CovertLab/vEcoli
Oct 2024 – Nov 2024
2 Months active
Languages Used
Jupyter NotebookPythonJSON
Technical Skills
Data AnalysisData ProcessingData VisualizationMatplotlibPandasPolars
Cyrus
PROFILE
Cyrus
Over a two-month period, contributed to the CovertLab/vEcoli repository by developing an end-to-end metalloproteome workflow and delivering simulation workflow enhancements. Built data ingestion and analysis pipelines that process accession-to-gene mappings, quantify protein and metal abundance, and generate visualizations such as heatmaps and isotopic mappings to highlight proteins with unknown functions. Enhanced reproducibility and reduced manual data wrangling by providing ready-to-share Jupyter Notebooks and CSV outputs. Leveraged Python, Pandas, and Seaborn for data processing and visualization, and refactored simulation workflows to improve speed and accuracy. The work enabled faster, more accurate simulations and clearer data interpretation for researchers.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
3
Lines of code
8,491
Activity Months2
Your Network
8 peopleShared Repositories
8
Shu-FeatherMember
alberthqzhangMember
annabellefowlerMember
thalassemiaMember
Heena SaqibMember
mpg19Member
Mica YangMember
SilentDawnMember
Work History
November 2024
3 Commits • 2 Features
Nov 1, 2024November 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.
3 Commits • 2 Features
Nov 1, 2024November 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.
November 2024
October 2024
2 Commits • 1 Features
Oct 1, 2024Month: 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.
October 2024
2 Commits • 1 Features
Oct 1, 2024Month: 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
Loading activity data...
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
Overview of all repositories you've contributed to across your timeline