Cell Maps for Artificial Intelligence - October 2025 Data Release (Beta)

Version 2.1
Clark, T; Parker, J; Al Manir, S; Axelsson, U; Ballllosero Navarro, F; Chinn, B; Churas, CP; Dailamy, A; Doctor, Y; Fall, J; Forget, A; Gao, J; Hansen, JN; Hu, M; Johannesson, A; Khaliq, H; Lee, YH; Lenkiewicz, J; Levinson, MA; Marquez, C; Metallo, C; Muralidharan, M; Nourreddine, S; Niestroy, J; Obernier, K; Pan, E; Polacco, B; Pratt, D; Qian, G; Schaffer, L; Sigaeva, A; Thaker, S; Zhang, Y; Bélisle-Pipon, JC; Brandt, C; Chen, JY; Ding, Y; Fodeh, S; Krogan, N; Lundberg, E; Mali, P; Payne-Foster, P; Ratcliffe, S; Ravitsky, V; Sali, A; Schulz, W; Ideker, T, 2025, "Cell Maps for Artificial Intelligence - October 2025 Data Release (Beta)", https://doi.org/10.18130/V3/K7TGEM, University of Virginia Dataverse, V2
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Dataset Description

Description

This dataset is the October 2025 Data Release of Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org), the Functional Genomics Grand Challenge in the NIH Bridge2AI program. CM4AI is generating multi-modal data including protein-protein interaction (PPI), spatial localization, and genetic perturbation data in MDA-MB-468 breast cancer cells (+/- paclitaxel or vorinostat) and iPSCs (+/- differentiation). This Beta release includes:

  • Perturb-seq data for MDA-MB-468 breast cancer cells +/- treatment and undifferentiated (parental) KOLF2.1J iPSCs
  • SEC-MS data for MDA-MB-468 breast cancer cells +/- treatment, undifferentiated KOLF2.1J iPSCs, and iPSC-derived neuron progenitor cells (NPCs), neurons, and cardiomyocytes
  • IF images in MDA-MB-468 breast cancer cells +/- treatment

External Data Links

Access external data resources related to this dataset:

  • Perturb-seq data in KOLF2.1J iPSCs (undifferentiated): Embargoed
  • Perturb-seq data in MDA-MB-468 breast cancer cells (+/- treatment): Embargoed
  • SEC-MS data in KOLF2.1J iPSCs (undifferentiated, NPC, neuron, and cardiomyocyte): MassIVE Repository
  • SEC-MS data in MDA-MB-468 breast cancer cells (+/- treatment): MassIVE Repository

Data Governance & Ethics

  • Human Subjects: No
  • De-identified Samples: Yes
  • FDA Regulated: No
  • Data Governance Committee: Jillian Parker (jillianparker@health.ucsd.edu)
  • Ethical Review: Vardit Ravitsky (ravitskyv@thehastingscenter.org) and Jean-Christophe Belisle-Pipon (jean-christophe_belisle-pipon@sfu.ca)

Completeness

These data are not yet in completed final form:

  • Some datasets are under temporary pre-publication embargo
  • Protein-protein interaction (SEC-MS), protein localization (IF imaging), and CRISPRi perturbSeq data interrogate sets of proteins which incompletely overlap
  • Computed cell maps not included in this release

Maintenance Plan

  • Dataset will be regularly updated and augmented through the end of the project in November 2026
  • Updates on a quarterly basis
  • Long term preservation in the University of Virginia Dataverse, supported by committed institutional funds

Intended Use

This dataset is intended for:

  • AI-ready datasets to support research in functional genomics
  • AI model training
  • Cellular process analysis
  • Cell architectural changes and interactions in presence of specific disease processes, treatment conditions, or genetic perturbations

Limitations

Researchers should be aware of inherent limitations:

  • This is an interim release
  • Does not contain predicted cell maps, which will be added in future releases
  • The current release is most suitable for bioinformatics analysis of the individual datasets
  • Requires domain expertise for meaningful analysis

Prohibited Uses

  • These laboratory data are not to be used in clinical decision-making or in any context involving patient care without appropriate regulatory oversight and approval

Potential Sources of Bias

Users should be aware of potential biases:

  • Data in this release was derived from commercially available de-identified human cell lines
  • Does not represent all biological variants which may be seen in the population at large
(2025-06-30)
Subject Medicine, Health and Life Sciences
Keyword AI, affinity purification, AP-MS, artificial intelligence, breast cancer, Bridge2AI, cardiomyocyte, CM4AI, CRISPR/Cas9, induced pluripotent stem cell, iPSC, KOLF2.1J, machine learning, mass spectroscopy, MDA-MB-468, neural progenitor cell, NPC, neuron, paclitaxel, perturb-seq, perturbation sequencing, protein-protein interaction, protein localization, single-cell RNA sequencing, scRNAseq, SEC-MS, size exclusion chromatography, subcellular imaging, vorinostat
Related Publication References: Clark T, Parker J, Schaffer L, Obernier K, Al Manir S, Churas CP, Dailamy A, Doctor Y, Forget A, Hansen JN, Hu M, Lenkiewicz J, Levinson MA, Marquez C, Nourreddine S, Niestroy J, Pratt D, Qian G, Thaker S, Bélisle-Pipon JC, Brandt C, Chen J, Ding Y, Fodeh S, Krogan N, Lundberg E, Mali P, Payne-Foster P, Ratcliffe S, Ravitsky V, Sali A, Schulz W, Ideker T. 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
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CC BY-NC-SA 4.0

