Lab focus: Statistical bioinformatics and cancer research

Modern technologies are revolutionizing the field of biomedical research and changing the way scientists study cancer. With the help of the single-cell and the spatial technologies, we are now able to examine gene expression and gene regulation at the cellular level while keeping track of the cells' spatial context. This allows us to identify cell of origin for various cancer diseases and to study how tumour cells influence their microenvironment.

The goal of my research group is to develop novel bioinformatics methods and software tools to analyze and interpret experimental data generated by these cutting-edge technologies for cancer research.

Research Interest

The Chen laboratory collaborates closely with biomedical scientists on cancer research, using the latest genomic technologies to study cancer genesis and other diseases. We analyze RNA-seq data to identify differentially expressed genes, transcripts or molecular pathways between experimental conditions. We analyze ChIP-seq and ATAC-seq experiments to study epigenetic marks, chromatin structure and accessibility. We analyze bisulfite-seq data to examine DNA methylation. We also analyze single-cell RNA-seq and spatial transcriptomics data to explore cellular composition and cancer development at the single-cell level as well as in the spatial context.

In addition to research collaborations, our laboratory develops novel statistical strategies and bioinformatics methods to better interpret different types of data. We also implement our methods in open-source software, which is publicly available through the Bioconductor project.