Ze Zhang

The paper introduces decemedip, a Bayesian hierarchical model for cell type deconvolution of MeDIP-seq data, showing its accuracy and utility in identifying methylation signatures.

This study identifies DNA methylation alterations in tumor endothelial cells using bulk specimens and deconvolution methods, revealing potential therapeutic targets in breast cancer.

SNAP improves classification performance for cell-free chromatin data while maintaining data retention through optimized quality filters and modular design.

The paper enhances cell deconvolution of peripheral blood using DNA methylation to provide high-resolution immune profiling by including 12 leukocyte subtypes and validated libraries.