Synthetic Biology Open Language (SBOL) Version 2.2.0

Robert Sidney Cox III 1 , Curtis Madsen 2 , James Alastair McLaughlin 3 , Tramy Nguyen 4 , Nicholas Roehner 5 , Bryan Bartley 6 , Jacob Beal 5 , Michael Bissell 7 , Kiri Choi 6 , Kevin Clancy 8 , Raik Grünberg 9 , Chris Macklin 7 , Goksel Misirli 10 , Ernst Oberortner 11 , Matthew Pocock 12 , Meher Samineni 4 , Michael Zhang 4 , Zhen Zhang 13 , Zach Zundel 4 , John H. Gennari 6 , Chris Myers 14 , Herbert Sauro 6  and Anil Wipat 3
  • 1 Prospect Bio, Brisbane, CA, USA
  • 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 ThermoFisher Scientific, San Diego, CA, USA
  • 9 King Abdullah University for Science and Technology, Thuwal, Saudi Arabia
  • 10 Keele University, Keele, Staffordshire, United Kingdom of Great Britain and Northern Ireland
  • 11 DOE Joint Genome Institute, Walnut Creek, CA, USA
  • 12 Turing Ate My Hamster LTD, Newcastle, UK
  • 13 Utah State University, Logan, UT, USA
  • 14 University of Utah, Salt Lake City, UT, USA

Abstract

Synthetic 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 2.2.0 of SBOL that builds upon version 2.1.0 published in last year’s JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.

If the inline PDF is not rendering correctly, you can download the PDF file here.

OPEN ACCESS

Journal + Issues

The Journal of Integrative Bioinformatics is an international journal dedicated to methods and tools of computer science and electronic infrastructure applied to biotechnology. The journal covers mainly but not exclusively data/method integration, modeling, simulation and visualization in combination with applications of theoretical/computational tools and any other approach supporting an integrative view of complex biological systems.

Search