Big Data Analysis and Biomedical Research meet in our lab: We develop novel Data Mining Algorithms to detect patterns and statistical dependencies in large datasets from Biology and Medicine.
We try to reach two grand goals: To enable the automatic generation of new knowledge from Big Data through Machine Learning, and to gain an understanding of the relationship between the function of Biological Systems and their molecular properties. This understanding is of fundamental importance for Personalized Medicine, which tailors medical treatment to the molecular properties of each patient.
Our lab receives significant external funding from the European Union through a Marie Curie Initial Training Network (2013-2016), from the Krupp Foundation through the Alfried-Krupp Award (2013-2018), and from the Swiss National Science Foundation through a Starting Grant from the ERC backup scheme (2015-2020).
The source code and data sets of our research projects can be downloaded from our GitHub repository. More information on the individual projects can be found here.
easyGWAS Our online platform for computing, storing, sharing, analyzing and comparing the results of genome-wide association studies.