Jinyuan Guo

Tripleknock predicts lethal effects of three-gene knockouts in bacteria using deep learning, achieving faster predictions than FBA with high cross-species accuracy.

KuafuPrimer uses machine learning to design 16S rRNA gene primers with minimal bias, improving taxonomic accuracy and detecting rare taxa missed by universal primers.

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.