compbiozurich/UZH-BIO392
May 2026 – May 2026
1 Month active
Languages Used
Pythonpython
Technical Skills
PandasPythonbioinformaticsdata analysisdata visualizationmachine learning
FrancescoNocera
PROFILE
Francesconocera
Developed a CNV-based data analysis toolkit for the compbiozurich/UZH-BIO392 repository, enabling classification of glioblastoma versus colorectal carcinoma using CNV-derived features. Leveraging Python and Pandas, the work incorporated a survival analysis workflow utilizing Kaplan-Meier curves and Cox proportional hazards modeling to support patient stratification. The implementation included metadata merging and standardized folder naming based on ISO formats, enhancing reproducibility and data hygiene across analyses. Documentation and project structure were updated to reflect these changes, and a survival analysis script with presentation materials was added. This work established a robust foundation for CNV-driven research and downstream bioinformatics analyses.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
18,043
Activity Months1
Your Network
27 peopleShared Repositories
27
Work History
May 2026
2 Commits • 1 Features
May 1, 2026Monthly summary for 2026-05: Implemented the CNV-based data analysis toolkit in compbiozurich/UZH-BIO392, enabling CNV-derived feature classification to distinguish glioblastoma from colorectal carcinoma, plus a survival analysis workflow using Kaplan-Meier curves and Cox proportional hazards modeling. Added metadata merging and standardized folder naming to ISO format to improve reproducibility and data hygiene. These changes lay groundwork for CNV-driven patient stratification and robust downstream analyses. Commit activity included: 278ac112e16f3189937af5e7234a8669d21e44fe (finished all stuff) and b5ab96af0c90ccd91e486b56613a2734bf9feffb (added survival analysis script and presentation, changed foldernames to ISO).
2 Commits • 1 Features
May 1, 2026Monthly summary for 2026-05: Implemented the CNV-based data analysis toolkit in compbiozurich/UZH-BIO392, enabling CNV-derived feature classification to distinguish glioblastoma from colorectal carcinoma, plus a survival analysis workflow using Kaplan-Meier curves and Cox proportional hazards modeling. Added metadata merging and standardized folder naming to ISO format to improve reproducibility and data hygiene. These changes lay groundwork for CNV-driven patient stratification and robust downstream analyses. Commit activity included: 278ac112e16f3189937af5e7234a8669d21e44fe (finished all stuff) and b5ab96af0c90ccd91e486b56613a2734bf9feffb (added survival analysis script and presentation, changed foldernames to ISO).
May 2026
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Pythonpython
Technical Skills
PandasPythonbioinformaticsdata analysisdata visualizationmachine learningsurvival analysis
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline