Our research interests are in using and developing computational methods for the analysis of single-cell genomic data to elucidate cell-to-cell heterogeneity within a population of cells with the ultimate goal of understanding how gene expression levels are regulated. Recent technological developments for single-cell DNA and RNA sequencing in conjunction with both microfluidic and combinatorial barcoding approaches allow genomes and transcriptomes from tens of thousands of single cells to be assayed. Despite the exponential increase in the amount of single-cell data, the computational tools necessary to achieve robust biological findings are still either undeveloped or in their infancy.
Our ultimate research goal is to understand how genetic, epigenetic, environmental, and stochastic variation regulate the relationship between genotype and phenotype at the single-cell level. Our group with strong statistical and computational backgrounds collaborates with outstanding empirical groups to provide novel solutions to complex biological problems. We will help design experiments properly thus isolating biological variables of interest, utilize and develop computational methods analyzing high-throughput genomic data, and assess whether a biological question of interest and its related hypothesis are sensible for the data.
Advisor Professor : Kim, Jong Kyoung
Lab of Single-cell Genomics Homepage