Wei Tian

The paper maps 3D genome organization and DNA methylation across 86,689 single nuclei from 16 human tissues, revealing cell-type-specific variations and discrepancies between methylation and chromatin structure.

This paper creates a multimodal single-cell atlas of the human basal ganglia, revealing epigenomic and 3D genome features across cell types and linking them to disease-associated genetic risk.

This study identifies how genetic and environmental factors shape the human immune cell epigenome through differential methylation and chromatin accessibility changes.

This study examines DNA methylation changes in blood and muscle across different training programs and timepoints, identifying DMRs linked to exercise adaptation, sex, and physiological functions.

The paper maps epigenetic and spatial transcriptomic changes in aging mouse brain using single-cell multi-omic data and develops deep-learning models to predict age-related gene expression changes.

The paper introduces BAllC, a binary format for single-cell DNA methylation data, and BAllCools, a toolkit to improve storage and operational efficiency.

CASTpFold extends the CASTp tool to provide accurate and comprehensive protein surface topography analysis using AlphaFold2 structures and functional annotations.

The paper generates a single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain, identifying methylation patterns and regulatory networks across cell types and brain regions.

This study identifies AD-specific DNA methylation signatures and chromosomal epigenome erosion in LOAD brain cells and shows their conservation in induced neurons.

The paper constructs a single-cell chromatin accessibility atlas of the human brain, identifies cell-type-specific regulatory elements, and develops models to predict regulatory function of disease risk variants.

The paper analyzes gene regulatory programs in the neocortex of rodents and primates using single-cell multiomics, finding rapid evolution of cell type-specific gene expression and TE-driven cCREs.

The paper identifies 188 cell types in the human brain using single-cell DNA methylation and 3D genome data, and develops a tool to predict cell types based on methylation patterns.

The paper compares cellular diversity in the primary motor cortex across human, marmoset, and mouse using single-nucleus transcriptomics and epigenomics, finding conserved cell types and species-specific adaptations.

The paper constructs a DNA methylation atlas of the mouse brain at single-cell resolution, revealing epigenetic diversity and spatial organization of neuronal subtypes.