Xinze Wu

Building a learnable universal coordinate system for single-cell atlas with a joint-VAE model

The paper introduces UniCoord, a joint-VAE model that learns a universal coordinate system for single-cell transcriptomic data to capture heterogeneity and enable data generation and analysis.

Toward mastering the cell language by learning to generate

The paper introduces scMulan, a large AI model trained to generate cell transcriptomics data with specific attributes, showing it can generate pseudo data, predict missing attributes, and identify driving regulators.

A generic reference defined by consensus peaks for scATAC-seq data analysis

The paper constructs a generic chromatin accessibility reference (cPeaks) from bulk ATAC-seq data to improve scATAC-seq analysis and cell type identification.