Chen‐Rui Xia

The paper constructs a single-cell atlas of cerebrospinal fluid and blood from CNS diseases, revealing immune features of NPSLE and providing a public resource for future research.

The paper introduces a metric to quantify gene expression predictability from histology images and identifies genes that can or cannot be predicted.

PASSAGE identifies phenotype-associated spatial signatures in spatial transcriptomics data using a deep learning framework.

DECIPHER generates high-fidelity disentangled embeddings for large-scale heterogeneous spatial omics data, outperforming existing methods and enabling global analysis.

SLAT aligns heterogeneous spatial omics data by integrating omics profiles and spatial context, improving cell-typing resolution and regulatory inference.