Shiwei Zheng

The paper profiles human myeloid cells across aging and Alzheimer's disease, identifies AD-associated changes, and links GPNMB to neuroprotection via TREM2.

The paper develops a machine learning framework to identify cell type-specific gene targets for IBD using a harmonized single-cell atlas and validates them experimentally.

ONTraC uses a graph neural network to analyze spatial transcriptomics data, improving trajectory reconstruction and revealing microenvironment-dependent changes in gene regulation and cell interactions during development.

The paper uses spatial transcriptomics to identify injury-specific microenvironments and molecular interactions in the mouse kidney during injury and regeneration.

The paper uses integrated spatial genomics to study nuclear architecture in mouse brain cortex cells, revealing chromatin fixed points and cell-type specific organization of nuclear bodies.

Weighted-nearest neighbor (WNN) analysis in Seurat v4 learns per-cell modality weights to define cell states, enabling a 228-antibody human PBMC CITE-seq reference for RNA-only query mapping.

The paper maps chromatin states, DNA loci, and gene expression in single mouse embryonic stem cells using DNA seqFISH+ and immunofluorescence, revealing nuclear zones and subpopulations with distinct chromatin features.

The paper introduces cell hashing using barcoded antibodies to enable multiplexing and doublet detection in single-cell genomics, demonstrating its effectiveness with human PBMC samples.