Modular training resources for bioimage analysis

Modern microscopy enables us to measure structural and dynamical properties of many biological processes and is therefore an indispensable research tool. However, the amount and complexity of the produced imaging data is steadily increasing. Thus, handling the data as well as reproducibly and automatically extracting accurate scientific information require dedicated 'bioimage analysis' expertise. To facilitate the dissemination of this ubiquitously required expertise we developed an open-access bioimage analysis training resource. The resource is designed to help trainers to design and run courses on bioimage analysis for life scientists. The material is modular where each module covers one concise topic and provides corresponding activities using microscopy images from biological samples. The activities can be executed using various popular software packages (e.g. ImageJ, Python). The material is hosted on a public software repository allowing the bioimaging community to readily contribute new training modules or improve existing modules. Within the last 3 years, the material has been used by several trainers in numerous courses and continuously improved.

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Publication Details

Journal
Journal of Microscopy
Published
2026-06-18
DOI
https://doi.org/10.1111/jmi.70133
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
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article

Modular training resources for bioimage analysis

T. Mark Hodges, Elnaz Fazeli, Sebastián González-Tirado, Antonio Z. Politi et al.
Journal of Microscopy
Cell Image Analysis Techniques
article

Modular training resources for bioimage analysis

T. Mark Hodges, Elnaz Fazeli, Sebastián González-Tirado, Antonio Z. Politi, Stefania Marcotti, Aliaksandr Halavatyi, Tim-Oliver Buchholz, Md. Arif Khan, F Schneider, Anniek Stokkermans, Nicola Gritti, Dominik Kutra, Christian Tischer, Martin Schorb, Julian Hennies, Yi Sun, Bugra Oezdemir, Nima Vakili
article en

Abstract

Modern microscopy enables us to measure structural and dynamical properties of many biological processes and is therefore an indispensable research tool. However, the amount and complexity of the produced imaging data is steadily increasing. Thus, handling the data as well as reproducibly and automatically extracting accurate scientific information require dedicated 'bioimage analysis' expertise. To facilitate the dissemination of this ubiquitously required expertise we developed an open-access bioimage analysis training resource. The resource is designed to help trainers to design and run courses on bioimage analysis for life scientists. The material is modular where each module covers one concise topic and provides corresponding activities using microscopy images from biological samples. The activities can be executed using various popular software packages (e.g. ImageJ, Python). The material is hosted on a public software repository allowing the bioimaging community to readily contribute new training modules or improve existing modules. Within the last 3 years, the material has been used by several trainers in numerous courses and continuously improved.

Journal of Microscopy
European Molecular Biology Organization (DE), University of Helsinki (FI), King's College London (GB), Heidelberg University (DE), European Molecular Biology Laboratory (ES), Friedrich Miescher Institute (CH), Hubrecht Institute for Developmental Biology and Stem Cell Research (NL), Community Initiatives (US), Max Planck Institute of Experimental Medicine (DE), European Molecular Biology Laboratory (DE), European Molecular Biology Laboratory (DE), BioMed X Institute (DE)
Openalex Percentile: Top 6%
Cell Image Analysis Techniques
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