We are computational biology lab! Our lab is focused on development of statistical and computational algorithms to explore genetic and epigenetic regulation in cancer and eye diseases from high-throughput sequencing data. We attempt to dissect the upstream and downstream regulatory mechanisms of deregulated genetic and epigenetic elements involved in the development and progression of tumors, by uncovering multidimensional omics data of genomic, transcriptional, post-transcriptional and epigenetic levels.
Precise identification of molecular biomarkers for cancer diagnosis, prognosis and therapeutic intervention
a. Computational identification of epigenetically-regulated cancer driver targets and genome-wide CRISPR screening validation.
b. Functional exploration of ncRNAs in cancer-immune system interactions.
Artificial Intelligence and biostatistical algorithms development for medical diagnosis
a. Development of statistical methods and algorithms for analysis of single-cell RNA sequencing data and DNA methylation data.
b. Development and application of Artificial Intelligence algorithm in eye disease medical diagnosis.
Evolution and allelic architecture of eye diseases: investigate the impact of common and rare genetic variants to both the non-Mendelian and Mendelian phenotype
The field of human genetics has been leveraged by large-cohort based genome-wide association studies (GWAS) and mutation burden, which identified thousands of genomic regions containing polymorphisms/variants that influence a wide variety of disease trait. These disease-associated loci have provided tremendous novel clues for disease biology and molecular mechanisms. We are enthusiastically working on building causal networks linking specific genetic loci to refractive error of eye disease phenotypes.