
Machine Learning and Synthetic Biology used to Optimize a Cellular Factory for Industrially Relevant Products
A collaboration between the Technical University of Denmark, Lawrence Berkeley National Laboratory, and TeselaGen Biotechnology, Inc. has shown that mechanistic and machine learning models can complement each other and can be combined to enable accurate genotype-to-phenotype predictions, and increase the productivity of important bioproducts produced by industrial organisms.