Data Science for Life Sciences

Continuous new developments in DNA sequencing and mass spectrometry have opened up the possibility of probing the molecular landscape of single and bulk cells on an unprecedented scale. 

For example, The Cancer Genome Atlas (TCGA) and the International Cancer Genomics Consortium (ICGC) have applied Next Generation Sequencing (NGS) technologies to screen the tumor mutational landscape of more than 85,000 cancer patients, generating over 3 petabytes of data. Using this large dataset, multi-institutional research teams have identified hundreds of cancer driver genes, which can drive cancerous growth in normal cells upon mutations. With this knowledge, pharma companies have started developing novel targeted and immuno- therapies for precision medicine.

Our research is in alignment with the aforementioned international and multi-institutional research programs for precision medicine. We have extensive experience in the development of novel Omics-based diagnostics algorithms and the analysis of non-coding mutations in cancer patients. We focus in particular on the detection of cancer-specific alternative splicing events for diagnostic purposes. For our investigations, we integrate whole-genome Next-Generation-Sequencing data, RNA sequencing data, Mass-Spectrometry based proteomics data, experimental X-ray protein structures, and protein interaction network data