Objectives & Innovations
The deCYPher project will develop a standardised platform to profoundly implement artificial intelligence (AI) and machine learning (ML) techniques to overcome current hurdles in industrial biotechnology and truly unlock the full potential in biotech engineering.
The project will apply this platform to solve a pertinent problem in the microbial production of plant secondary metabolites, namely the bio-based production of terpenoids and flavonoids. Based on the Design-Build-Test-Learn (DBTL) cycle deCYPher brings together AI/ML with synthetic biology generating transparency, reproducibility, and modularity – supporting the European Green Deal and the circular economy.
Main innovations:
- The development of an AI/ML platform for biotechnology applications
- Use, reinforce, and extend existing ELIXIR resources for (meta)data management
- Use of an integrated holistic approach in the development chain of a bioprocess
- Case studies: economical and sustainable production of oxygenated plant metabolites
- Novel insights & deeper understanding of the societal ramifications of using AI/ML and SynBio for industrial biotechnology
