Jingyang Qian

miRTalk infers EV-derived miRNA-mediated cell-cell communication from scRNA-seq data, showing high accuracy in simulated and real datasets.

Bulk2Space deconvolves bulk RNA-seq data to reveal spatial and cellular heterogeneity using single-cell and spatial transcriptomics references, identifying immune cell spatial variance and novel gene patterns in mouse brain regions.

SpaTalk infers cell-cell communication from spatial transcriptomic data using a knowledge graph and graph network, outperforming existing methods on public datasets and revealing insights into tissue communication mechanisms.

scSpace reconstructs a pseudo-space from single-cell RNA-seq data to identify spatially variable cell subclusters and their biological relevance.

The paper constructs a single-cell transcriptomic atlas of liver non-parenchymal cells in healthy and diseased mice, identifying disease-specific heterogeneity and functional changes.