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.

© dkfz.de

Brors group

Applied Bioinformatics

We use computational methods, statistics and machine learning to study cancer genomics and derive treatment predictions; this includes cancer epigenetics and computational oncoimmunology methods.

© dkfz.de

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.

© dkfz.de

Höfer group

Theoretical Systems Biology

The Höfer group ....

© dkfz.de

Stegle group

Computational Genomics & Systems Genetics

The Stegle team uses statistics and machine learning to analyse and integrate genomic variation datasets.

Contact

Oliver Stegle

to top
powered by webEdition CMS