id: "doi:10.18130/V3/B35XWX"
name: CM4AI March 2025 Data Release (Beta)
title: Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
description: >
  March 2025 Data Release of Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org),
  the Functional Genomics Grand Challenge in the NIH Bridge2AI program. This Beta release
  includes: (a) perturb-seq data in undifferentiated KOLF2.1J iPSCs; (b) SEC-MS data in
  undifferentiated KOLF2.1J iPSCs and iPSC-derived NPCs, neurons, and cardiomyocytes;
  and (c) immunofluorescence (IF) subcellular imaging in MDA-MB-468 breast cancer cells
  under untreated and chemotherapy (vorinostat and paclitaxel) conditions. CM4AI output
  data are packaged with provenance graphs and rich metadata as AI-ready datasets in
  RO-Crate format using the FAIRSCAPE framework. Data will be augmented regularly through
  the end of the project. Collaboration includes UCSD, UCSF, Stanford, UVA, Yale, UA
  Birmingham, Simon Fraser University, and the Hastings Center.
same_as:
  - https://doi.org/10.18130/V3/B35XWX
purposes:
  - response: Provide AI-ready, FAIR data products in functional genomics and cell mapping to support machine learning research.
tasks:
  - response: Single-cell perturb-seq analysis and modeling of gene function and fitness phenotypes.
  - response: Protein complex inference and PPI network analysis from SEC-MS profiles.
  - response: Subcellular protein localization analysis and ML benchmarking from IF images; drug response phenotyping.
creators:
  - name: Clark, T
    affiliation: University of Virginia
    id: "https://orcid.org/0000-0003-4060-7360"
  - name: Parker, J
    affiliation: University of California, San Diego
    id: "https://orcid.org/0000-0003-4535-3486"
  - name: Al Manir, S
    affiliation: University of Virginia
    id: "https://orcid.org/0000-0003-4647-3877"
  - name: Axelsson, U
    affiliation: KTH Royal Institute of Technology
  - name: Ballllosero Navarro, F
    affiliation: Stanford University
    id: "https://orcid.org/0000-0002-4180-422X"
  - name: Chinn, B
    affiliation: University of California San Diego
  - name: Churas, C P
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0001-9998-705X"
  - name: Dailamy, A
    affiliation: University of California, San Diego
    id: "https://orcid.org/0000-0002-6711-8260"
  - name: Doctor, Y
    affiliation: University of California, San Diego
    id: "https://orcid.org/0009-0009-0483-7506"
  - name: Fall, J
    affiliation: KTH - Royal Institute of Technology
  - name: Forget, A
    affiliation: University of California San Francisco
    id: "https://orcid.org/0000-0003-0223-0312"
  - name: Gao, J
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0002-6311-3526"
  - name: Hansen, J N
    affiliation: Stanford University
    id: "https://orcid.org/0000-0002-4650-9094"
  - name: Hu, M
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0002-1571-8029"
  - name: Johannesson, A
    affiliation: KTH - Royal Institute of Technology
  - name: Khaliq, H
    affiliation: University of California San Diego
  - name: Lee, Y H
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0003-0917-355X"
  - name: Lenkiewicz, J
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0001-7252-8638"
  - name: Levinson, M A
    affiliation: University of Virginia
    id: "https://orcid.org/0000-0003-0384-8499"
  - name: Marquez, C
    affiliation: University of California San Diego
  - name: Metallo, C
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0003-2404-3040"
  - name: Muralidharan, M
    affiliation: University of California San Francisco
  - name: Nourreddine, S
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0003-3881-7588"
  - name: Niestroy, J
    affiliation: University of Virginia
    id: "https://orcid.org/0000-0002-1103-3882"
  - name: Obernier, K
    affiliation: University of California San Francisco
    id: "https://orcid.org/0000-0002-4025-1299"
  - name: Pan, E
