a useful resource for extending Synthetic Biology approaches towards non-standard bacterial species as well as genetically programming new prokaryotic chassis for a suite of fundamental and biotechnological endeavours.

scholarly journals Synthetic Biology Open Language (SBOL) Version 2.1.0

2016 ◽  
Vol 13 (3) ◽  
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.

scholarly journals Synthetic biology open language visual (SBOL visual) version 3.0

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Hasan Baig ◽  
Pedro Fontanarossa ◽  
James McLaughlin ◽  
James Scott-Brown ◽  
Prashant Vaidyanathan ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Synthetic Biology ◽  
Molecular Species ◽  
Data Model ◽  
Structure And Function ◽  
Sequence Features ◽  
Functional Relationships ◽  
Synthetic Biology Open Language ◽  
And Function ◽  
Biological Organisms

Abstract People who engineer biological organisms often find it useful to draw diagrams in order to communicate both the structure of the nucleic acid sequences that they are engineering and the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. SBOL Visual aims to organize and systematize such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 3.0 of SBOL Visual, a new major revision of the standard. The major difference between SBOL Visual 3 and SBOL Visual 2 is that diagrams and glyphs are defined with respect to the SBOL 3 data model rather than the SBOL 2 data model. A byproduct of this change is that the use of dashed undirected lines for subsystem mappings has been removed, pending future determination on how to represent general SBOL 3 constraints; in the interim, this annotation can still be used as an annotation. Finally, deprecated material has been removed from collection of glyphs: the deprecated “insulator” glyph and “macromolecule” alternative glyphs have been removed, as have the deprecated BioPAX alternatives to SBO terms.

The Synthetic Biology Open Language

2014 ◽  
pp. 323-336 ◽  
Author(s):  
Chris Myers ◽  
Kevin Clancy ◽  
Goksel Misirli ◽  
Ernst Oberortner ◽  
Matthew Pocock ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Synthetic Biology Open Language

scholarly journals Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0

2018 ◽  
Vol 15 (1) ◽  
Author(s):  
Robert Sidney Cox ◽  
Curtis Madsen ◽  
James McLaughlin ◽  
Tramy Nguyen ◽  
Nicholas Roehner ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Best Practices ◽  
Molecular Species ◽  
Data Model ◽  
Functional Relationships ◽  
Version 2.0 ◽  
Synthetic Biology Open Language ◽  
And Function ◽  
The Relationship ◽  
Biological Organisms

AbstractPeople 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.

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