NVIDIA/bionemo-framework
Jun 2025 – Jun 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
BioinformaticsData VisualizationDeep LearningGene Expression AnalysisMachine LearningMatplotlib
jyin-bst
PROFILE
Jyin-bst
Developed and integrated a Geneformer-based gene embeddings calculation within the NVIDIA/bionemo-framework, enabling researchers to compute gene embeddings and construct gene co-expression networks for advanced gene-level analytics. The work introduced the bionemo.geneformer package and an accompanying Jupyter Notebook that demonstrates end-to-end extraction of gene embeddings and network construction. Implementation was carefully scoped to the geneformer module, reducing risk and simplifying future maintenance. Leveraging Python, PyTorch, and Pandas, the solution supports downstream network-based insights in bioinformatics research. This focused contribution enhanced the framework’s analytical capabilities, providing a robust foundation for gene expression analysis and data visualization within the existing ecosystem.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,632
Activity Months1
Your Network
22 peopleShared Repositories
22
Work History
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025: Implemented Geneformer-based gene embeddings calculation within the NVIDIA/bionemo-framework, enabling computation of gene embeddings and construction of a gene co-expression network. Introduced the bionemo.geneformer package and a companion notebook demonstrating end-to-end usage. Changes scoped to the geneformer module to minimize risk and simplify maintenance, following issue #808. This work enhances gene-level analytics capabilities and supports downstream network-based insights for researchers.
1 Commits • 1 Features
Jun 1, 2025June 2025: Implemented Geneformer-based gene embeddings calculation within the NVIDIA/bionemo-framework, enabling computation of gene embeddings and construction of a gene co-expression network. Introduced the bionemo.geneformer package and a companion notebook demonstrating end-to-end usage. Changes scoped to the geneformer module to minimize risk and simplify maintenance, following issue #808. This work enhances gene-level analytics capabilities and supports downstream network-based insights for researchers.
June 2025
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
BioinformaticsData VisualizationDeep LearningGene Expression AnalysisMachine LearningMatplotlibNetworkXPandasPyTorchPythonscikit-learn
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