Our mission

Knowledge transfer

Our goal is to promote the adoption of high-quality and state-of-the-art data science in every laboratory. We do not see ourselves as a generic “pay-as-you-go” facility; rather, we want to empower each research group directly. Our mission is to support PhD students and postdocs embedded in wet labs by training them in specific data science methods, pointing them to relevant datasets, and ensuring that, while they may not become full-fledged experts, they will gain the skills to confidently integrate data science into their work, adopt best practices, and enjoy the process.

Ultimately, researchers should leave as more independent scientists, fully equipped to thrive in their own projects.

Valorisation of Open Research Data

Data is one of the greatest assets of any laboratory, but its true potential emerges when datasets are shared and combined.

Our activities will include:

  • Curating, annotating, and cataloging datasets to avoid duplication

  • Sharing raw and processed data, as well as code and pipelines

  • Reducing redundancy, saving computational costs, and boosting efficiency

Through these practices, researchers will be able to identify key datasets, generate pilot data, and accelerate their studies. Together, we can foster rigor, transparency, and reuse, which drives scientific discovery.

We aim to cultivate a robust culture of data sharing and reuse at the university. We already know how to leverage such practices for new deep learning models. Beyond sharing raw data, we aim to share code, pre-processed datasets, and pipelines, reducing duplication, saving computing costs, and increasing efficiency.

We will set up catalogs of data, enabling researchers to identify key datasets to generate pilot data. We will increase the value of such data (in particular multimodal and temporal datasets) by building foundation models that address real-world questions, capitalizing on the expertise of the Luisier lab researchers, and placing the Faculty of Medicine of Bern or even Bern University as a generator of knowledge and models that serve the scientific community at large.

Together, we can build a culture of rigor, transparency, and reuse of data that will accelerate scientific discovery.

Uniting the UniBE Community

Disruptive science arises from exposure to diverse questions, challenges, datasets, and technologies. Achieving this requires open exchange and opportunities for collaboration.

To build such an environment, we will:

  • Host recurring in-person meetings, with keynote presentations followed by informal presentations, discussions of ongoing projects, and brainstorming

  • Develop catalogs of expertise across labs and faculties, helping scientists identify potential collaborators

  • Engage with bioinformaticians across the university

  • Collaborate with Core facilities

This initiative will help build a strong local community, encourage collaborations, and make connections across disciplines.

Swiss community: a Network of Competence in Biomedical Data Science

Switzerland is small, but expertise is distributed across many institutions. To avoid duplication of effort and maximize impact, we will facilitate national-level collaboration in biomedical data science.

We are already connected with EPFL AI Center, SIB Swiss Institute of Bioinformatics, NCCR RNA & Disease, and are developing collaborations with the Vision Center in Zurich. Our mission is to bring these communities together and foster interaction between academia and industry. We will establish a national Biological Data Science Symposium rotating annually between Zurich, Lausanne, Geneva, and Bern.

In the long run, we envisage an officially recognized Network of Competence in Biomedical Data Science, which will facilitate research funding and foster international visibility.

This initiative will connect academics and industries at the country level and gain international visibility