Biomedical Data Analysis

The Biomedical Data Analysis team mainly focuses on the data obtained in medical biology with high-throughput molecular profiling and to make omics technologies usable for translational applications. These include the extraction of relevant biological signals and predictive features from neurodegenerative diseases and immunity across species (human, mouse, rat, pig) and in a variety of tissues and biofluids (kidney, liver, brain, blood) on various modalities: DNA methylation, RNA expression, protein abundance, and tissue histopathological images. We focus on integration and analysis of the data using machine learning approaches and statistics to reveal disease-relevant regulated pathways and improve our understanding of whole biological systems. Our group continuously develops and applies state-of-the-art omics pipelines, as well as omics-based diagnostic analysis and therapeutic approaches closely collaborating with the Data Integration and Genomic AI teams and in cooperation with several research groups both within and outside the UKE. The main experiences we have are in biostatistics, large-scale data analysis and integration of multi-omics data, machine learning and scientific programming, which are beneficial for our collaborators.