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Cyrus

PROFILE

Cyrus

Cyrus developed and refined data analysis workflows for the CovertLab/vEcoli repository, focusing on metalloproteome data ingestion, simulation, and visualization. Over two months, he delivered an end-to-end pipeline that processes accession-to-gene mappings, analyzes protein and metal abundance, and generates ready-to-share visualizations, including heatmaps and isotopic mappings. Using Python, Pandas, and Seaborn, he automated data wrangling and enhanced reproducibility through Jupyter Notebooks. His work included simulation workflow improvements for faster, more accurate results and new visualizations for cofactor contributions. The solutions reduced manual data handling, improved analytics readiness, and provided researchers with actionable insights for metalloproteome discovery.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

5Total
Bugs
0
Commits
5
Features
3
Lines of code
8,491
Activity Months2

Work History

November 2024

3 Commits • 2 Features

Nov 1, 2024

November 2024 (CovertLab/vEcoli): Delivered two major feature developments with notable business value and improved reliability. Key features delivered include simulation workflow refinements and analysis notebook updates, plus cofactor contribution visualization. No major bugs fixed this month. Overall impact centers on faster, more accurate simulations and clearer data interpretation, supported by reproducible notebooks and data pipelines. Technologies demonstrated include Python data wrangling, plotting, and notebook automation; workflow refactoring to improve performance and analytics readiness.

October 2024

2 Commits • 1 Features

Oct 1, 2024

Month: 2024-10 — Delivered an end-to-end Metalloproteome workflow for CovertLab/vEcoli, enabling ingestion of accession-to-gene mappings, analysis of protein and metal abundance, and visualization. The work produced a data CSV for mapping, a Jupyter Notebook for processing and joining data with experimental conversion tables, and plotting enhancements (heatmaps and isotopic mappings) to surface proteins with unknown functions and accelerate metalloproteome discovery for researchers and decision-makers. This pipeline improves reproducibility, reduces manual data wrangling, and strengthens decision support by delivering ready-to-share visualizations and insights to stakeholders.

Activity

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Quality Metrics

Correctness80.0%
Maintainability80.0%
Architecture72.0%
Performance76.0%
AI Usage28.0%

Skills & Technologies

Programming Languages

JSONJupyter NotebookPython

Technical Skills

Data AnalysisData ManipulationData ProcessingData VisualizationJuliaMatplotlibPandasPolarsPythonScientific ComputingSeabornSimulation

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

CovertLab/vEcoli

Oct 2024 Nov 2024
2 Months active

Languages Used

Jupyter NotebookPythonJSON

Technical Skills

Data AnalysisData ProcessingData VisualizationMatplotlibPandasPolars

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