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

Version 1.4
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 - March 2025 Data Release (Beta)", https://doi.org/10.18130/V3/B35XWX, University of Virginia Dataverse, V1
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Dataset Description
This dataset is the 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 perturb-seq data in undifferentiated KOLF2.1J iPSCs; SEC-MS data in undifferentiated KOLF2.1J iPSCs and iPSC-derived NPCs, neurons, and cardiomyocytes; and IF images in MDA-MB-468 breast cancer cells in the presence and absence of chemotherapy (vorinostat and paclitaxel). CM4AI output data are packaged with provenance graphs and rich metadata as AI-ready datasets in RO-Crate format using the FAIRSCAPE framework. Data presented here will be augmented regularly through the end of the project. CM4AI is a collaboration of UCSD, UCSF, Stanford, UVA, Yale, UA Birmingham, Simon Fraser University, and the Hastings Center. This data is Copyright (c) 2025 The Regents of the University of California except where otherwise noted. Spatial proteomics raw image data is copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University. Dataset licensed for reuse under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license (https://creativecommons.org/licenses/by-nc-sa/4.0/). Attribution is required to the copyright holders and the authors. Any publications referencing this data or derived products should cite the Related Publication below, as well as directly citing this data collection (2025-03-04). (2025-03-07)
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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ro-crate-metadata.json
CRISPR Perturbation Cell Atlas/JSON - 31.1 KB
Published Mar 3, 2025
10 Downloads
MD5: cbdb263b1c099396d75e16f00a79a818
This dataset represents an expressed genome-scale CRISPRi Perturbation Cell Atlas in undifferentiated KOLF2.1J human induced pluripotent stem cells (hiPSCs) mapping transcriptional and fitness phenotypes associated with 11,739 targeted genes, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) Functional Genomics Grand Challenge, a component of the U.S. National Institute of Health’s (NIH) Bridge2AI program. We validated these findings via phenotypic, protein-interaction, and metabolic tracing assays.
ro-crate-metadata.json
CRISPR Perturbation RNA Sequences - Raw Sequences/JSON - 1000.1 KB
Published Mar 3, 2025
4 Downloads
MD5: 1cafefa32a897998e3e2ba0a29a3ef5c
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, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) Functional Genomics Grand Challenge, a component of the U.S. National Institute of Health’s (NIH) Bridge2AI program.
cm4ai-v0.6-beta-if-images-paclitaxel.zip
Protein Localization Subcellular Images/ZIP Archive - 2.6 GB
Published Mar 3, 2025
7 Downloads
MD5: 9422486c80bc9e1d35b2fbbc72a5f043
This data set displays the spatial localization of 563 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 "Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-paclitaxel.zip"
cm4ai-v0.6-beta-if-images-untreated.zip
Protein Localization Subcellular Images/ZIP Archive - 3.2 GB
Published Mar 3, 2025
12 Downloads
MD5: 0b4d129f5fbc3bb7f7ea564cd032cef7
This data set displays the spatial localization of 563 proteins of interest in untreated cells of the breast cancer cell line MDA-MB-468 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 "Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-untreated.zip"
cm4ai-v0.6-beta-if-images-vorinostat.zip
Protein Localization Subcellular Images/ZIP Archive - 2.8 GB
Published Mar 3, 2025
10 Downloads
MD5: ac577109a41a9806978461157b777d52
This data set displays the spatial localization of 563 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 "Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-vorinostat.zip"
ro-crate-metadata.json
Protein-protein Interaction SEC-MS/JSON - 2.9 KB
Published Mar 3, 2025
3 Downloads
MD5: cb67e7749b15ce87b9042a9feba9d032
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, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) Functional Genomics Grand Challenge, a component of the U.S. National Institute of Health’s (NIH) Bridge2AI program. The data will be uploaded to Pride when available.
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