Is HPC for you? A collective perspective on adopting high‐performance computing for bioimage analysis in imaging facilities
Biomedical sciences use various imaging technologies and bioimage analysis has become data-intensive, often requiring resources that exceed those available on personal laptop computers or workstations. High-performance computing (HPC) can solve most of the problems connected to the data burden of modern bioimaging, offering scalable and reliable computational resources. However, most of the biomedical researchers and core facility staff might lack the required expertise and knowledge to fully leverage the capabilities of HPC. In this work, we aim to eliminate misconceptions about the use of HPC and highlight how researchers with no coding skills can use HPC tools to scale up their bioimage analysis workflows. The promotion of HPC software solutions is a duty of research support technologists, but their deployment can benefit both core facility staff and digital research infrastructure teams, helping to speed up the implementation of bioimage analysis workflows. In summary, we showcase how HPC offers helpful solutions to meet the growing computational demands that imaging facilities are facing today.
Authors
- Chiara Rossi (ORCID: https://orcid.org/0000-0002-0992-8054)
- Rocco D’Antuono (ORCID: https://orcid.org/0000-0003-0180-6500)
- Benjamin Pavie (ORCID: https://orcid.org/0000-0002-0249-3844)
- Marie Held (ORCID: https://orcid.org/0000-0003-0118-5898)
- Paul A. Wilkinson (ORCID: https://orcid.org/0000-0002-8836-5439)
- Konstantin B. Borisenko (ORCID: https://orcid.org/0000-0002-2368-4500)
- Tatiana Marianne Woller (ORCID: https://orcid.org/0000-0002-6958-6498)
- Marco Marcello (ORCID: https://orcid.org/0000-0002-2392-8640)
- Sebastian Munck (ORCID: https://orcid.org/0000-0002-5182-5358)
- Andrew Collins (ORCID: https://orcid.org/0000-0003-0507-6912)
Institutions
- University of Liverpool (GB)
- The Francis Crick Institute (GB)
- Vlaams Instituut voor Biotechnologie (BE)
- University of Reading (GB)
- KU Leuven (BE)
Publication Details
- Journal
- Journal of Microscopy
- Published
- 2026-10-30
- DOI
- https://doi.org/10.1111/jmi.70198
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Wellcome Trust
- Cancer Research UK
- University of Liverpool
- Fonds Wetenschappelijk Onderzoek
- Medical Research Council