Cell Painting Gallery
Data and Resources
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Cell Painting Gallery
The Cell Painting Gallery is a collection of light microscopy images of...
Additional Info
| Field | Value |
|---|---|
| Last Updated | March 19, 2026, 18:20 (UTC) |
| Created | March 19, 2026, 18:20 (UTC) |
| accessRights | <p>open</p> |
| columnDataDict | Harmonized metadata columns are: {'File Path':'S3 Path for image file', 'File Name': 'Name of image file', 'Source': 'Data source', 'Batch': 'Data batch', 'Plate': 'Plate name', 'Well': 'Well name', 'Site': 'Site number', 'Plate_Size': 'Number of wells in multiwell plate', 'CP_Version': 'Version of the Cell Painting Assay', 'DOI_to_Cite': 'DOI to cite when using data', 'Year_Imaged': 'Year of image acquisition', 'Cell_Line_Name': 'Name of the cell line, if named', 'Cell_Line_Type': 'Cell type', 'Cell_Line_Modification': 'Line modifications (clone selection, Cas9 overexpression, etc.)', 'Label_Fluorophore': 'Fluorophore conjugated to reagent or dye variant', 'Label_Mechanism': 'Mechanism of labeling reagent', 'Label_Molecule': 'Molecule targeted by the label', 'Label_Reagent': 'Reagent used to label sample in image', 'Label_Structure': 'Expected structure that is labeled in image', 'Treatment_Primary_Treatment': 'Perturbation applied to cells, common name', 'Treatment_Broad_Sample': 'Perturbation applied to cells, Broad Sample ID', 'Treatment_Concentration': 'Concentration if chemical perturbation', 'Treatment_InChIKey': 'Perturbation applied to cells, InChiKey representation', 'Treatment_Mechanism': 'Annotation about mechanism of treatment', 'Treatment_PubChem_CID': 'Perturbation applied to cells, PubChem Cid', 'Treatment_SMILES': 'Perturbation applied to cells, SMILES representation', 'Treatment_Solvent': 'Solvent if chemical perturbation', 'Treatment_Secondary_Treatment': 'Secondary treatment applied to cells, if present', 'Treatment_Category': 'Treatment is compound, ORF, or CRISPR', 'Treatment_Control_Class': 'Treatment is an experimental variable or a control', 'Microscope_Name': 'Microscope manufacturer and type', 'Microscope_Binning': 'Binning of the microscope', 'Microscope_Modality': 'Microscope modality', 'Microscope_Objective_Magnification': 'Magnification of the microscope objective', 'Microscope_Objective_NA': 'Numerical aperture of the microscope objective', 'Microscope_Pixel_Size': 'Size of a pixel in microns', 'Microscope_Excitation_Peak': 'Excitation peak of the microscope channel imaged', 'Microscope_Excitation_Width': 'Excitation width of the microscope channel imaged', 'Microscope_Emission_Peak': 'Emission peak of the microscope channel imaged', 'Microscope_Emission_Width': 'Emisison width of the microscope channel imaged', 'Image_Bit_Depth': 'Bit depth of the image', 'Image_Position_Z': 'Relative Z-plane of the image', 'Image_Size_X': 'Image size in pixels, X dimension', 'Image_Size_Y': 'Image size in pixels, Y dimension', 'Timepoint_Primary_Treatment': 'Time in hours since primary treatment', 'Timepoint_Secondary_Treatment': 'Time in hours since secondary treatment', 'Timepoint_Acquisition': 'For data with time dimension, time in hours since start of acquisition'} |
| creationMethod | <p><span style="color: rgb(0, 0, 0);">Each dataset within the CPG has its own publication/provenance.</span></p> |
| creatorEmail | |
| creatorName | |
| dataAuthType | public |
| dataType | .tif, .csv, .parquet |
| datasetPageUrl | https://broadinstitute.github.io/cellpainting-gallery/overview.html |
| docsURL | https://broadinstitute.github.io/cellpainting-gallery/ |
| doi | 10.1038/s41592-024-02399-z |
| issueDate | 2024-09-02 |
| lang | en |
| lastUpdateDate | 2026-03-19 |
| license | cc0 |
| ndp_creator_md5 | 1e087fd2ef07452db2e29a65fd0bfbd2 |
| pocEmail | eweisbar@broadinstitute.org |
| pocName | Erin Weisbart |
| publisherEmail | |
| publisherName | |
| status | submitted |
| theme | [] |
| updateFreq | monthly |
| uploadType | dataset |
| usageInfo | <p><span style="color: rgb(0, 0, 0);">Because the CPG is a collection of similar datasets, each with multiple data types (e.g. images, segmented objects, raw features, processed profiles), researchers can parse the Gallery in a variety of ways (e.g. accessing a single or multiple datasets, a single or multiple data types within the dataset/s, similar or diverse data within or across datasets). This enables the data to be used at a diversity of scales - small subsets for classroom training or large collections of datasets for experienced researchers. This also enables the data to be used for very diverse applications from image analysis through data analysis. The Cell Painting Gallery supports many potential AI use cases including computer vision/deep learning for biological image analysis, representation learning, explainable AI, style transfer, and multimodal learning combining images with numerical data.</span></p> |