
Contributed to the BiodataAnalysisGroup/BioHackathon repository by developing a Python-based data extraction script that interacts with the KnockTF API to automate retrieval and processing of gene data, outputting results in CSV format for downstream analysis. Leveraged skills in web scraping, command line interface design, and data processing to streamline gene search and dataset identification. Additionally, created Dockerfiles to containerize the SCENIC+ workflow, ensuring reproducible Python environments and simplifying dependency management with Docker and Shell scripting. These efforts reduced manual data preparation, improved reproducibility, and enhanced onboarding and collaboration for future research and validation cycles within the project.
Concise monthly summary for 2024-11 focusing on delivering data extraction and reproducible deployment capabilities for the BioHackathon project, with emphasis on business value, technical achievements, and future readiness.
Concise monthly summary for 2024-11 focusing on delivering data extraction and reproducible deployment capabilities for the BioHackathon project, with emphasis on business value, technical achievements, and future readiness.

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