Software for Synthetic Biology Workflows: How to Improve Your Productivity and Impact | AIChE

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Software for Synthetic Biology Workflows: How to Improve Your Productivity and Impact

Presenters:

  • Chris J. Myers, University of Colorado Boulder
  • Jacob Beal, BBN/Raytheon
  • Gonzalo Vidal Pena, Pontificia Universidad Católica de Chile
  • Daniel Bryce, SIFT



This workshop will present four synthetic biology workflows: (1) a modeling workflow for genetic design, (2) a production workflow for the design of libraries of genetic constructs, (3) a data management workflow for genetic circuit characterization experiments, and (4) a test and learn workflow for high throughput laboratory science. The four workflows that will be presented are:

  • First, a workflow that leverages the design, modeling, and analysis tools SBOLCanvas and iBioSim coupled with characterization data in SynBioHub to produce computational analyses of genetic designs.  
  • Second, the iGEM Engineering Committee is working to establish widely accessible measurement and calibration protocols and standards and to improve the availability of biological devices with well-understood and predictable behavior. One of the key components in this ongoing work is collective design and production of libraries of genetic constructs for interlaboratory studies, which is the second workflow that will be presented.  
  • The third workflow uses Flapjack, a data management and analysis application for genetic circuit characterization, to store, share, mix, analyze and plot your synthetic biology data. Flapjack has a database backend, a webapp as frontend and a Python API, this allows you to access your data remotely using an intuitive user interface and be able to integrate it easily in Python workflows for automation.  
  • Finally, the fourth workflow is the Synergistic Discovery and Design (SD2) Round Trip architecture that automates many of the key steps in the Test and Learn phases of a Design, Build, Test, and Learn loop for high throughput laboratory science. In this part of the presentation, we highlight the major software components and data representations that enable the Round Trip to speed up the design and analysis of experiments two orders of magnitude over prior ad hoc methods.