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

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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
License/Data Use Agreement	CC BY-NC-SA 4.0

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	ro-crate-metadata.json CRISPR Perturbation Cell Atlas/JSON - 31.1 KB Published Mar 3, 2025 23 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.	Access File File Access Public Download Options JSON Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	ro-crate-metadata.json CRISPR Perturbation RNA Sequences - Raw Sequences/JSON - 1000.1 KB Published Mar 3, 2025 12 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.	Access File File Access Public Download Options JSON Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	cm4ai-v0.6-beta-if-images-paclitaxel.zip Protein Localization Subcellular Images/ZIP Archive - 2.6 GB Published Mar 3, 2025 46 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" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	cm4ai-v0.6-beta-if-images-untreated.zip Protein Localization Subcellular Images/ZIP Archive - 3.2 GB Published Mar 3, 2025 37 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" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	cm4ai-v0.6-beta-if-images-vorinostat.zip Protein Localization Subcellular Images/ZIP Archive - 2.8 GB Published Mar 3, 2025 32 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" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	ro-crate-metadata.json Protein-protein Interaction SEC-MS/JSON - 2.9 KB Published Mar 3, 2025 15 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.	Access File File Access Public Download Options JSON Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX

Citation Metadata

Persistent Identifier	doi:10.18130/V3/B35XWX
Publication Date	2025-03-03
Title	Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
Author	Clark T (University of Virginia) - ORCID: https://orcid.org/0000-0003-4060-7360 Parker J (University of California, San Diego) - ORCID: https://orcid.org/0000-0003-4535-3486 Al Manir S (University of Virginia) - ORCID: https://orcid.org/0000-0003-4647-3877 Axelsson U (KTH Royal Institute of Technology,) Ballllosero Navarro F (Stanford University) - ORCID: https://orcid.org/0000-0002-4180-422X Chinn B (University of California San Diego) Churas CP (University of California San Diego) https://orcid.org/0000-0001-9998-705X Dailamy A (University of California, San Diego) - ORCID: https://orcid.org/0000-0002-6711-8260 Doctor Y (University of California, San Diego) - ORCID: https://orcid.org/0009-0009-0483-7506 Fall J (KTH - Royal Institute of Technology) Forget A (University of California San Francisco) - ORCID: https://orcid.org/0000-0003-0223-0312 Gao J (University of California San Diego) - ORCID: https://orcid.org/0000-0002-6311-3526 Hansen JN (Stanford University) - ORCID: https://orcid.org/0000-0002-4650-9094 Hu M (University of California San Diego) https://orcid.org/0000-0002-1571-8029 Johannesson A (KTH - Royal Institute of Technology) Khaliq H (University of California San Diego) Lee YH (University of California San Diego) - ORCID: https://orcid.org/0000-0003-0917-355X Lenkiewicz J (University of California San Diego) https://orcid.org/0000-0001-7252-8638 Levinson MA (University of Virginia) - ORCID: https://orcid.org/0000-0003-0384-8499 Marquez C (University of California San Diego) - ORCID: 0000-0003-3960-420X Metallo C (University of California San Diego) - ORCID: https://orcid.org/0000-0003-2404-3040 Muralidharan M (University of California San Francisco) Nourreddine S (University of California San Diego) https://orcid.org/0000-0003-3881-7588 Niestroy J (University of Virginia) - ORCID: https://orcid.org/0000-0002-1103-3882 Obernier K (University of California San Francisco) - ORCID: https://orcid.org/0000-0002-4025-1299 Pan E (University of California San Diego) Polacco B (University of California San Francisco) Pratt D (University of California San Diego) - ORCID: https://orcid.org/0000-0002-1471-9513 Qian G (University of California San Diego) - ORCID: https://orcid.org/0009-0005-4217-2745 Schaffer L (University of California San Diego) - ORCID: https://orcid.org/0000-0001-6339-9141 Sigaeva A (KTH Royal Institute of Technology) - ORCID: https://orcid.org/0000-0003-3361-3797 Thaker S (University of Alabama at Birmingham) - ORCID: https://orcid.org/0000-0001-6730-2773 Zhang Y (University of California San Diego) Bélisle-Pipon JC (Simon Fraser University) - ORCID: https://orcid.org/0000-0002-8965-8153 Brandt C (Yale University) - ORCID: https://orcid.org/0000-0001-8179-1796 Chen JY (The University of Alabama at Birmingham) - ORCID: https://orcid.org/0000-0002-6112-415X Ding Y (University of Texas at Austin) - ORCID: https://orcid.org/0000-0003-2567-2009 Fodeh S (Yale University) - ORCID: https://orcid.org/0000-0003-4664-3143 Krogan N (University of California San Francisco) - ORCID: https://orcid.org/0000-0003-4902-337X Lundberg E (Stanford University) - ORCID: https://orcid.org/0000-0001-7034-0850 Mali P (University of California San Diego) https://orcid.org/0000-0002-3383-1287 Payne-Foster P (University of Alabama) - ORCID: https://orcid.org/0000-0002-3508-3577 Ratcliffe S (University of Virginia) - ORCID: https://orcid.org/0000-0002-6644-8284 Ravitsky V (University of Montreal) - ORCID: https://orcid.org/0000-0002-7080-8801 Sali A (University of California San Diego) - ORCID: https://orcid.org/0000-0003-0435-6197 Schulz W (Yale University) - ORCID: https://orcid.org/0000-0002-2048-4028 Ideker T (University of California San Diego) - ORCID: https://orcid.org/0000-0002-1708-8454
Point of Contact	Use email button above to contact. Ideker Trey (University of California San Diego)
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 http://purl.obolibrary.org/obo/NCIT_C16309 (NCI Thesaurus) affinity purification http://www.bioassayontology.org/bao#BAO_0002603 (BioAssay Ontology (BAO)) AP-MS http://www.ebi.ac.uk/swo/SWO_1100012 (Software Ontology) artificial intelligence http://purl.obolibrary.org/obo/NCIT_C16309 (NCI Thesaurus) breast cancer http://purl.bioontology.org/ontology/LNC/LA14283-8 (LOINC) Bridge2AI cardiomyocyte http://purl.obolibrary.org/obo/CL_0000746 CM4AI CRISPR/Cas9 http://www.bioassayontology.org/bao#BAO_0010249 (Bioassay Ontology (BAO)) induced pluripotent stem cell http://www.ebi.ac.uk/efo/EFO_0004905 (Experimental Factor Ontology (EFO)) iPSC http://www.ebi.ac.uk/efo/EFO_0004905 (Experimental Factor Ontology (EFO)) KOLF2.1J machine learning http://purl.obolibrary.org/obo/OBI_0002587 (Ontology of Biomedical Investigations (OBI)) http://purl.obolibrary.org/obo/obi.owl mass spectroscopy http://purl.bioontology.org/ontology/MESH/D013058 (Medical Subject Headings (MeSH)) MDA-MB-468 neural progenitor cell http://purl.obolibrary.org/obo/CL_0011020 (Cell Ontology (CL)) NPC http://purl.obolibrary.org/obo/CL_0011020 (Cell Ontology (CL)) http://purl.obolibrary.org/obo/cl.owl neuron http://purl.obolibrary.org/obo/CL_0000540 (Cell Ontology (CL)) http://purl.obolibrary.org/obo/cl.owl paclitaxel http://purl.obolibrary.org/obo/CHEBI_45863 (Chemical Entitites of Biological Interest (CHEBI)) perturb-seq http://www.ebi.ac.uk/efo/EFO_0008860 (Experimental Factor Ontology (EFO)) perturbation sequencing http://www.ebi.ac.uk/efo/EFO_0008860 (Experimental Factor Ontology (EFO)) protein-protein interaction http://purl.obolibrary.org/obo/NCIT_C18469 (NCI Thesaurus (NCIT)) protein localization http://purl.obolibrary.org/obo/GO_0008104 (Gene Ontology (GO)) http://purl.obolibrary.org/obo/go/extensions/go-plus.owl single-cell RNA sequencing http://www.ebi.ac.uk/efo/EFO_0008913 (Experimental Factor Ontology (EFO)) scRNAseq http://www.ebi.ac.uk/efo/EFO_0008913 (Experimental Factor Ontology (EFO)) SEC-MS size exclusion chromatography subcellular imaging vorinostat http://purl.obolibrary.org/obo/CHEBI_45716 (Chemical Entitites of Biological Interest (CHEBI))
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 Nourreddine S, Doctor Y, Dailamy A, Forget A, Lee YH, Chinn B, Khaliq H, Polacco B, Muralidharan M, Pan E, Zhang Y, Sigaeva A, Hansen JN, Gao J, Parker JA, Obernier K, Clark T, Chen JY, Metallo C, Lundberg E, Ideker T, Krogan N, Mali P. 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
Data Creation Date	2025-02-27
Production Location	University of California San Diego; University of California San Francisco; University of California San Francisco; Stanford University; University of Virginia
Funding Information	National Institutes of Health: 1OT2OD032742-01
Depositor	Niestroy, Justin
Deposit Date	2025-02-27

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