The lab focuses primarily on various aspects of machine learning and data mining of biomedical data and on developing innovative approaches for systems medicine. Many of the projects are conducted in the close cooperation with the Odense University Hospital as well as with the Department of Biochemistry and Molecular Biology.
Recently, Richard Röttger has become co-PI, steering board member and work package leader of the 4.5M EUR H2020 project "FeatureCloud" (grant nr. 826078). Here, we are developing in close collaboration with medical doctors, novel federated machine learning techniques which finally enable the training of artificial intelligence on molecular medical data and electronic health records in a secure and privacy-aware manner: We bring the machine learning to the data and not the sensitive data into the cloud.
Besides the just mentioned FeatureCloud project, the Computational Biology Group group is also the core devleoper of ClustEval, an efficient, highly adaptable and fully automated clustering framework. In terms of bosting systems medicine, we have recently published a time-series clustering tool coupled with network enrichment, TiCoNE. Furthermore, we developed TransClust, an efficient, state-of-the-art clustering tool and web-platforms for the in depths analysis of gene regulatory networks.
A complete list of publications by Richard Röttger can be found here.