Dongmei Li

This paper introduces DeepSAS, a deep graph framework to identify senescent cells and their associated genes, revealing cell-type-specific senescence features in aging and disease.

The paper develops SenSet, a gene signature for human lung senescence, validated in 3D culture models and identifies cell-type specific senescence mechanisms in aging and disease.

B-Lightning identifies marker genes and cell subpopulations for specific sources of heterogeneity while filtering out confounding factors, improving sensitivity and robustness in single-cell data analysis.

The paper evaluates RNA-seq differential analysis methods across simulated and real data, finding EBSeq and DESeq2 perform best under specific conditions.