SBOL-OWL: An ontological approach for formal and semantic representation of synthetic biology information

Misirli

Abstract

Standard representation of data is key for the reproducibility of designs in synthetic biology. The Synthetic Biology Open Language (SBOL) has already emerged as a data standard to represent information about genetic circuits, and it is based on capturing data using graphs. The language provides the syntax using a free text document that is accessible to humans only. This paper describes SBOL-OWL, an ontology for a machine understandable definition of SBOL. This ontology acts as a semantic layer for genetic circuit designs. As a result, computational tools can understand the meaning of design entities in addition to parsing structured SBOL data. SBOL-OWL not only describes how genetic circuits can be constructed computationally, it also facilitates the use of several existing Semantic Web tools for synthetic biology. This paper demonstrates some of these features, for example, to validate designs and check for inconsistencies. Through the use of SBOL-OWL, queries can be simplified and become more intuitive. Moreover, existing reasoners can be used to infer information about genetic circuit designs that cannot be directly retrieved using existing querying mechanisms. This ontological representation of the SBOL standard provides a new perspective to the verification, representation, and querying of information about genetic circuits and is important to incorporate complex design information via the integration of biological ontologies.

Citation

Misirli. (2019). SBOL-OWL: An ontological approach for formal and semantic representation of synthetic biology information. ACS synthetic biology, 1498-1514. https://doi.org/10.1021/acssynbio.8b00532

• Acceptance Date: May 6, 2019
• Publication Date: Jul 1, 2019
• Journal: ACS Synthetic Biology
• Publisher: American Chemical Society
• Pages: 1498-1514
• DOI: https://doi.org/10.1021/acssynbio.8b00532
• Keywords: ontology, Synthetic Biology Open Language, standardization, genetic circuits
• Publisher URL: http://doi.org/10.1021/acssynbio.8b00532