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Bioinformatics

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

 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

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

New DFG Funding

New DFG Funding

We successfully attracted funding from the German Research Foundation (DFG) for the project “Reinforcement Learning for Automated Flowsheet Synthesis of Steady-State Processes”

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New Publication in Nature Methods: The AIMe registry for artificial intelligence in biomedical research

New Publication in Nature Methods: The AIMe registry for artificial intelligence in biomedical research

An international research team with participants from several universities including Prof. Dr. Dominik Grimm has proposed a standardized registry for artificial intelligence (AI) work in biomedicine to improve the reproducibility of results and create trust in the use of AI algorithms in biomedical research and, in the future, in everyday clinical practice. The scientists presented their proposal in the scientific journal “Nature Methods”.

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New Publication: Automated Flowsheet Synthesis Using Hierarchical Reinforcement Learning

New Publication: Automated Flowsheet Synthesis Using Hierarchical Reinforcement Learning

Recently we showed that reinforcement learning can be used to automatically generate process flowsheets without heuristics or prior knowledge. For this purpose, SynGameZero, a novel two-player game has been developed. In this work we extend SynGameZero by structuring the agent’s actions in several hierarchy levels, which improves the approach in terms of scalability and allows the consideration of more sophisticated flowsheet problems. We successfully demonstrate the usability of our novel framework for the fully automated synthesis of an ethyl tert-butyl ether process.

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Kontakt

Professorship Bioinformatics

Petersgasse 18
94315 Straubing

Head

Prof. Dr. Dominik Grimm

Phone: +49 (0) 9421 187-230
Fax: +49 (0) 9421 187-285
E-Mail: dominik.grimm@hswt.de

Team Assistant

Anna Fischer

Phone: +49 (0) 9421 187-231
Fax: +49 (0) 9421 187-285
E-Mail: anna.fischer@hswt.de

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