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A framework for benchmarking single-cell machine learning models

Project description

CZ Benchmarks

What is cz-benchmarks?

cz-benchmarks is a package for standardized evaluation and comparison of machine learning models for biological applications (first, in the single-cell transcriptomics domain, with future plans to expand to additional domains). The package provides a toolkit for running containerized models, executing biologically-relevant tasks, and computing performance metrics. We see this tool as a step towards ensuring that large-scale ML Models can be harnessed to deliver genuine biological insights -- by building trust, accelerating development, and bridging the gap between ML and biology communities.

Why benchmarking? Why now?

Last year, CZI hosted a workshop focused on benchmarking and evaluation of ML Models in biology, and the insights gained have reinforced our commitment to supporting the development of a robust benchmarking infrastructure, which we see as critical to achieving our Virtual Cell vision.

💬 Community Feedback & Contributions

We're working to get the alpha version of cz-benchmarks stable to build with the community. In the meantime, for issues you may identify, feel free to open an issue on GitHub or reach out to us at virtualcellmodels@chanzuckerberg.com.

Getting Started

To get started with cz-benchmarks, refer to the Quick Start Guide.

📚 Additional Resources

📖 Documentation: The full documentation is available at cz-benchmarks

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