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Our research aims at deepening the understanding of genome biology and advancing personalized medicine. Besides our own fields of interest we engage in collaborative research projects with the department of Human Genetics, the Excellence Cluster Immunosensation and with basically any lab on the campus that has challenging high dimensional data. In most of our projects we are using artificial intelligence in the analysis of big biomedical data sets and we are trying to understand what the machines are doing.

In the PEDIA (Prioritization of Exome Data by Image Analysis) study we evaluate whether computer vision can improve the interpretation of genomic data. The PEDIA score integrates multipe information from the molecular level and phenotypic level, amongst them HPO-based phenomizer scores and gestalt-scores from Face2Gene CLINIC.




Computer-assisted image analysis also allows a systematic analysis of molecular pathway disorders. As an examplary disease we work on GPI-anchor deficiencies.



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