The M3 Research Center
Malignome, Metabolome and Microbiome

The development of data science methods for biomedical research is our deeply grounded research focus. The technological developments, in particular for high-throughput methods (omics) and imaging, have led to unprecedented changes on how biomedical research is being performed, but has also significantly increased the promises that are associated with the data generated by these technologies for patients, researchers and other stakeholders. Through interfaces between heterogeneous data repositories, it is our goal to build Big (FAIR) Data ecosystems. The bioinformatics workflow framework (https://nf-co.re) that we co-develop since 2020 (Ewels et al., Nature Biotech, 2020) is our workhorse technology to provide highly reproducible and scalable preprocessing of biomedical high-throughput and imaging data. Nf-core has become and
outstanding international open-source project, counting today more than 6,000 data scientists contributing and using the framework. Following data FAIRification, we are currently working on new methods for reproducible, robust and scalable data propressing and translational AI, alike. Some of this work got recently accepted for publication in Oxford Bioinformatics (Heumos et al., 2023). With this research we intend to increase the knowledge on the technical needs for clinical translational of AI methods.

Biosketch

Sven Nahnsen studied Biomathematics at the University of Greifswald (Greifswald) and Biotechnology and the Universtiy of Strasbourg (France). He complemented his studied with a research stay at the University of Cambridge (UK) and graduated with a Diplôme d’ingénieure en biotechnology from the Ecole superieure de biotechnology (ESBS) of the Universities of Strasbourg, Basel and Freiburg. In 2010 he gradueated with a PhD in Bioinformatics from the University of Tübingen. Since 2012 he is heading the Quantitative Biology Center (QBiC) and become its scientific director in 2018. Since 2021 he is professor for Biomedical Data Science at the Department of Computer Science at the Science Faculty and also co-opted at the Faculty of Medicine of the University of Tübingen.

Interview

Data science methods for biomedical research – Interview with Prof. Dr. Sven Nahnsen

In this Interview, Prof. Dr. Sven Nahnsen explains how open-source tools like nf-core and FAIR data principles are shaping the future of biomedical research. Learn how the team bridges data, reproducibility, and translational AI to bring innovation into the clinic.

Beim Abspielen des Videos werden Daten an YouTube übertragen. Weitere Hinweise finden Sie in unserer Datenschutzerklärung.

Team

• Team-Members (QBic)

Co-affiliations

• Quantitative Biology Center (QBiC), Eberhard-Karls University of Tübingen, Tübingen, Germany.
• Biomedical Data Science, Department of Computer Science, Eberhard-Karls University of Tübingen, Tübingen, Germany
• Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard-Karls University of Tübingen, Tübingen, Germany