Xiaohui Fan

The paper introduces Palette, a method to infer spatial gene expression from bulk RNA-seq data, and constructs DreSTEP, a resource for studying gene expression and spatial interactions in zebrafish embryos.

The paper identifies differences in stress response and function between macular and peripheral Muller cells, linking these differences to vulnerability to degenerative diseases.

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

This study evaluates GPT-4 and GPT-3.5 in molecular tasks, showing their strengths in molecular optimization but challenges in generating complex molecules.

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 transplanted livers and identifies an EAD-associated pathogenic cellular module.

scDeepSort is a reference-free cell-type annotation tool for scRNA-seq data that outperforms reference-dependent methods in accuracy across human and mouse datasets.

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.