    affiliation: University of California San Diego
  - name: Polacco, B
    affiliation: University of California San Francisco
  - name: Pratt, D
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0002-1471-9513"
  - name: Qian, G
    affiliation: University of California San Diego
    id: "https://orcid.org/0009-0005-4217-2745"
  - name: Schaffer, L
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0001-6339-9141"
  - name: Sigaeva, A
    affiliation: KTH Royal Institute of Technology
    id: "https://orcid.org/0000-0003-3361-3797"
  - name: Thaker, S
    affiliation: University of Alabama at Birmingham
    id: "https://orcid.org/0000-0001-6730-2773"
  - name: Zhang, Y
    affiliation: University of California San Diego
  - name: Bélisle-Pipon, J C
    affiliation: Simon Fraser University
    id: "https://orcid.org/0000-0002-8965-8153"
  - name: Brandt, C
    affiliation: Yale University
    id: "https://orcid.org/0000-0001-8179-1796"
  - name: Chen, J Y
    affiliation: The University of Alabama at Birmingham
    id: "https://orcid.org/0000-0002-6112-415X"
  - name: Ding, Y
    affiliation: University of Texas at Austin
    id: "https://orcid.org/0000-0003-2567-2009"
  - name: Fodeh, S
    affiliation: Yale University
    id: "https://orcid.org/0000-0003-4664-3143"
  - name: Krogan, N
    affiliation: University of California San Francisco
    id: "https://orcid.org/0000-0003-4902-337X"
  - name: Lundberg, E
    affiliation: Stanford University
    id: "https://orcid.org/0000-0001-7034-0850"
  - name: Mali, P
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0002-3383-1287"
  - name: Payne-Foster, P
    affiliation: University of Alabama
    id: "https://orcid.org/0000-0002-3508-3577"
  - name: Ratcliffe, S
    affiliation: University of Virginia
    id: "https://orcid.org/0000-0002-6644-8284"
  - name: Ravitsky, V
    affiliation: University of Montreal
    id: "https://orcid.org/0000-0002-7080-8801"
  - name: Sali, A
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0003-0435-6197"
  - name: Schulz, W
    affiliation: Yale University
    id: "https://orcid.org/0000-0002-2048-4028"
  - name: Ideker, T
    affiliation: University of California San Diego
    id: "https://orcid.org/0000-0002-1708-8454"
funders:
  - grantor:
      id: "https://reporter.nih.gov/"
      name: National Institutes of Health
    grant:
      name: Bridge2AI CM4AI
      grant_number: 1OT2OD032742-01
existing_uses:
  - description: Clark T, et al. Cell Maps for Artificial Intelligence: AI-Ready Maps of Human Cell Architecture from Disease-Relevant Cell Lines. 2024. doi: http://doi.org/10.1101/2024.05.21.589311
  - description: Nourreddine S, et al. A PERTURBATION CELL ATLAS OF HUMAN INDUCED PLURIPOTENT STEM CELLS. bioRxiv. 2024 Nov 4; 2024.11.03.621734. PMCID: PMC11580897 doi: https://doi.org/10.1101/2024.11.03.621734
distribution_formats:
  - description: RO-Crate packages (JSON metadata) and ZIP archives for imaging data.
distribution_dates:
  - description: 2025-03-03
license_and_use_terms:
  description:
    - Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Attribution to copyright holders and authors required.
    - Cite related publication(s) and this data collection when used.
ip_restrictions:
  description:
    - Copyright (c) 2025 The Regents of the University of California except where otherwise noted.
    - Spatial proteomics raw image data copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University.
maintainers:
  - description:
      - Hosted/maintained by University of Virginia Dataverse (LibraData). Contact via dataset page.
      - Point of Contact: Trey Ideker (University of California San Diego).
updates:
  description:
    - Data will be augmented regularly through the end of the project.
use_repository:
  - description:
      - Public access via University of Virginia Dataverse; large datasets may require selective file downloads.
      - Repository software: Dataverse (version 6.6 build 1829-192cdc4).
