Alex Toftgaard Nielsen

The paper develops an automated online pressure sensor for microbial batch cultivation to improve data quality and experimental efficiency.

This study maps microbial metabolic phases using online pressure and backscatter measurements in closed batch vials, identifying distinct catabolic and anabolic phases in yeast and syngas fermentation.

This paper introduces a method to measure microbial catabolism in real-time using pressure measurements, distinguishing metabolic shifts not detectable by biomass alone.

MillionFull collects large-scale sequence-fitness data for enzymes at low cost, enabling machine learning for enzyme engineering.

The paper introduces a modular expression platform for screening heterologous protein expression across diverse prokaryotic hosts, enabling data-driven host selection.

The paper reconstructs and validates a genome-scale metabolic model for Lactobacillus reuteri JCM 1112T, demonstrating its accuracy in predicting metabolic behavior and identifying strategies for metabolic engineering.