Projects
Biospectroscopy
Bioinformatics
Computational analysis plays a central role in unveiling disease specific biomarkers - both for tissue imaging data and spectral data obtained from body fluids. To identify disease specific features out of complexly structured spectral data, algorithmic methods of pattern recognition are employed that use spectral or morphological features to distinguish healthy from diseased samples. In this context also up to date Deep Learning methods are used. Combining image data and spectral data from different microscopes often result in a more detailed overall picture of the disease pattern. These cross platform analyses present an essential challenge for the bioinformatics and thus constitute a main focus of bioinformatics work in PURE.
In order to store and process the large amounts of data with computationally demanding pattern recognition algorithms, the bioinformatics group maintains an IT infrastructure with a central file server facility as well as high-performance computing facilities.
Equipment
Storage Infrastructure featuring a total capacity of >400 TByte
High-Performance-Computing:
> computing capacity with >1500 CPU cores
> HPC computer with up to 1 TByte main memory
> GPU computer