Jacques Bourg developed a notebook-driven analysis workflow for the Pasteur-BioImage-Analysis-Course-2025 repository, focusing on end-to-end exercises for bioimage analysis and quantitative gene expression. He implemented V1 notebooks featuring N1 workflows and spot detection, integrated Napari for raw data visualization, and added BigFish pipeline imagery to enhance data inspection. Using Python, Jupyter Notebook, and the Bigfish library, Jacques introduced semi-automatic spot detection with SNR calculations and a uFish detection script, expanding analytical capabilities. He also refactored the codebase, improved documentation, and reorganized assets, resulting in a more maintainable, accessible, and release-ready repository for both learners and contributors.
May 2025 delivered a notebook-first analysis flow and broad repository hygiene improvements for the Pasteur-BioImage-Analysis-Course-2025 project. Key work established end-to-end, notebook-driven exercises with V1 notebooks, including the N1 workflow and spot detection, plus a second notebook with assets and tests to accelerate learner setup. Added Napari raw data viewing and BigFish pipeline imagery, enabling direct, visual data inspection and richer demonstrations. Implemented semi-automatic spot detection with SNR calculations and introduced a uFish detection script, expanding quantitative analysis capabilities. Completed extensive repo cleanup and documentation updates (refactor, README, colocalization notes, folder organization, data scaffolding, presegmented data, and UI tweaks) to improve maintainability, onboarding, and release preparedness.
May 2025 delivered a notebook-first analysis flow and broad repository hygiene improvements for the Pasteur-BioImage-Analysis-Course-2025 project. Key work established end-to-end, notebook-driven exercises with V1 notebooks, including the N1 workflow and spot detection, plus a second notebook with assets and tests to accelerate learner setup. Added Napari raw data viewing and BigFish pipeline imagery, enabling direct, visual data inspection and richer demonstrations. Implemented semi-automatic spot detection with SNR calculations and introduced a uFish detection script, expanding quantitative analysis capabilities. Completed extensive repo cleanup and documentation updates (refactor, README, colocalization notes, folder organization, data scaffolding, presegmented data, and UI tweaks) to improve maintainability, onboarding, and release preparedness.
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