SBOL-OWL: An Ontological Approach for Formal and Semantic Representation of Synthetic Biology Information
- Submitting institution
-
University of Newcastle upon Tyne
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 258182-68649-1292
- Type
- D - Journal article
- DOI
-
10.1021/acssynbio.8b00532
- Title of journal
- ACS Synthetic Biology
- Article number
- -
- First page
- 1498
- Volume
- 8
- Issue
- 7
- ISSN
- 2161-5063
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2019
- URL
-
https://doi.org/10.1021/acssynbio.8b00532
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
7
- Research group(s)
-
B - Interdisciplinary Computing and Complex Biosystems (ICOS)
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- SBOL is the most widely recognised computational standard in the field of synthetic biology. It has been adopted by multiple industrial and academic institutes. This paper presents, for the first time, a formal ontological representation of the standard in work conceived and carried out at Newcastle in collaboration with Keele University and the University of Washington. The research presented here paves to way to computational approaches to reasoning about synthetic biology designs and the automation of their implementation.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
