What We Do
Research
Research Areas
Somatic Mosaicism
We study somatic mutations that accumulate during cell division, tracing their origins through mutational signature and lineage analysis across diverse tissue types.
Brain
Detecting somatic variants from high-depth WGS/WES and mapping brain cellular heterogeneity through scRNA-seq and spatial transcriptomics.
Lung
Discovering rare disease genes via whole-exome sequencing in pulmonary hypertension cohorts, supported by bulk and single-cell transcriptomic analyses.
Urine
Building prognostic models for kidney transplant outcomes by integrating transcriptomic data with single-cell foundation models.
Multi-Omics
Integrating genomic, transcriptomic, epigenomic, and proteomic data to functionally interpret somatic mutations and their impact on disease.
Developmental Senescence
Exploring how chromatin accessibility changes trigger senescence in hESCs using scATAC-seq, combined with scRNA-seq to build gene regulatory networks that reveal epigenome–transcriptome cross-talk.
Parkinson's Disease
Investigating how somatic mutations accumulate in the aging brain and contribute to neurodegeneration, using multi-omics approaches to trace mutation–phenotype relationships.
Bio-AI
Leveraging foundation models and deep learning to predict variant effects, design therapeutics, and build prognostic tools.
| Model | Application |
|---|---|
| Single Cell FM | Prognostic prediction for transplant recipients using scFM and transcriptomic data |
| Genomic FM | Predicting functional impact of genetic variants through large-scale genomic language models |
| Structure Prediction | Designing novel receptor-binding proteins with RFdiffusion and AlphaFold3, validated through structural filtering pipelines |