Jianhui Liu

This study uses single-cell RNA sequencing to analyze human retinal samples and identifies microglial states and neural-immune interactions in diabetic retinopathy.

The paper identifies cell-type-specific aging signatures in human retinal cells using single-cell RNA sequencing and machine learning, revealing molecular changes and vulnerabilities associated with aging.

The paper constructs a single-cell transcriptomic atlas of the human retina from Chinese donors, identifying 10 cell types and subtypes, and mapping their molecular programs and biological functions.

The paper generates a scRNA-seq reference atlas of living and early post-mortem human retina, revealing distinct transcriptional dynamics and a novel mlCone cluster.

The paper identifies cell-type-specific biomarkers for diabetic retinopathy using single-cell transcriptomics and machine learning, achieving high classification accuracy across disease states.