      - Site includes Terms of Use and Privacy Policy.
subsets:
  - id: CRISPR Perturbation Cell Atlas/ro-crate-metadata.json
    name: ro-crate-metadata.json
    title: CRISPR Perturbation Cell Atlas RO-Crate metadata
    description: >
      Expressed genome-scale CRISPRi Perturbation Cell Atlas in undifferentiated
      KOLF2.1J hiPSCs mapping transcriptional and fitness phenotypes for 11,739 targeted genes.
      Metadata and provenance packaged as RO-Crate.
    format: JSON
    media_type: application/json
    md5: cbdb263b1c099396d75e16f00a79a818
    purposes:
      - response: AI-ready functional genomics data release to support ML research.
    tasks:
      - response: Single-cell perturb-seq analysis and model development.
      - response: Gene function and fitness phenotype modeling.
    instances:
      - representation: CRISPR perturbation atlas metadata (RO-Crate)
        data_type: JSON metadata describing samples, assays, and provenance
    acquisition_methods:
      - description: CRISPR interference (CRISPRi) with perturb-seq in KOLF2.1J hiPSCs.
    collection_timeframes:
      - description: Data created 2025-02-27; published 2025-03-03.
    data_collectors:
      - description: CM4AI consortium; UC San Diego and collaborating institutions.
    funders:
      - grantor:
          id: "https://reporter.nih.gov/"
          name: National Institutes of Health
        grant:
          name: Bridge2AI CM4AI
          grant_number: 1OT2OD032742-01
    existing_uses:
      - description: Related: Cell Maps for Artificial Intelligence (bioRxiv 2024.05.21.589311).
      - description: Related: A Perturbation Cell Atlas of Human iPSCs (bioRxiv 2024.11.03.621734).
    distribution_formats:
      - description: RO-Crate (JSON metadata).
    distribution_dates:
      - description: 2025-03-03
    license_and_use_terms:
      description:
        - CC BY-NC-SA 4.0. Attribution required; cite related publication and this data collection.
    ip_restrictions:
      description:
        - Copyright (c) 2025 The Regents of the University of California.
    maintainers:
      - description:
          - Hosted by University of Virginia Dataverse; contact via dataset page.
          - Point of Contact: Trey Ideker (UC San Diego).
  - id: CRISPR Perturbation RNA Sequences - Raw Sequences/ro-crate-metadata.json
    name: ro-crate-metadata.json
    title: CRISPR Perturbation RNA Sequences (Raw) RO-Crate metadata
    description: >
      Metadata for raw sequence data from CRISPRi perturb-seq in KOLF2.1J hiPSCs
      mapping transcriptional and fitness phenotypes for 11,739 targeted genes.
    format: JSON
    media_type: application/json
    md5: 1cafefa32a897998e3e2ba0a29a3ef5c
    purposes:
      - response: Provide raw RNA sequence context for AI/ML-ready perturb-seq analyses.
    tasks:
      - response: Single-cell RNA sequencing analysis of CRISPR perturbations.
    instances:
      - representation: Raw RNA sequence dataset metadata (RO-Crate)
        data_type: JSON metadata describing raw sequence files and provenance
    acquisition_methods:
      - description: CRISPRi with perturb-seq in KOLF2.1J hiPSCs; raw RNA sequences.
    collection_timeframes:
      - description: Data created 2025-02-27; published 2025-03-03.
    data_collectors:
      - description: CM4AI consortium; UC San Diego and collaborating institutions.
    funders:
      - grantor:
          id: "https://reporter.nih.gov/"
          name: National Institutes of Health
        grant:
          name: Bridge2AI CM4AI
          grant_number: 1OT2OD032742-01
    existing_uses:
      - description: Related: A Perturbation Cell Atlas of Human iPSCs (bioRxiv 2024.11.03.621734).
    distribution_formats:
      - description: RO-Crate (JSON metadata).
    distribution_dates:
      - description: 2025-03-03
    license_and_use_terms:
      description:
        - CC BY-NC-SA 4.0. Attribution required; cite related publication and this data collection.
    ip_restrictions:
      description:
        - Copyright (c) 2025 The Regents of the University of California.
    maintainers:
      - description:
          - Hosted by University of Virginia Dataverse; contact via dataset page.
