Xiaojun Li

This study investigates the molecular effects of RVd therapy on T cells using TEA-seq, revealing how individual and sequential drug administration impacts T cell function and states.

scVIP models single-cell transcriptomes to predict phenotypes and infer trajectories in development and disease.

The paper identifies diverse human antibody-secreting cell subsets using multi-omic methods and shows their distinct functional and spatial characteristics.

This study shows how multiple myeloma and its treatment alter the bone marrow niche, impairing immune reconstitution and vaccine responses, with mRNA vaccines showing better efficacy than influenza vaccines.

The paper creates a cell-type-specific IFN response atlas to distinguish IFN-I and IFN-II activities in human immune cells across diseases.

This study uses multi-omic profiling to analyze immune cell dynamics in healthy adults over time, finding age-related transcriptional changes in T cells and impaired memory B cell responses in older adults.

The paper identifies immune alterations preceding rheumatoid arthritis onset and provides tools for dataset exploration.

SPARROW integrates spatial transcriptomics and scRNA-seq to identify microenvironment zones and their influence on cell states and functions across tissues.

MOCHA improves scATAC-seq analysis by addressing technical and biological challenges, enabling better gene regulatory insights in human disease.