Journal article
SBOL converter: enabling backward compatibility for biological designs
Journal of integrative bioinformatics
08/18/2026
DOI: 10.1515/jib-2026-0005
PMID: 42608859
Abstract
The Synthetic Biology Open Language (SBOL) is a community-driven and machine-readable standard for creating and sharing biological designs. SBOL has evolved over the years, resulting in three major versions, each introducing new features. Although SBOL3 is the latest community-adopted version, it has not been fully integrated into software tools and repositories due to the lack of essential libraries to facilitate this transition. In this paper, we present the SBOL Converter, a backward-compatibility tool that can update legacy designs to the latest SBOL version. Designs can also be converted to previous versions to allow legacy tools to be used in ongoing projects. Moreover, it incorporates existing SBOL tools, providing a unified interface to orchestrate the validation of designs and checking against various compliance rules and best practices. The converter can also process other popular biological formats such as GenBank and FASTA. As a lightweight tool, it can be integrated into engineering biology design workflows to accelerate tool development and enable the transition to the latest versions as they are released, facilitating the reusability and reproducibility of biological designs.
Details
- Title: Subtitle
- SBOL converter: enabling backward compatibility for biological designs
- Creators
- Metehan Ünal - Keele UniversityChris J. Myers - University of Colorado BoulderIhsan Tolga Medeni - Ankara Yıldırım Beyazıt UniversityJacob Beal - Raytheon (United States)Prashant Vaidyanathan - Oxford BioMedica (United Kingdom)Lukas Buecherl - Utah State UniversityFelipe Buson - University of BristolGeorgie Hau Sørensen - University of BristolGonzalo Vidal - University of Colorado BoulderCarolus Vitalis - University of Colorado BoulderErik Kubaczka - Technische Universität DarmstadtRoberto Galizi - Keele UniversityGöksel Mısırlı - Keele University
- Resource Type
- Journal article
- Publication Details
- Journal of integrative bioinformatics
- DOI
- 10.1515/jib-2026-0005
- PMID
- 42608859
- NLM abbreviation
- J Integr Bioinform
- ISSN
- 1613-4516
- eISSN
- 1613-4516
- Publisher
- WALTER DE GRUYTER GMBH
- Grant note
- Biotechnology and Biological Sciences Research Council (BBSRC): BB/Z517367/1 Excellence programme of the state of Hesse-LOEWE top professorships: LOEWE/4a/519/05/00.003 (0007)/121 ERC-PoC grant PLATE: 101082333 Army Research Office: W911NF-22-2-0210 DARPA: HR0011-24-C-0423
M.U., R.G., and G.M. were supported by the Biotechnology and Biological Sciences Research Council (BBSRC) under grant number BB/Z517367/1. E.K. acknowledges funding by the excellence programme of the state of Hesse-LOEWE top professorships (LOEWE/4a/519/05/00.003 (0007)/121) and ERC-PoC grant PLATE (101082333). C.J.M., G.V., and C.V. were supported by the Army Research Office and was accomplished under Cooperative Agreement Number W911NF-22-2-0210 and DARPA grant number HR0011-24-C-0423. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorised to reproduce and distribute reprints for Government purposes, notwithstanding any copyright notation herein.
- Language
- English
- Electronic publication date
- 08/18/2026
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9985219307902771
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