German Cancer Research Center
Matthias Schlesner‘s research focuses on the integrative analysis of large-scale biomedical data and the development of computational methods for the analysis of omics data. Specific aims include to improve the understanding of mechanisms driving malignant transformation and tumour progression, and to identify tumour-specific vulnerabilities as well as resistance mechanisms. The analysis pipelines developed in his group are used for whole genome sequence data analysis at the DKFZ, in the three German projects within the International Cancer Genome Consortium (ICGC), and as core analysis pipelines in the ICGC Pan Cancer of Whole Genome Analysis (PCAWG) initiative.
Principal Investigator | Supervisor
Projects within the Big Data Project
- PhD thesis supervised within the RTG framework:
„Integrative analysis of imaging and multi-omic data“ (working title)
Open for more cooperations in the field
Research interests of relevance to the project
- Integrative omics data analysis
- Cancer genomics
- Personalized medicine
- Method development for computational biology
Field of Expertise
- Computational Biology
- Paramasivam N. et al. (2019) Mutational patterns and regulatory networks in epigenetic subgroups of meningioma. Acta Neuropathol, epub ahead of print
- López C. et al. (2019) Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma. Nat Commun, 10(1):1459.
- Gröbner S.N. et al. (2018) The landscape of genomic alterations across childhood cancers. Nature, 555(7696):321-327.
- Gu Z. et al. (2016) Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics, 32(18):2847-9
- Richter J. et al. (2012) Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing. Nat Genet, 44(12):1316-20.
Bioinformatics and Omics Data Analytics (B240)
m Neuenheimer Feld 280
Phone: +49 6221 42-2720
Fax: +49 6221 42-3563