Mo Li

eBiota: Designing microbial communities from large seed pools with desired function using rapid optimization and deep learning

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

Developing Foundation Models for Predicting Viral Animal Host Range in Intelligent Surveillance

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: Identification of Prokaryotic and Eukaryotic Virus-derived sequences in virome using deep learning

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

Distinguish virulent and temperate phage-derived sequences in metavirome data with a deep learning approach

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