compbiozurich/UZH-BIO392
Apr 2026 – May 2026
2 Months active
Languages Used
MarkdownPythonR
Technical Skills
JupyterJupyter NotebookPandasR programmingbioinformaticsdata analysis
Emily Mosberger
PROFILE
Emily Mosberger
Developed a suite of genomics data analysis and training materials for the compbiozurich/UZH-BIO392 repository, focusing on reproducible research and educational workflows. Delivered feature-rich Jupyter and R notebooks covering sequence alignment, variant calling, population structure analysis, and CNV frequency analysis for cancer datasets. Applied Python, R programming, and Pandas to enable hands-on exploration, machine learning preparation, and survival analysis using real-world data. Enhanced project maintainability by restructuring educational content, streamlining folder organization, and removing outdated materials. Emphasized clear documentation and version control, resulting in ready-to-run resources that support both teaching and research in bioinformatics and data science.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
11Total
Bugs
0
Commits
11
Features
6
Lines of code
1,256,367
Activity Months2
Your Network
27 peopleShared Repositories
27
Work History
May 2026
7 Commits • 2 Features
May 1, 2026May 2026 performance summary for compbiozurich/UZH-BIO392: Delivered structured CNV data analysis training materials and a survival analysis notebook, and completed comprehensive content restructuring to streamline educational materials. The work enhances learner onboarding, reproducibility, and maintainability, delivering tangible business value by providing ready-to-use resources and a cleaner project structure. Technical achievements include notebook-based survival analysis with Progenetix CNV data and disciplined folder-structure harmonization.
7 Commits • 2 Features
May 1, 2026May 2026 performance summary for compbiozurich/UZH-BIO392: Delivered structured CNV data analysis training materials and a survival analysis notebook, and completed comprehensive content restructuring to streamline educational materials. The work enhances learner onboarding, reproducibility, and maintainability, delivering tangible business value by providing ready-to-use resources and a cleaner project structure. Technical achievements include notebook-based survival analysis with Progenetix CNV data and disciplined folder-structure harmonization.
May 2026
April 2026
4 Commits • 4 Features
Apr 1, 2026Monthly summary for 2026-04: Delivered a cohesive set of feature-rich notebooks and documentation for compbiozurich/UZH-BIO392, enabling hands-on genomics data exploration, analysis workflows, and reproducible research practices. The work aligns with course objectives, enhances data literacy, and provides ready-to-run pipelines for teaching and research.
April 2026
4 Commits • 4 Features
Apr 1, 2026Monthly summary for 2026-04: Delivered a cohesive set of feature-rich notebooks and documentation for compbiozurich/UZH-BIO392, enabling hands-on genomics data exploration, analysis workflows, and reproducible research practices. The work aligns with course objectives, enhances data literacy, and provides ready-to-run pipelines for teaching and research.
Activity
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Quality Metrics
Correctness100.0%
Maintainability92.8%
Architecture98.2%
Performance92.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonR
Technical Skills
JupyterJupyter NotebookMatplotlibPandasPythonR programmingbioinformaticsdata analysisdata visualizationgenomicsmachine learningstatistical analysissurvival analysisvariant calling
Repositories Contributed To
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