Research Group Computational Virology

We are a computational research group, embedded in the RESIST cluster of excellence, that is interested in studying viruses and viral infections using sequence-based approaches. A common theme in our projects is the utilization of unprocessed data from public sequencing archives to generate and test scientific hypotheses in close collaboration with experimental virologists and clinicians. We develop and apply high-performance computing and deep learning workflows to analyze the vast amount of available data and metadata.

A major line of our research is the study of viral genetic diversity and virus evolution. We aim at characterizing, as comprehensively as possible, the eukaryotic virome as well as the total virome of diseased and healthy humans to explore the impact of inter-individual differences on diseases. Moreover, we seek to discover unknown animal viruses that are closely related to pathogenic human viruses and may thus serve as experimental models. And we aim at quantifying the risk of specific RNA viruses or virus groups for spill-over into humans in order to become better prepared for future pandemics.

In a second, complementary line of research, we are interested in computationally dissecting the complex interplay of genetic variation in the human genome in order to identify those changes that are associated with course or severity of diseases. We closely collaborate with other RESIST researchers with the aim to uncover such genetic determinants for severe infection with the human respiratory syncytial virus (RSV) among young children.