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Cell Maps for Artificial Intelligence - June 2025 Data Release (Beta)
Version 2.0









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 - June 2025 Data Release (Beta)", https://doi.org/10.18130/V3/F3TD5R, University of Virginia Dataverse, V2
                


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                                                            Dataset Description
                                                            

Description
This dataset is the June 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, iPSC-derived NPCs, neurons, cardiomyocytes, and treated and untreated MDA-MB468 breast cancer cells; and IF images in MDA-MB-468 breast cancer cells in the presence and absence of chemotherapy (vorinostat and paclitaxel).
External Data Links
Access external data resources related to this dataset:

Sequence Read Archive (SRA) Data: NCBI BioProject
Mass Spectrometry Data (Human iPSCs): MassIVE Repository
Mass Spectrometry Data (Human Cancer Cells): MassIVE Repository


Data Governance & Ethics

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

Completeness
These data are not yet in completed final form:

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

Maintenance Plan

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

Intended Use
This dataset is intended for:

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

Limitations
Researchers should be aware of inherent limitations:

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

Prohibited Uses

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

Potential Sources of Bias
Users should be aware of potential biases:

Data in this release was derived from commercially available de-identified human cell lines
Does not represent all biological variants which may be seen in the population at large
 (2025-06-30)
                                                                    

                                                            Subject
                                                            
Medicine, Health and Life Sciences

                                                            Keyword
                                                            

AI, affinity purification, AP-MS, artificial intelligence, breast cancer, Bridge2AI, cardiomyocyte, CM4AI, CRISPR/Cas9, induced pluripotent stem cell, iPSC, KOLF2.1J, machine learning, mass spectroscopy, MDA-MB-468, neural progenitor cell, NPC, neuron, paclitaxel, perturb-seq, perturbation sequencing, protein-protein interaction, protein localization, single-cell RNA sequencing, scRNAseq, SEC-MS, size exclusion chromatography, subcellular imaging, vorinostat

                                                            Related Publication
                                                            
References: Clark T, Parker J, Schaffer L, Obernier K, Al Manir S, Churas CP, Dailamy A, Doctor Y, Forget A, Hansen JN, Hu M, Lenkiewicz J, Levinson MA, Marquez C, Nourreddine S, Niestroy J, Pratt D, Qian G, Thaker S, Bélisle-Pipon JC, Brandt C, Chen J, Ding Y, Fodeh S, Krogan N, Lundberg E, Mali P, Payne-Foster P, Ratcliffe S, Ravitsky V, Sali A, Schulz W, Ideker T. Cell Maps for Artificial Intelligence: AI-Ready Maps of Human Cell Architecture from Disease-Relevant Cell Lines. 2024.doi: http://doi.org/10.1101/2024.05.21.589311


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This data set displays the spatial localization of 464 proteins of interest in cells of the breast cancer cell line MDA-MB-468 treated with paclitaxel as imaged by immunofluorescence-based staining (ICC-IF) and confocal microscopy in the Lundberg Lab at Stanford University, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) project. Nuclei were stained with DAPI (blue channel); endoplasmic reticulum with a calreticulin antibody (yellow channel); microtubules with tubulin antibody (red channel); and antibody against protein of interest (green channel).


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This data set displays the spatial localization of 464 proteins of interest in cells of the breast cancer cell line MDA-MB-468 treated as imaged by immunofluorescence-based staining (ICC-IF) and confocal microscopy in the Lundberg Lab at Stanford University, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) project. Nuclei were stained with DAPI (blue channel); endoplasmic reticulum with a calreticulin antibody (yellow channel); microtubules with tubulin antibody (red channel); and antibody against protein of interest (green channel).


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This data set displays the spatial localization of 464 proteins of interest in cells of the breast cancer cell line MDA-MB-468 treated with vorinostat as imaged by immunofluorescence-based staining (ICC-IF) and confocal microscopy in the Lundberg Lab at Stanford University, as part of the Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org) project. Nuclei were stained with DAPI (blue channel); endoplasmic reticulum with a calreticulin antibody (yellow channel); microtubules with tubulin antibody (red channel); and antibody against protein of interest (green channel).


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                                            Persistent Identifier
                                            

doi:10.18130/V3/F3TD5R


                                            Publication Date
                                            

2025-07-01


                                            Title
                                            
Cell Maps for Artificial Intelligence - June 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
                                            
Description
This dataset is the June 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, iPSC-derived NPCs, neurons, cardiomyocytes, and treated and untreated MDA-MB468 breast cancer cells; and IF images in MDA-MB-468 breast cancer cells in the presence and absence of chemotherapy (vorinostat and paclitaxel).
External Data Links
Access external data resources related to this dataset:

Sequence Read Archive (SRA) Data: NCBI BioProject
Mass Spectrometry Data (Human iPSCs): MassIVE Repository
Mass Spectrometry Data (Human Cancer Cells): MassIVE Repository


Data Governance & Ethics

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

Completeness
These data are not yet in completed final form:

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

Maintenance Plan

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

Intended Use
This dataset is intended for:

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

Limitations
Researchers should be aware of inherent limitations:

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

Prohibited Uses

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

Potential Sources of Bias
Users should be aware of potential biases:

Data in this release was derived from commercially available de-identified human cell lines
Does not represent all biological variants which may be seen in the population at large
 (2025-06-30)



                                            Subject
                                            
Medicine, Health and Life Sciences



                                            Keyword
                                            
AI 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; 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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