Large-scale biomedical data analysis for next generation diagnostics

The members of the MEDLAB develop new mathematical methods that allow identification of disease signatures within modern large-scale bio-medical datasets, such as genomics, proteomics or imaging sources. These signatures are the foundation to build new diagnostic tests but also to gain insights about the underlying disease mechanisms.

The key aspects in our work is that disease-related changes in cells happen on many biological levels. Our methods enable a data-centric integrative analysis of all these levels combining machine-learning, image analysis and network-based approaches. This ultimately allows generation of more detailed and informative models, compared to classical approaches.


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