Multi-dimensional omics data analysis
Our research group focuses on software development to identify, analyze, and integrate omics data.
Previous and Current Research
The Multidimensional Omics Data Analysis group is a cooperation with the Leibniz Institute for Analytical Science (ISAS). The development of novel omics methods in the last 10-20 years has made it possible to analyze and characterize the pathogenesis of most diseases in detail. However, these methods require complex and fast bioinformatics workflows to identify and interpret the corresponding genes, proteins and metabolites in the raw data. Subsequently, prognostic and predictive markers and possibly new therapeutic targets can be derived from the multi-omics data sets using biostatistical methods and machine learning algorithms. The challenge here is to link the individual omics data with each other, with clinical data (diagnoses, analyses, therapy), with information from clinical databases and already known publications and finally to visualize the results. In addition, omics data sets enable the development of mathematical models to describe the disease. These models could be used to test therapeutic approaches, or they could be fed back into the clinic to support diagnosis and clinical decisions.
Key research topics of the group
- Development of cloud-based web software
- Usage of knowledge graphs for omics data integration and analysis
- Linking omics data with modeling
- Microbiome research