          - Point of Contact: Trey Ideker (UC San Diego).
  - id: Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-untreated.zip
    name: cm4ai-v0.6-beta-if-images-untreated.zip
    title: Protein Localization Subcellular Images - Untreated (MDA-MB-468)
    description: >
      Spatial localization of 563 proteins in untreated MDA-MB-468 cells using ICC-IF and confocal microscopy
      (Lundberg Lab, Stanford). Channels: DAPI (nuclei, blue), calreticulin (ER, yellow), tubulin (red),
      protein-of-interest (green).
    format: ZIP
    media_type: application/zip
    md5: 0b4d129f5fbc3bb7f7ea564cd032cef7
    purposes:
      - response: AI-ready subcellular imaging for protein localization analysis and ML benchmarking.
    tasks:
      - response: Subcellular localization classification and feature learning from IF images.
    instances:
      - representation: Immunofluorescence confocal microscopy images (untreated MDA-MB-468)
        data_type: Multichannel TIFF/imagery within ZIP archive
    acquisition_methods:
      - description: ICC-IF staining and confocal microscopy; channels as specified.
    collection_timeframes:
      - description: Published 2025-03-03.
    data_collectors:
      - description: Lundberg Lab, Stanford University.
    funders:
      - grantor:
          id: "https://reporter.nih.gov/"
          name: National Institutes of Health
        grant:
          name: Bridge2AI CM4AI
          grant_number: 1OT2OD032742-01
    distribution_formats:
      - description: ZIP archive of imaging data.
    distribution_dates:
      - description: 2025-03-03
    license_and_use_terms:
      description:
        - CC BY-NC-SA 4.0. Attribution required; cite related publication and this data collection.
    ip_restrictions:
      description:
        - Spatial proteomics raw image data copyright (c) 2025 The Board of Trustees of the
          Leland Stanford Junior University.
        - Other data copyright (c) 2025 The Regents of the University of California.
    maintainers:
      - description:
          - Hosted by University of Virginia Dataverse; contact via dataset page.
          - Point of Contact: Trey Ideker (UC San Diego).
  - id: Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-paclitaxel.zip
    name: cm4ai-v0.6-beta-if-images-paclitaxel.zip
    title: Protein Localization Subcellular Images - Paclitaxel-treated (MDA-MB-468)
    description: >
      Spatial localization of 563 proteins in MDA-MB-468 cells treated with paclitaxel (ICC-IF, confocal; Lundberg Lab).
      Channels: DAPI (blue), calreticulin (ER, yellow), tubulin (red), protein-of-interest (green).
    format: ZIP
    media_type: application/zip
    md5: 9422486c80bc9e1d35b2fbbc72a5f043
    purposes:
      - response: Support ML studies on chemotherapy-induced subcellular localization changes.
    tasks:
      - response: Image-based ML for drug response phenotyping.
    instances:
      - representation: Immunofluorescence images (paclitaxel-treated MDA-MB-468)
        data_type: Multichannel microscopy images in ZIP archive
    acquisition_methods:
      - description: ICC-IF staining and confocal microscopy under paclitaxel treatment.
    collection_timeframes:
      - description: Published 2025-03-03.
    data_collectors:
      - description: Lundberg Lab, Stanford University.
    funders:
      - grantor:
          id: "https://reporter.nih.gov/"
          name: National Institutes of Health
        grant:
          name: Bridge2AI CM4AI
          grant_number: 1OT2OD032742-01
    distribution_formats:
      - description: ZIP archive of imaging data.
    distribution_dates:
      - description: 2025-03-03
    license_and_use_terms:
      description:
        - CC BY-NC-SA 4.0. Attribution required; cite related publication and this data collection.
    ip_restrictions:
      description:
        - Spatial proteomics raw image data copyright (c) 2025 The Board of Trustees of the
          Leland Stanford Junior University.
        - Other data copyright (c) 2025 The Regents of the University of California.
    maintainers:
      - description:
          - Hosted by University of Virginia Dataverse; contact via dataset page.
          - Point of Contact: Trey Ideker (UC San Diego).
