Building and sustaining a Community of computational biologists at EMBL through Consulting, Training, and Infrastructure
Year: 2025
Type: article
Abstract: Collaboration is essential in computational biology, where interdisciplinary approaches drive innovation and address complex challenges. At the European Molecular Biology Laboratory (EMBL), the Data Science Internal Support (DaSIS) strengthens this collaboration through four key pillars: consulting, training, infrastructure, and community building.Consulting is central to our work, providing expert guidance on challenges ranging from statistical analysis and mathematical modeling to coding and project management. By connecting researchers with domain-specific experts across EMBL, we help facilitate impactful, collaborative projects.Training empowers researchers to thrive in a fast-evolving landscape. We offer hybrid workshops, self-paced resources, and focused sessions on topics like programming, visualization, and machine learning. Our approach balances accessibility with depth, helping scientists stay at the forefront of their fields.Robust infrastructure supports our mission. We maintain tools such as coding platforms, version control systems, and cloud-based environments tailored to bioinformatics. Combined with collaborative and communication platforms, these ensure seamless research workflows.Community unites these efforts. We foster engagement through meetups, clubs, and knowledge-sharing forums that encourage connection, collaboration, and lasting professional networks.While our work is rooted in life sciences, the challenges and strategies are relevant across disciplines. We share our approach at the Open Science Fair to promote broader dialogue on effective research support and to learn from others. Crucially, we advocate for research support as a vital, rewarding career in academia. By highlighting this work, we hope to inspire conversations about career development, institutional priorities, and how to better recognize and integrate support roles into the scientific ecosystem.
Authors: Paladin, Lisanna, Paredes-Cisneros, Isabela, Alves, Renato, Geissen, Eva-Maria, Kaspar, Sarah, Miranda, Jacobo
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7105912601
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