Daiwei Zhang

iSCALE predicts super-resolution gene expression and annotates tissue architecture in large tissues, revealing features missed by conventional spatial transcriptomics.

The paper conducts proteome-wide and transcriptome-wide association studies for blood lipids, finding high-level consistency between proteome and transcriptome-lipid associations across tissues.

This paper introduces Patho-DBiT, a method for spatial transcriptomics in FFPE tissues, enabling RNA biology analysis including splicing, variants, and regulatory networks in clinical samples.

TESLA annotates tumor microenvironment cells and detects spatial transcriptome differences using spatial transcriptomics data.

This study identifies 303 novel genetic signals associated with plasma metabolites in Finnish men, revealing biological insights into disease mechanisms.

This study evaluates the utility of breast and prostate cancer polygenic risk scores across different ancestry groups using UK Biobank data, showing significant enrichments in cancer cases within top PRS percentiles.

This paper introduces two methods to improve ancestry prediction in GWAS by reducing bias and computational cost compared to existing approaches.