- Focusing on data-driven cancer research, combining high-throughput genomic, transcriptomic and proteomic profiling approaches, to comprehensively investigate molecular landscapes of GI cancer and identify prognosis/predictive biomarkers and novel therapeutic targets
- Functional study of identified candidate genes using patient derived tumor organoids, a new generation of ex vivo models.
- Pan-cancer study and in-depth data mining.
Tools & Databases we developed
- PINA: An integrated platform for protein interaction network construction, filtering, analysis, visualization and management
- CVCDAP: DIY Your Cancer Cohort & Omics-X Analysis
- The center is equipped with a high-performance cluster computing system (760 CPU cores and 5.12 TB memory) and a high-speed (56Gb/s) storage network (1.44 PB) for analysis of large cohorts of -omics data.