metabolic engineering

CRI-SPA: a high-throughput method for systematic genetic editing of yeast libraries

A highly efficient, reproducible and scalable genome editing method

Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae

Using computational simulations to find the best way to produce the heme cofactor

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

Over-producing tryptophan using a combination of machine learning and flux balance analysis

Model-Assisted Fine-Tuning of Central Carbon Metabolism in Yeast through dCas9-Based Regulation

Over-producing acetyl/malonyl-CoA using _in silico_ & experimental methods