Research Theme: A computational biology lab focused on understanding various contexts at single-cell resolution, including both data analysis and method development

Single-cell technology enables people to distinguish the heterogeneous signals from a biological sample. Accordingly, many single-cell-based methods and data have been generated. Currently, it is quite demanding for researchers to analyze this big data to extract a hidden feature that cannot be detected by single dataset. Especially, we are interested in understanding cancer field but also interested in other immunological diseases. We are trying to establish a hidden feature with big “pan-cancer” data.

Approach

• Single-cell RNA, TCR/BCR, ATAC, Spatial, Perturb-seq
  
• Cancer & Immunology
  
• Mulit-modal integration
  
• AI-based method development or analysis (GAN, LLM-based)
  

Projects

• Title: Pan-cancer big data analysis
  
  
  
  
  
  
  

• Title: LLM-based pan-cancer single-cell modeling