Data-Driven Virus Discovery (DDVD) is revolutionizing the way novel viruses are discovered. Being independent of the collection and processing of biological samples, DDVD allows for screening massive amounts of next generation sequencing (NGS) data for the presence of known and unknown viral genome sequences. We utilize DDVD to analyze 1+ million of public NGS datasets from the Sequence Read Archive (SRA) and find 150+ thousand sequences of viral origin. We use these data to assess the risk of spillover into humans across the RNA viruses and to study various aspects of viral evolution across geologic time scales.

Cancer mutanome vaccines targeting neoepitopes derived from somatic mutations have ideal properties to become an essential part of modern multimodal cancer therapy. Our goal is to fully realize this personalized cancer immunotherapy concept by addressing the key genomic and immunological challenges for successful application of this approach in patients with any type of cancer.

We work on imaging for particle therapy. Particle beams (e.g. protons) can precisely destroy tumors while sparing healthy tissue. To verify the irradiation, Compton cameras (CC) can be used to detect gamma rays emerging from the patient. CC require complex algorithms to reconstruct images. We employ Monte Carlo simulations to recreate the irradiation and test reconstruction algorithms. The simulations and development of reconstruction approaches require much computing power. Thanks to HLRN, we simulate realistic therapeutic beams, the emerging rays and its detection with CC, and can test our reconstruction. Our approaches notably improve image quality. Further improvements are planed using a-prori information and refined data selection.