Lihua Zhang

SpaTranslator translates spatial omics data across modalities using a deep generative framework, outperforming baselines in clustering and biological coherence.

The paper identifies keratinocyte subpopulations in stable vitiligo skin that drive disease persistence through CXCL signaling and altered metabolism.

CellChat infers communication probabilities between cell groups using a mass-action model and 2,021 curated ligand-receptor interactions (multimeric complexes, cofactors), then compares signaling networks across scRNA-seq datasets.

This paper introduces scFAN, a deep learning model that predicts genome-wide TF binding in single cells using single-cell ATAC-seq data and pre-trained on bulk ATAC-seq, DNA sequence, and ChIP-seq data.

This study compares eight imputation methods for scRNA-seq data, finding no single method outperforms all others across different tasks and datasets.