Andrew C. Warden

The paper combines experimental screening with sequence-based deep learning to efficiently discover high-performing enzyme variants.

EMMAi automates enzyme constraint integration into GEMs using AI-predicted kcat values, improving biomass prediction accuracy across carbon sources without manual curation.

MMINT provides an interactive tool for exploring and comparing metabolic networks derived from genome-scale models to identify metabolic drivers of phenotypes.

The paper describes engineered enzymes that retain and regenerate cofactors, enabling continuous-flow biocatalysis.

This paper designs a NifDK polyprotein resistant to mitochondrial degradation, enabling functional nitrogenase expression in plants and yeast.