Computational solutions from data science and machine learning to solve biomedical problems


Our research focuses on developing computational solutions from data science and machine learning to solve biomedical problems. In addition, we aim to develop new methods and algorithms, e.g., for analyzing (meta-)genomic and (meta-)transcriptomic data of microorganisms, as well as for genome assembly and functional annotation.

The de.NBI cloud allows us to perform computationally intensive calculations without limitations and thus increases our options to achieve set research goals! Among other things, we have used de.NBI to identify novel antimicrobial resistance targets using Deep Learning, develop a complex genome annotation framework (MOSGA), or establish a new error-correcting code for DNA data storage applications. We benefited from the exceptionally high computing power and the diverse configuration options, which allowed us to specifically adapt the requested resources to our needs, e.g., via OpenStack VMs.

Thanks to the excellent support provided by de.NBI, resource release, subsequen software installation, process development, and environment migrations are quick and easy. In addition, the support team is happy to provide immediate assistance in implementing technical solutions to complicated issues. Therefore the de.NBI cloud is an extremely valuable resource for newcomers and experienced data scientists with ambitious research goals. Several projects are currently running on de.NBI and future applications are planned.

Prof. Dr. Dominik Heider
Prof. Dr. Dominik Heider from Biomedical informatics, Department of Mathematics & Computer Science University of Marburg