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Adding new dataset CHAMMI-75
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datasets/chammi.yaml

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Name: CHAMMI-75
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Description: |
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Quantifying cell morphology using images and machine learning models has proven to be a powerful tool to study the response of cells to treatments.
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However, the models used to quantify cellular morphology are typically trained with a single microscopy imaging type and under controlled experimental conditions.
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This results in specialized models that cannot be reused across biological studies because the technical specifications do not match (e.g., different number of channels),
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or because the target experimental conditions are out of distribution. We have created CHAMMI-75, a large-scale dataset containing 2.8 million multi-channel,
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high-resolution images curated from 75 diverse, publicly available biological studies. This dataset is useful to investigate and develop channel-adaptive models,
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which could process microscopy images of varying technical specifications and regardless of the number of channels. By breaking the limitations of existing models,
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CHAMMI-75 is an invaluable resource for creating the next generation of foundation models for image-based biological research.
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Documentation: https://github.com/CaicedoLab/CHAMMI-75
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Contact: Juan Caicedo, [email protected]
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ManagedBy: Morgridge Institute for Research
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UpdateFrequency: Every 2 years
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Tags:
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- microscopy
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- machine learning
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- biology
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- life sciences
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- imaging
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- high-throughput imaging
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- cell imaging
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- fluorescence imaging
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- aws-pds
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License: CC BY 4.0 License
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Citation:
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Resources:
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- Description: "CHAMMI-75 Dataset: Images, training set and evaluation set available in an S3 bucket"
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ARN: arn:aws:s3:::chammi-data
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Region: us-west-2
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Type: S3 Bucket
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DataAtWork:
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Tutorials:
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- Title: "Get To Know A Dataset: CHAMMI-75"
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URL: https://github.com/CaicedoLab/CHAMMI-75/blob/main/aws-tutorials/
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NotebookURL: https://github.com/CaicedoLab/CHAMMI-75/blob/main/aws-tutorials/get-to-know-a-dataset-template.ipynb
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AuthorName: Vidit Agrawal, Juan Caicedo
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- Title: Running CHAMMI-75 Evaluation Benchmarks
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URL: https://github.com/CaicedoLab/CHAMMI-75/blob/main/aws-tutorials/
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NotebookURL: https://github.com/CaicedoLab/CHAMMI-75/blob/main/aws-tutorials/running-benchmarks.ipynb
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AuthorName: Vidit Agrawal, Juan Caicedo
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Tools & Applications:
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- Title: CHAMMI-75 Source Code
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URL: https://github.com/CaicedoLab/CHAMMI-75
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AuthorName: Vidit Agrawal
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- Title: CHAMMI Benchmarking Source Code
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URL: https://github.com/chaudatascience/channel_adaptive_models
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AuthorName: Chau Pham
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Publications:
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- Title: "CHAMMI: A benchmark for channel-adaptive models in microscopy imaging"
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URL: https://neurips.cc/virtual/2023/poster/73620
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AuthorName: Zitong Sam Chen, Chau Pham, Siqi Wang, Michael Doron, Nikita Moshkov, Bryan Plummer, Juan C. Caicedo
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ADXCategories:
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- Healthcare & Life Sciences Data

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