Dr. Chan leads the Quantitative Science Division of the Duke Center for Human Systems Immunology and oversees a broad research program in quantitative immunology.
Mathematical immunology. We construct mathematical models, informed by experiments, to investigate and generate mechanistic hypotheses for how the immune system interreacts with and responds to microbes, vaccines, cancer, and senescent cells. We have developed deterministic and stochastic mathematical models to provide insight into diverse immune phenomena, including TCR activation, immune synapse function, light and dark zone formation in the germinal center, HIV rebound after treatment interruption, and transplacental transmission of CMV.
Immune data science. We develop statistics and machine learning methods and software to provide insight into complex assay data from immunological experiments. We have developed these tools for flow and mass cytometry, high-throughput screening for natural product testing, shRNA and CRISPR screens, GWAS, antibody function assays, immunofluorescent imaging, single cell RNA-seq and ATAC-seq, and spatial transcriptomics. Most of these methods are implemented as open-source R or Python packages.
Collaborative projects. We are engaged in long-term collaborative interdisciplinary projects where the focus is on the analysis and interpretation of complex immune data sets. These projects span multiple medicinal domains, including vaccine development, infectious disease, solid organ transplantation, cellular senescence, cancer immunology, allergy and atopy, and autoimmunity. Recently, we are engaged in collaborations to refine the concept of immune resilience (IR) and its role in response to infection, surgical trauma, and climate-change induced immune stressors.