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The bioinformatics lab at the Technical University of Munich, TUM Campus Straubing for Biotechnology and Sustainability is led by Prof. Dr. Dominik Grimm from the University of Applied Sciences Weihenstephan-Triesdorf. 

Bioinformatics is a young interdisciplinary research area that develops computational and statistical tools to analyze, store, integrate and visualize biological and biomedical data. One of the main research areas of our group is the development and usage of novel computational tools and machine learning methods to gain a deeper understanding of the underlying genetic architecture of complex biological processes and phenotypes. In addition, we are interested in developing efficient pipelines and applications to process and analyze Next Generation Sequencing (NGS) data. Further, we develop modern cloud-based applications and databases to simplify the analysis, storage, retrieval and visualization of diverse and complex biological and biomedical data.

Software & Resources


 easyGWAS is a novel web- and cloud platform for performing, analysing and comparing  genome-wide association studies (GWAS).

The AraGWAS Catalog

The AraGWAS Catalog is a public and manually curated database for standardised GWAS results for Arabidopsis thaliana.


AraPheno is a central and public repository of high-quality Arabidopsis thaliana phenotypes.

Software & Methods

Software and Methods developed by the group can be found and downloaded at our Github repository.

Lab News

Ist ein Computer schlau?

Ist ein Computer schlau?

„Ist ein Computer dumm oder schlau, was meint ihr?“ Mit dieser Frage hat Prof. Dr. Grimm, Leiter der Professur für Bioinformatik, die erste Vorlesung der Kinderuni im Jahr 2023 eröffnet. Mithilfe von Lego- Steinen und eines Roboterarms machten sich die jungen Forscher mit Prof. Grimm auf die Suche nach einer Antwort.

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Dominik talks at the Computomics Podcast about ML for agriculture

Dominik talks at the Computomics Podcast about ML for agriculture

In this episode Dominik gives us insights into CropML, a BMBF funded project. The project evaluates new machine learning techniques for more accurate plant breeding by integrating heterogeneous external factors.  Different phenotype prediction models, including basic genomic selection methods to more advanced deep learning-based techniques have been compared. Learn why advanced models are the future and where the challenges are.

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Professorship Bioinformatics

Petersgasse 18
94315 Straubing


Prof. Dr. Dominik Grimm

Phone: +49 (0) 9421 187-230
Fax: +49 (0) 9421 187-285

Team Assistant

Anna Fischer

Phone: +49 (0) 9421 187-231
Fax: +49 (0) 9421 187-285