  - id: Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-vorinostat.zip
    name: cm4ai-v0.6-beta-if-images-vorinostat.zip
    title: Protein Localization Subcellular Images - Vorinostat-treated (MDA-MB-468)
    description: >
      Spatial localization of 563 proteins in MDA-MB-468 cells treated with vorinostat (ICC-IF, confocal; Lundberg Lab).
      Channels: DAPI (blue), calreticulin (ER, yellow), tubulin (red), protein-of-interest (green).
    format: ZIP
    media_type: application/zip
    md5: ac577109a41a9806978461157b777d52
    purposes:
      - response: Enable ML analyses of HDAC inhibitor effects on protein localization.
    tasks:
      - response: Subcellular imaging analysis under vorinostat treatment.
    instances:
      - representation: Immunofluorescence images (vorinostat-treated MDA-MB-468)
        data_type: Multichannel microscopy images in ZIP archive
    acquisition_methods:
      - description: ICC-IF staining and confocal microscopy under vorinostat treatment.
    collection_timeframes:
      - description: Published 2025-03-03.
    data_collectors:
      - description: Lundberg Lab, Stanford University.
    funders:
      - grantor:
          id: "https://reporter.nih.gov/"
          name: National Institutes of Health
        grant:
          name: Bridge2AI CM4AI
          grant_number: 1OT2OD032742-01
    distribution_formats:
      - description: ZIP archive of imaging data.
    distribution_dates:
      - description: 2025-03-03
    license_and_use_terms:
      description:
        - CC BY-NC-SA 4.0. Attribution required; cite related publication and this data collection.
    ip_restrictions:
      description:
        - Spatial proteomics raw image data copyright (c) 2025 The Board of Trustees of the
          Leland Stanford Junior University.
        - Other data copyright (c) 2025 The Regents of the University of California.
    maintainers:
      - description:
          - Hosted by University of Virginia Dataverse; contact via dataset page.
          - Point of Contact: Trey Ideker (UC San Diego).
  - id: Protein-protein Interaction SEC-MS/ro-crate-metadata.json
    name: ro-crate-metadata.json
    title: Protein-Protein Interaction SEC-MS RO-Crate metadata
    description: >
      Size exclusion chromatography-mass spectrometry (SEC-MS) in undifferentiated KOLF2.1J hiPSCs,
      generated in the Nevan Krogan laboratory at UCSF as part of CM4AI (NIH Bridge2AI program).
      Data will be uploaded to PRIDE when available.
    format: JSON
    media_type: application/json
    md5: cb67e7749b15ce87b9042a9feba9d032
    purposes:
      - response: Provide AI-ready proteomics interaction data for modeling protein complexes.
    tasks:
      - response: Protein complex inference and PPI network analysis from SEC-MS profiles.
    instances:
      - representation: SEC-MS assay metadata (RO-Crate)
        data_type: JSON metadata describing SEC-MS experiments and provenance
    acquisition_methods:
      - description: Size exclusion chromatography followed by mass spectrometry (SEC-MS) in KOLF2.1J hiPSCs.
    collection_timeframes:
      - description: Data created 2025-02-27; published 2025-03-03.
    data_collectors:
      - description: Nevan Krogan Laboratory, University of California San Francisco.
    funders:
      - grantor:
          id: "https://reporter.nih.gov/"
          name: National Institutes of Health
        grant:
          name: Bridge2AI CM4AI
          grant_number: 1OT2OD032742-01
    external_resources:
      - external_resources: PRIDE repository (planned upload when available).
    distribution_formats:
      - description: RO-Crate (JSON metadata).
    distribution_dates:
      - description: 2025-03-03
    license_and_use_terms:
      description:
        - CC BY-NC-SA 4.0. Attribution required; cite related publication and this data collection.
    ip_restrictions:
      description:
        - Copyright (c) 2025 The Regents of the University of California.
    maintainers:
      - description:
          - Hosted by University of Virginia Dataverse; contact via dataset page.
          - Point of Contact: Trey Ideker (UC San Diego).