Design–build–test–learn (DBTL) cycles are commonly used in biotechnology and in natural product discovery as they provide a systemic and efficient framework for the metabolic engineering of microbes.
A novel platform that automates multiomics analyses of microbes could enable faster and better DBLT cycles for your research. In this webinar, the development and validation of the high-throughput, automated platform using model microbial organisms is described, as well as the recent work in applying the platform to cell factory and natural products engineering.
- Learn how automation can enable better and faster DBLT cycles in the life sciences
- Evaluate the pros and cons of taking an automated and digital approach to life science workflows
- Discover the next frontiers of technology that will have an impact in biotechnology