paraSBOLv: a foundation for standard-compliant genetic design visualization tools

Charlie J Clark, James Scott-Brown, Thomas E Gorochowski*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)
18 Downloads (Pure)

Abstract

Diagrams constructed from standardized glyphs are central to communicating complex design information in many engineering fields. For example, circuit diagrams are commonplace in electronics and allow for a suitable abstraction of the physical system that helps support the design process. With the development of the Synthetic Biology Open Language Visual (SBOLv), bioengineers are now positioned to better describe and share their biological designs visually. However, development of computational tools to support the creation of these diagrams is currently hampered by an excessive burden in maintenance due to the large and expanding number of glyphs present in the standard. Here, we present a Python package called paraSBOLv that enables access to the full suite of SBOLv glyphs through use of machine-readable parametric glyph definitions. These greatly simplify the rendering process while allowing extensive customization of the resulting diagrams. We demonstrate how adoption of paraSBOLv can accelerate the development of highly specialized biodesign visualization tools or even form the basis for more complex software by removing the burden of maintaining glyph specific rendering code. Looking forward, we suggest that incorporation of machine-readable parametric glyph definitions into the SBOLv standard could further simplify the development of tools to produce standard-compliant diagrams and integration of visual standards across fields.
Original languageEnglish
Article numberysab022
Number of pages7
JournalSynthetic Biology
Volume6
Issue number1
DOIs
Publication statusPublished - 30 Aug 2021

Structured keywords

  • BrisSynBio
  • Bristol BioDesign Institute

Keywords

  • SBOL Visual
  • genetic design visualization
  • synthetic biology
  • Python

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