Fig 1.
Schematic of a machine learning-driven “design-build-test-learning” (DBTL) cycle in synthetic biology.
The DBTL cycle is a framework in synthetic biology for developing organisms with desired functionalities. Over the years, the bottlenecks associated with the technologies depicted in the figure have gradually been resolved, enabling the advancement of each stage in the cycle. However, developments in the “learn” stage continue to lag. Machine learning can bridge the gap between the “learn” and “design” stages to further accelerate the DBTL cycle. This figure was created using clipart from BioRender.com.