Chair for Computational Biology of Spatial Biomedical Systems

The chair's research focus lies in the areas of scale and dimensional analysis of multi-omics data from systems medicine and/or immunological research, in particular in the development of machine learning and deep learning methods for the integrative analysis of multi-omics data (e.g. single cell RNA sequencing, spatial transcriptomics and imaging techniques) which allow the spatial and functional representation and modelling of complex cellular networks and interactions from tissue samples. These methods are intended to advance basic research in systems biology through the further development of AI methods and to facilitate the personalised diagnosis and therapy of diseases.

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