Taking synthetic biology to large scales

We work towards laboratory automation

Our objectives

Determine the extended metabolic design space

We will determine the number of production circuits that can be plugged in a microbial host and the number of molecules that can be detected through biosensor circuits. The combination of both will lead us to find out the potential regulated pathways that a microbe can host.

Build machine learning-based response models

We will develop context-aware dynamic models to control the synthetic metabolic pathways, and these models will be regulated with feedback control loops

Develop design tools for automated assembly

We will generate assembly instructions for liquid-handling robots integrated in the design, build, test and learn cycle. In addition, we will develop a computer-aided design platform for dynamically regulated pathways based on optimal experimental design.