We are leveraging computational approaches and large-scale functional genomics resources to understand the GWAS-identified risk loci of human complex diseases, including questions about 1) prioritization of functional variants, 2) linkage of target genes, 3) identification of critical tissues/cell types, 4) functional pleiotropy across different diseases, 5) multifaceted integration of functional genomics data, 6) single-cell characterization, and 7) evolutionary forces in shaping diseases susceptibility.

We are utilizing cutting-edge artificial intelligence algorithms to enable high-performance screening, early detection, accurate diagnosis, and effective management of human diseases, including the clinical applications of 1) deep learning algorithms, 2) large language models, 3) cross-modality fusion between genetic and clinical data, and 4) real-world application design.