Priscilla Zwartjens

This paper applies a machine learning-assisted recommendation strategy with exploration-exploitation balance to optimize p-coumaric acid production in yeast, achieving a 137% increase over parent strains.

The paper uses machine learning to optimize p-coumaric acid production in yeast through DBTL cycles, achieving a 68% increase in production.

The paper evaluates 12,000 signal peptides using a high-throughput assay, trains a machine learning model to predict secretion efficiency, and explains the model's features.