Analysis of Single Cell Data
The analysis of the large data sets generated from single cell sequencing experiments is crucial to reveal the information on cellular heterogeneity and cell fate trajectories. In this field, a number of DKFZ groups working in computational biology and mathematical modeling have strong activities.
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Brors group
We use computational methods, statistics and machine learning to study cancer genomics and derive treatment predictions; this includes cancer epigenetics and computational oncoimmunology methods.
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Goncalves group
Somatic Evolution and Early Detection
The Goncalves group develops and applies computational methods to genomic datasets to address questions in basic and translational cancer research.
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Stegle group
Computational Genomics & Systems Genetics
The Stegle team uses statistics and machine learning to analyse and integrate genomic variation datasets.
Contact
Oliver Stegle