Project: BioNT

BioNT: The Bio Network for Training

BioNT is an international consortium dedicated to providing high-quality training and fostering a community for digital skills in the biotechnology and biomedical sectors. The project's training model is built on three core missions:

1. Curriculum Delivery:
   • To offer high-quality courses within two complementary curricula: Basic and Advanced curricula. These courses aim to improve the basic digital skills of staff and job seekers in the healthcare and biotechnology fields.
2. Community Impact:
   • To benefit not only course participants but also their wider communities. This includes supporting the development of a foundational level of digital intensity within SMEs and businesses across the focus sectors.
3. Sustainability:
   • To ensure the longevity of the community and its activities beyond the project's duration. This is achieved through the empowerment of individuals involved and their business-specific, sector-specific, and language-specific communities. By managing the training content in a FAIR (Findable, Accessible, Interoperable, Reusable) way, the project will use collaborative methods (like social coding) to build communities around the program, thus ensuring the pedagogical content is sustainably maintained.

The consortium comprises nine partners: six academic institutions and three Small and Medium enterprises (SMEs).

1. University of Oslo (Norway)
2. European Molecular Biology Laboratory, project coordinator (Germany)
3. ZB MED (Germany)
4. ?cole polytechnique f¨¦d¨¦rale de Lausanne (Switzerland)
5. University of Barcelona (Spain)
6. Albert-Ludwigs-Universit?t Freiburg (Germany)
7. RIcapacity (Germany)
8. BioByte (Germany)
9. HPCNow! (Spain)

Duration

• 1 January 2023 - 30 June 2026

Project results

BioNT has developed multiple training courses on digital skills (see list below). Materials for the courses and information about each course can be found here: BioNT- Training

• Basic curriculum
  • A practical introduction to bioinformatics and RNA-seq using Galaxy
  • Introduction to programming languages
  • Command line and cluster computing
  • Open and Fair, data management
• Advanced curriculum
  • Software Best Practices
  • Machine learning of Biological Data
  • System administration for HPC

University of Oslo contributions

• Served as resource persons and in organizational capacities, contributing to both basic and advanced curricula.
• Main organiser of the "Machine learning for Biological Data" course.
• Provided high-performance computational resources for the "Machine learning for Biological Data" course through the Norwegian AI Cloud (NAIC).

Contact

• Sabry Razick
• Pubudu Samarakoon

Coordinator:

• European Molecular Biology Laboratory
• Contact:
  • EMBL, Meyerhofstr. 1, 69126 Heidelberg, Germany
  • contact@biont-training.eu

Funding

This project is co-funded by the EU Digital Europe program, grant agreement number 101100604. Views and opinions expressed on this page are however those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

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