Thu Elizabeth Duong

The paper creates a high-resolution multimodal lung atlas using single-nucleus RNA and chromatin data from 11 healthy adults, identifying 70 cell populations and 332,846 chromatin regions.

NS-Forest v4.0 identifies optimal marker genes for cell type classification in scRNA-seq data, improving accuracy and selectivity for closely related cell types.

The paper uses single-cell multi-omics to analyze HARs and HGEs in fetal human brain development, identifying regulatory networks and key transcription factors involved in human-specific neurodevelopment.

Across 1,176,683 airway and lung cells from 22 datasets, ACE2 rises with age, in males and in smokers' multiciliated cells, and is lowest in young children.

The paper develops two single-cell methods to analyze human brain cells, identifies neuronal subtypes and non-neuronal cell types, and links genetic risk factors to specific cell types.