A big data approach for personalised infection medicine The immune function at an individual level is highly variable. It is therefore important to capture the impact of genetics and biological molecules on the immune function to better understand the immune system as a whole. In my talk, I will describe novel strategies to study these factors by simultaneously modeling information from genome, transcriptome, proteome, metabolome and environmental profiles. The results from such a study will reveal insights into the mechanisms driving the immune response to pathogens and provide mathematical models for predicting individual variation in immune functions, a crucial step towards personalized prevention/treatment of infectious diseases. Yang Li is a computational biologist focusing on integration of multi-omics and single cell omics data to study the interaction of genetic background and environment, and its contribution to infection and immune-related diseases. Y. Li showed how genetic risk factors of the host and their downstream molecular pathways determine and predict the human immune functions, which are crucial to treat infectious and allergic diseases in an individualized manner (Cell 2016, Nat Med 2016, Nat Immunol 2018). She recently performed one of the first multi-omics studies of dysfunctional immune system in mild and severe COVID19 patients (Cell 2020). For her research, she just received the prestigious ERC Starting Grant “ModVaccine” on improving vaccine efficiency.