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

































































































































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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


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CRISPR Perturbation Cell Atlas/JSON - 31.1 KB
Published Mar 3, 2025
33 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. 


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CRISPR Perturbation RNA Sequences - Raw Sequences/JSON - 1000.1 KB
Published Mar 3, 2025
19 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. 


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                        cm4ai-v0.6-beta-if-images-paclitaxel.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 2.6 GB
Published Mar 3, 2025
95 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). 


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                        cm4ai-v0.6-beta-if-images-untreated.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 3.2 GB
Published Mar 3, 2025
70 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). 


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                        cm4ai-v0.6-beta-if-images-vorinostat.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 2.8 GB
Published Mar 3, 2025
59 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). 


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Protein-protein Interaction SEC-MS/JSON - 2.9 KB
Published Mar 3, 2025
22 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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                                            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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Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta) - Cell Maps for Artificial Intelligence

































































































































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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


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CRISPR Perturbation Cell Atlas/JSON - 31.1 KB
Published Mar 3, 2025
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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. 


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CRISPR Perturbation RNA Sequences - Raw Sequences/JSON - 1000.1 KB
Published Mar 3, 2025
19 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. 


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                        cm4ai-v0.6-beta-if-images-paclitaxel.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 2.6 GB
Published Mar 3, 2025
95 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). 


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                        cm4ai-v0.6-beta-if-images-untreated.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 3.2 GB
Published Mar 3, 2025
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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). 


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                        cm4ai-v0.6-beta-if-images-vorinostat.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 2.8 GB
Published Mar 3, 2025
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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). 


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Protein-protein Interaction SEC-MS/JSON - 2.9 KB
Published Mar 3, 2025
22 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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                                            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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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


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CRISPR Perturbation Cell Atlas/JSON - 31.1 KB
Published Mar 3, 2025
33 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. 


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CRISPR Perturbation RNA Sequences - Raw Sequences/JSON - 1000.1 KB
Published Mar 3, 2025
19 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. 


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                        cm4ai-v0.6-beta-if-images-paclitaxel.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 2.6 GB
Published Mar 3, 2025
95 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). 


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                        cm4ai-v0.6-beta-if-images-untreated.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 3.2 GB
Published Mar 3, 2025
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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). 


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                        cm4ai-v0.6-beta-if-images-vorinostat.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 2.8 GB
Published Mar 3, 2025
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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). 


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Protein-protein Interaction SEC-MS/JSON - 2.9 KB
Published Mar 3, 2025
22 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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                                            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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Our Community Norms as well as good scientific practices expect that proper credit is given via citation. Please use the data citation shown on the dataset page.
                                   


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

































































































































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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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CRISPR Perturbation Cell Atlas/JSON - 31.1 KB
Published Mar 3, 2025
33 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. 


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CRISPR Perturbation RNA Sequences - Raw Sequences/JSON - 1000.1 KB
Published Mar 3, 2025
19 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. 


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                        cm4ai-v0.6-beta-if-images-paclitaxel.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 2.6 GB
Published Mar 3, 2025
95 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). 


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                        cm4ai-v0.6-beta-if-images-untreated.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 3.2 GB
Published Mar 3, 2025
70 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). 


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                        cm4ai-v0.6-beta-if-images-vorinostat.zip
                    

Protein Localization Subcellular Images/ZIP Archive - 2.8 GB
Published Mar 3, 2025
59 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). 


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Protein-protein Interaction SEC-MS/JSON - 2.9 KB
Published Mar 3, 2025
22 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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                                            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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