Zhihua Ou

STID provides a standardized framework for analyzing spatial transcriptomic data in infectious diseases, enabling pathogen background correction, niche identification, and multi-sample comparative analyses.

The paper creates a spatiotemporal transcriptome atlas of human embryos after gastrulation, revealing organ-specific regulons and regulatory networks during development.

This study uses spatial transcriptomics to show that cerebral vasculatures, particularly meninges, drive inflammation and tissue damage in Japanese encephalitis by forming a feedback loop involving immune cells and cell death mechanisms.

This study uses spatiotemporal transcriptomics to analyze immune dynamics in E. multilocularis infected mouse liver, identifying key immune cell roles and shifts in immune strategy during infection.

This study shows SARS-CoV-2 infection in hamsters causes persistent lung inflammation and alveolar-bronchiolization linked to Notch signaling dysregulation and potential cancer risk.

The paper analyzes the genetic diversity of HPV types 16, 18, 52, and 58 in southern China, identifying sublineages and mutations associated with oncogenic potential.

The paper analyzes mutation profiles, glycosylation sites, and codon usage bias in HPV16 genomes to understand lineage differences and adaptation mechanisms.

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.

The paper identifies CTP synthesis as a metabolic bottleneck that constrains SARS-CoV-2 evolution towards attenuation and highlights viperin's role in antiviral defense.

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.