Research Platform Genomics

Practical example and current challenges

• Biomedical research has developed into a data-intensive science: Genome sequencing generates project data in the tera-byte range per sequencing unit within a few days.
• Research is dependent on a technical infrastructure, that both enables the secure storage of large amounts of data and provides a powerful computer architecture for the complex analysis of data in the petabyte range.
• In order to be able to better predict the development of cancer in the future and support the development of new treatment methods on the basis of data, the German Cancer Research Institute in Heidelberg and the Berlin Institute of Health/ Charité are currently setting up a cloud platform for the storage and analysis of genome data.
• This research platform makes use of the cloud of the German National Bioinformatics Initiative (de.NBI), which is funded by the Federal Ministry of Education and Research. The federated de.NBI cloud offers the largest academic cloud infrastructure for German life scientists.
• One challenge will be to connect the platform to other research or health domains via cloud and edge technologies and to integrate the project into international projects.

What added value does the "GAIA-X project" offer?

• The project enables secure and DSGVO-compliant access to data of different actors in the health care system through centralised checks of the corresponding GAIA-X nodes.
• The possibility of integrating providers of powerful (infrastructure) components and high-performance calculation and analysis functions into the GAIA-X network, as well as their accessibility for different users, promises time, cost and efficiency advantages through the use of scaling effects.
• The openness and the resulting flexibility enable the connection of existing (data) platforms to further research and health domains and international initiatives. The simple and well-proven access will enable even greater use of the de.NBI cloud in the future, for example, in connection with future funding projects based on the GAIA-X architecture.
• With its ability to integrate data across individual domains (e.g. image data, clinical information), the GAIA-X network offers the potential to realise more complex integrative analyses within personalised medicine for the benefit of patients.

Use Case Team

• Christian Lawerenz – Berlin Institute of Health and Charité – University Medicine Berlin
• Prof. Dr. Roland Eils – Berlin Institute of Health and Charité – University Medicine Berlin
• Jürgen Eils – Berlin Institute of Health and Charité – University Medicine Berlin
• Prof. Dr. Peter Lichter – German Cancer Research Center
• Dr. Ivo Buchhalter – German Cancer Research Center