Huanzi Zhong

Genos-m is a foundation model for human-associated microbial genomes that outperforms existing models in gene-fitness prediction and community structure analysis.

The paper constructs a comprehensive gut microbiome reference database from Chinese and non-Chinese populations, revealing population-specific microbial features linked to host physiology.

The paper expands the gene catalog of mouse gut metagenomes by integrating new samples and genomes, increasing gene count and improving taxonomic and functional annotations.

This study characterizes intra-host SARS-CoV-2 genomic variants and their evolutionary dynamics in COVID-19 patients using deep sequencing data.

This study compares SARS-CoV-2 viral populations in COVID-19 patients to show narrow transmission bottlenecks and stochastic dynamics in intra-host and inter-host evolution.

This paper performs M-GWAS on a Chinese cohort to identify genetic contributions to the gut microbiome and its associations with complex diseases.

This paper compares amplicon, hybrid capture, and metatranscriptomic sequencing methods for directly sequencing SARS-CoV-2 genomes from clinical samples, finding differences in bias, sensitivity, and accuracy.

This study identifies age-related sex differences in gut microbiota composition and functionality across two population cohorts, showing women have more diverse and stable microbiota than men, with sex differences diminishing in older adults.

MetaPGN constructs and visualizes pangenome networks from microbial genomes or metagenomes, revealing genetic diversity in E. coli and gut microbiomes.