Mo Li

eBiota designs microbial communities from large strain pools to generate target products using optimization and deep learning, showing accurate predictions and experimental validation.

This paper introduces VirHRanger, a foundation model for predicting viral host range using genomic and protein data, achieving high accuracy across diverse viruses and host categories.

IPEV identifies and classifies prokaryotic and eukaryotic virus-derived sequences in viromes using deep learning, achieving higher precision and efficiency than existing methods.

DeePhage is a deep learning tool that classifies virulent and temperate phage-derived sequences in metavirome data with high accuracy and speed.