S. Moreno-Paz

Machine learning-guided optimization of p-coumaric acid production in yeast

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

CFSA: Comparative Flux Sampling Analysis as a guide for strain design

CFSA identifies metabolic engineering targets by comparing metabolic spaces of microbial strains to improve production of lipids and naringenin.

Enzyme-constrained models predict the dynamics of Saccharomyces cerevisiae growth in continuous, batch and fed-batch bioreactors

This study improves metabolic models for yeast by incorporating enzyme constraints, enhancing their predictive accuracy in bioreactor simulations.