Published April 3, 2024 | Version v1
Dataset Open

AI4Life-MDC24 Challenge data: JUMP Cell Painting Datasets

  • 1. Broad Institute
  • 1. ROR icon Human Technopole
  • 2. The University of Birmingham
  • 3. University of Birmingham

Description

This is a subset of the cpg0016-jump dataset (Chandrasekaran et al., 2022), available from the Cell Painting Gallery on the Registry of Open Data on AWS (https://registry.opendata.aws/cellpainting-gallery/). 

The selected subset contains 517 images with four channels in the form of a single multi-channel tiff file. Gaussian noise is applied to each image to simulate the detector noise.

The GitHub repository with the details about the original dataset is available at https://github.com/jump-cellpainting/datasets. The preprint describing the original dataset is available on BioRxiv

AI4Life has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement number 101057970. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

 

Files

noisy.tiff

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Additional details

Related works

Is described by
Preprint: 10.1101/2023.03.23.534023 (DOI)

Funding

European Commission
Horizon Europe research and innovation programme 101057970