Prof. Dr. Tim Beissbarth

Contact information

Phone :
+49 - (0)551 - 39 14912
Mail: tim.beissbarth(at)
Room: 2.106 in the Goldschmidtstr. 1, 37077 Göttingen
ORCID-iD: 000-0001-6509-2143

Curriculum Vitae

Academic Carrer

> since 10.2018: Professor, Head of the Institute of Medical Bioinformatics, University Medical Center Göttingen
> 2008-2018: Professor for Biostatistics of the group Statistical Bioinformatics in the Department of Medical Statistics at the University of Göttingen
> 2005-2011: Groupt leader at the Molecular Genome Analysis Department at German Cancer Research Center - DKFZ
> 2002-2005 Postdoctoral Fellow at the Bioinformatics Department at Walter and Eliza Hall Institute of Medical Research, Melbourne -WEHI
>2001-2002: Postdoctoral Fellow at: Computational Molecular Biology - Max-Planck-Institut Molecular Genetics, Berlin
                      Functional Genome Analysis- German Cancer Research Center, Heidelberg
> 6/2001/2002: Teaching of Bioinformatics courses at the Akademie fuer Weiterbildung


> 1998-2001: PhD thesis at the German Cancer Research Center- DKFZ
                       Departments: Theoretical Bioinformatics and Molecular Biology of the Cell I
> 1996-1998: Diplom (Masters) thesis in the Departement of Cell Genetics about MHC Class I - TAP interaction
> 1996: Assistant in Biochemical Practical Courses at the Institute for Biochemistry
> 1995-1996: Worked at the Regional Computing Center - Object Oriented Programming Courses
> 1992-1997: Study of Biology and Computer Science at the University of Cologne
1989-1990: West Valley Highschool - Cottonwood, CA, USA
> 1983-1992: Heinrich-Heine-Gymnasium - Cologne, Germany
> Sept. 8., 1972: Born in Cologne, Germany

Research fokus

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Current projects


In the MyPathSem project, we aim in collaboration with other institutes of the UMG to come up with with a computational platform, or toolbox, which can be used by clinicians for making optimal use of high-throughput data for diagnostic or therapeutic purposes. For more information, please see the official project site.


The aim of this project is to develop a system automatically matching genomic data to suitable treatment options, which will help clinicians to interpret genomic data in a fast and higly quantative manner. more

In Cooperation with the UMC Hamburg-Eppendorf or aim is the identification of a biomarker signature which associates with beneficial outcome on specific lipid therapy, and ideally is not dynamic under ongoing therapy. more

Selected Publications

Perera-Bel J., Hutter B., Heining C., Bleckmann A., Fröhlich M., Fröhlich S., Glimm H., Brors B., Beißbarth T.:
From somatic variants towards precision oncology: Evidence-driven reporting of treatment options in molecular tumor boards.
Genome Med. 10(1):18
doi: 10.1186/s13073-018-0529-2 link

Wolff A., Perera-bel J., Schildhaus HU, Homayounfar K., Schatlo B., Belckmann A., Beißbarth T.:
Using RNA-Seq Data for the Detection of a Panel of Clinically Relevant Mutations.
Stud. Health Technol. Inform. 253:217-221 link

Wolff A., Bayerlova M., Gaedecke J., Kube D., Beißbarth T.:
A comparative study of RNA-Seq and microarry data analysis on the two examples of rectal-cancer patients and Burkitt Lympoma cells.
PLoS One 13(5):e0197162
doi: 10.1371/journal.pone.0197162 link

Professional activities

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