Jingwen Zhou

This study introduces two models, PromoR and PromoS, for promoter recognition and classification in E. coli, achieving accuracies of 0.887 and 0.781 respectively.

DUnet predicts protein-ligand binding sites using a 3D convolutional neural network, outperforming existing methods and showing accuracy in industrial enzyme substrates.

The paper develops a dynamic regulation network in E. coli to balance malonyl-CoA for enhanced (2S)-naringenin synthesis, achieving an 8.4-fold production improvement with balanced growth.

This paper improves strain stability and pathway yield in engineered yeast by coupling metabolic addiction with negative autoregulation.

This study optimizes Y. lipolytica for producing flavonoids and hydroxylated flavonoids by engineering metabolic pathways and enzyme modules.