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Clinical bioinformatics & machine learning in translational single-cell biology

Rare cell populations play a pivotal role in the initiation and progression of immune processes and complex diseases. Our research aims at identification and molecular characterization of such subpopulations in the complex tissue context across health and disease states. Ultimately, we aim at elucidating intra- and intercellular mechanisms of such cell subsets conferring their function and association to organism-level phenotypes. Such insights will enable and drive a new kind of trials that are based on single-cell profiling and achieve cell identity biomarkers, i.e. biomarkers defined by cell subpopulations with characteristic molecular or morphological profiles. To this end, we follow an integrated experimental and machine learning approach that centers around information rich, high dimensional single cell measurements and their comprehensive mathematical analysis in the context of immune and cancer biology.