Image-Analysis-Hub/Pasteur-BioImage-Analysis-Course-2025
May 2025 – May 2025
1 Month active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
Bioimage AnalysisBioinformaticsCell SegmentationData AnalysisData VisualizationDocumentation
aliceblondel
PROFILE
Aliceblondel
Alice Blondel developed the RNA2seg notebook workflow for the Image-Analysis-Hub/Pasteur-BioImage-Analysis-Course-2025 repository, focusing on scalable cell segmentation in large biological images with an emphasis on spatial transcriptomics. She implemented a five-step workflow using Python and Jupyter Notebooks, integrating machine learning techniques for segmentation and data analysis. Her work addressed core development, improved documentation, and enhanced parameter tuning to support reproducibility and teaching scenarios. Alice also resolved a bug related to placeholder path and alignment, ensuring correct data handling and visualization. The depth of her contributions reflects a strong grasp of bioimage analysis, technical writing, and data visualization best practices.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
2
Lines of code
1,767
Activity Months1
Work History
May 2025
6 Commits • 2 Features
May 1, 2025Summary for 2025-05 (Image-Analysis-Hub/Pasteur-BioImage-Analysis-Course-2025): Delivered a robust RNA2seg notebook workflow enabling scalable cell segmentation in large biological images with spatial transcriptomics focus, with improvements to reliability, documentation, and performance metrics. Implemented core notebook development and usage workflow, fixed a placeholder path and alignment issue, and enhanced documentation and parameter tuning to support reproducibility and teaching use-cases. Major bug fix addressed placeholder path and text alignment to ensure correct data paths and improved visualization.
6 Commits • 2 Features
May 1, 2025Summary for 2025-05 (Image-Analysis-Hub/Pasteur-BioImage-Analysis-Course-2025): Delivered a robust RNA2seg notebook workflow enabling scalable cell segmentation in large biological images with spatial transcriptomics focus, with improvements to reliability, documentation, and performance metrics. Implemented core notebook development and usage workflow, fixed a placeholder path and alignment issue, and enhanced documentation and parameter tuning to support reproducibility and teaching use-cases. Major bug fix addressed placeholder path and text alignment to ensure correct data paths and improved visualization.
May 2025
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture80.0%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
Bioimage AnalysisBioinformaticsCell SegmentationData AnalysisData VisualizationDocumentationJupyter NotebooksMachine LearningPython ScriptingSpatial TranscriptomicsTechnical WritingZarr Data Handling
Repositories Contributed To
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