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cm4ai_mass-spec_KOLF2.zip
ZIP Archive - 23.8 MB
Published Oct 31, 2025
29 Downloads
MD5: fb04933a21e4395cce56930a014c6b4e
This dataset was generated by size exclusion chromatography-mass spectroscopy (SEC-MS) on undifferentiated KOLF2.1J human induced pluripotent stem cells (hiPSCs), in the Nevan Krogan laboratory at the University of California San Francisco.
Preview "cm4ai_mass-spec_KOLF2.zip"
cm4ai_mass-spec_MDA-MB-468.zip
ZIP Archive - 23.0 MB
Published Oct 31, 2025
24 Downloads
MD5: 662d62ced9d379f7024e5c6d55859fbb
This dataset was generated by size exclusion chromatography-mass spectroscopy (SEC-MS) following the treatment of vorinostat or paclitaxel on MDA-MB468 human breast cancer cells, in the Nevan Krogan laboratory at the University of California San Francisco.
Preview "cm4ai_mass-spec_MDA-MB-468.zip"
cm4ai_perturb-seq_KOLF2_cell_atlas.zip
ZIP Archive - 24.6 KB
Published Oct 31, 2025
32 Downloads
MD5: 15dc59312466dbfac85f59b57d27eee6
This dataset represents an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J human induced pluripotent stem cells (hiPSCs) mapping transcriptional and fitness phenotypes associated with 11,739 targeted genes.
Preview "cm4ai_perturb-seq_KOLF2_cell_atlas.zip"
cm4ai_perturb-seq_KOLF2_raw_sra.zip
ZIP Archive - 79.6 KB
Published Dec 22, 2025
17 Downloads
MD5: 1cfc4e8e2ead7513a035cc7730046ebb
This dataset represents raw sequence data from an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J human induced pluripotent stem cells (hiPSCs) mapping transcriptional and fitness phenotypes associated with 11,739 targeted genes.
Preview "cm4ai_perturb-seq_KOLF2_raw_sra.zip"
cm4ai_release_metadata.zip
ZIP Archive - 203.5 KB
Published Dec 22, 2025
29 Downloads
MD5: c14cc7aaaa0e7231a0d3ec296ff58518
Preview "cm4ai_release_metadata.zip"
cm4ai_ifimages_MDA-MB-468_paclitaxel.zip
Images/ZIP Archive - 3.8 GB
Published Oct 31, 2025
34 Downloads
MD5: 0d972b80744344ddeede516a0cf6e3d7
This data set displays the spatial localization of 464 proteins of interest in cells of the breast cancer cell line MDA-MB-468 treated with paclitaxel as imaged by immunofluorescence-based staining (ICC-IF) and confocal microscopy in the Lundberg Lab at Stanford University, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) project. Nuclei were stained with DAPI (blue channel); endoplasmic reticulum with a calreticulin antibody (yellow channel); microtubules with tubulin antibody (red channel); and antibody against protein of interest (green channel).
Preview "Images/cm4ai_ifimages_MDA-MB-468_paclitaxel.zip"
cm4ai_ifimages_MDA-MB-468_untreated.zip
Images/ZIP Archive - 4.6 GB
Published Oct 31, 2025
37 Downloads
MD5: a98affcc05429650c6bb3906cd836d55
This data set displays the spatial localization of 464 proteins of interest in cells of the breast cancer cell line MDA-MB-468 treated as imaged by immunofluorescence-based staining (ICC-IF) and confocal microscopy in the Lundberg Lab at Stanford University, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) project. Nuclei were stained with DAPI (blue channel); endoplasmic reticulum with a calreticulin antibody (yellow channel); microtubules with tubulin antibody (red channel); and antibody against protein of interest (green channel).
Preview "Images/cm4ai_ifimages_MDA-MB-468_untreated.zip"
cm4ai_ifimages_MDA-MB-468_vorinostat.zip
Images/ZIP Archive - 4.2 GB
Published Oct 31, 2025
23 Downloads
MD5: ad4e68ccc14b0f3349dad3321e7b81b2
This data set displays the spatial localization of 464 proteins of interest in cells of the breast cancer cell line MDA-MB-468 treated with vorinostat as imaged by immunofluorescence-based staining (ICC-IF) and confocal microscopy in the Lundberg Lab at Stanford University, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) project. Nuclei were stained with DAPI (blue channel); endoplasmic reticulum with a calreticulin antibody (yellow channel); microtubules with tubulin antibody (red channel); and antibody against protein of interest (green channel).
Preview "Images/cm4ai_ifimages_MDA-MB-468_vorinostat.zip"
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