Bioinformatics and Digital Health

Accurately processed data have an added value over unprocessed raw data. One can speak of a value chain here, comprising several processing and analysis steps that help transform the raw data into validated and conclusive results.

The Project Group for Bioinformatics improves the analysis of data collected in health research by using novel intelligent methods and provides special techniques that enable efficient and validated analyses. An example is the identification of suitable stratified cohorts for medical analyses.

In the future, analysis of health-related data will be based on efficient integration of large medical data sets. In the first place, large amounts of data will be generated in studies and examinations, in the field of multi-omics analyses in particular. In the second place, these data will then have to be linked with experimental and clinical metadata, such as annotations, and with other data, such as patient records, to enable meaningful analyses. Data integration, therefore, will have to support a broad range of data formats. By efficiently integrating several data sets ("data network") we enable insights that were impossible to get before through the use of isolated systems.