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.
Software and Methods developed by the group can be found and downloaded at our Lab News
New Journal Paper about Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward
Sara published a review paper in a collaboration with Zoran Nikoloski from the Max Planck Institute of Molecular Plant Physiology and the Intitute of Biochemistry and Biology at the University of Potsdam about the “Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward”
New Journal Paper about Genetic Characterization of Rat Hepatic Stellate Cell Line HSC-T6 for In Vitro Cell Line Authentication
In a great collaboration with Prof. Weiskirchen from the RWTH University Hospital Aachen we published a new paper about the “Genetic Characterization of Rat Hepatic Stellate Cell Line HSC-T6 for In Vitro Cell Line Authentication”
Deep Learning-based Early Weed Segmentation using UAV Images of Sorghum Fields (Video)
Nikita gave a talk at the 8th HEFagrar PhD Symposium from the Hans Eisenmann-Forum in Freising about “Deep Learning-based Early Weed Segmentation using UAV Images of Sorghum Fields”.
