A computational workflow for the automated generation of models of genetic designs

Misirli

Abstract

Computational models are essential to engineer predictable biological systems and to scale up this process for complex systems. Computational modelling often requires expert knowledge and data to build models. Clearly, manual creation of models is not scalable for large designs. Despite several automated model construction approaches, computational methodologies to bridge knowledge in design repositories and the process of creating computational models has still not been established. This paper describes a workflow for automatic generation of computational models of genetic circuits from data stored in design repositories using existing standards. This workflow leverages the software tool SBOLDesigner to build structural models that are then enriched by the Virtual Parts Repository API using Systems Biology Open Language (SBOL) data fetched from the SynBioHub design repository. The iBioSim software tool is then utilized to convert this SBOL description into a computational model encoding using the Systems Biology Markup Language (SBML). Finally, this SBML model can be simulated using a variety of methods. This workflow provides synthetic biologists with easy to use tools to create predictable biological systems, hiding away the complexity of building computational models. This approach can further be incorporated into other computational workflows for design automation.

• Acceptance Date: May 21, 2018
• Publication Date: May 21, 2018
• Journal: ACS Synthetic Biology
• Publisher: American Chemical Society
• Pages: 1548-1559
• DOI: https://doi.org/10.1021/acssynbio.7b00459
• Keywords: data standards, genetic design automation, modeling, SBML, SBOL, VPR API,
• Publisher URL: http://dx.doi.org/10.1021/acssynbio.7b00459