Ziyu Shi

LiverHomo integrates human liver scRNA-seq data with PPI and cell-cell communication networks to provide an interactive resource for exploring liver health and disease.

The paper introduces Cerebra-Epistasis, a framework that improves multi-mutant fitness prediction by modeling epistatic effects and integrating structure-aware sequence analysis.

MutCleaner standardizes mutation datasets for variant effect prediction by cleaning, validating, and organizing mutation records across 16 datasets with over 12.14 million entries.

LiverDCP models disease biology by integrating single-cell data and protein interactions to identify disease-risk genes and therapeutic targets.