Zhirui Hu

This paper introduces CREAM, a deep learning model for differential expression prediction using personalized genomes, showing improved performance on training genes but challenges in generalizing to unseen genes.

scATAnno automatically annotates scATAC-seq data using reference atlases, outperforming existing methods across multiple datasets.

CellWalker2 improves cell type annotation and mapping by integrating multi-omic data and hierarchical relationships, outperforming existing methods in simulations and demonstrating applications in brain and immune system data.

PccGEO designs functional genetic elements using a knowledge-constrained deep learning model, achieving high success rates in promoter design for E. coli.