SOURCE METADATA
Project: CM4AI
Source ID: june_2026_dataverse_release
Source type: data resource
Source URL: https://dataverse.lib.virginia.edu/dataset.xhtml?persistentId=doi:10.18130/V3/HIGT4C
Raw file: data/raw/CM4AI/dataverse_10.18130_V3_HIGT4C_2026-07-24.html
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Cell Maps for Artificial Intelligence - June 2026 Data Release (Beta) - Cell Maps for Artificial Intelligence
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Cell Maps for Artificial Intelligence
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Cell Maps for Artificial Intelligence - June 2026 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, 2026, "Cell Maps for Artificial Intelligence - June 2026 Data Release (Beta)",
https://doi.org/10.18130/V3/HIGT4C
, University of Virginia Dataverse, V2
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Dataset Description
Description
This dataset is the June 2026 Data Release of Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org), the Functional Genomics Grand Challenge in the NIH Bridge2AI program. CM4AI is generating multi-modal data including protein-protein interaction (PPI), spatial localization, and genetic perturbation data in MDA-MB-468 breast cancer cells (+/- paclitaxel or vorinostat) and iPSCs (+/- differentiation). This Beta release includes:
Perturb-seq data for MDA-MB-468 breast cancer cells +/- treatment and undifferentiated (parental) KOLF2.1J iPSCs
SEC-MS data for MDA-MB-468 breast cancer cells +/- treatment, undifferentiated KOLF2.1J iPSCs, and iPSC-derived neuron progenitor cells (NPCs), neurons, and cardiomyocytes
AP-MS data for MDA-MB-468 breast cancer cells + treatment
IF images in MDA-MB-468 breast cancer cells +/- treatment
External Data Links
Access external data resources related to this dataset:
Perturb-seq data in KOLF2.1J iPSCs (undifferentiated):
Embargoed
Perturb-seq data in MDA-MB-468 breast cancer cells (+/- treatment):
Embargoed
CRISPRi Perturbation Atlas of iPSCs:
Figshare
SEC-MS data in KOLF2.1J iPSCs (undifferentiated, NPC, neuron, and cardiomyocyte):
MassIVE Repository
SEC-MS data in MDA-MB-468 breast cancer cells (+/- treatment):
MassIVE Repository
AP-MS data in MDA-MB-468 breast cancer cells (treated with paclitaxel):
MassIVE Repository
AP-MS data in MDA-MB-468 breast cancer cells (treated with vorinostat):
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
License/Data Use Agreement
CC BY-NC-SA 4.0
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OAI_ORE
DataCite
OpenAIRE
Schema.org JSON-LD
DDI Codebook v2
Dublin Core
Croissant
DDI HTML Codebook
JSON
Citation Metadata
Persistent Identifier
doi:10.18130/V3/HIGT4C
Publication Date
2026-06-17
Title
Cell Maps for Artificial Intelligence - June 2026 Data Release (Beta)
Author
Clark T
https://ror.org/0153tk833
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
https://ror.org/0153tk833
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
https://ror.org/0153tk833
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
https://ror.org/0153tk833
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
https://ror.org/0153tk833
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 2026 Data Release of Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org), the Functional Genomics Grand Challenge in the NIH Bridge2AI program. CM4AI is generating multi-modal data including protein-protein interaction (PPI), spatial localization, and genetic perturbation data in MDA-MB-468 breast cancer cells (+/- paclitaxel or vorinostat) and iPSCs (+/- differentiation). This Beta release includes:
Perturb-seq data for MDA-MB-468 breast cancer cells +/- treatment and undifferentiated (parental) KOLF2.1J iPSCs
SEC-MS data for MDA-MB-468 breast cancer cells +/- treatment, undifferentiated KOLF2.1J iPSCs, and iPSC-derived neuron progenitor cells (NPCs), neurons, and cardiomyocytes
AP-MS data for MDA-MB-468 breast cancer cells + treatment
IF images in MDA-MB-468 breast cancer cells +/- treatment
External Data Links
Access external data resources related to this dataset:
Perturb-seq data in KOLF2.1J iPSCs (undifferentiated):
Embargoed
Perturb-seq data in MDA-MB-468 breast cancer cells (+/- treatment):
Embargoed
CRISPRi Perturbation Atlas of iPSCs:
Figshare
SEC-MS data in KOLF2.1J iPSCs (undifferentiated, NPC, neuron, and cardiomyocyte):
MassIVE Repository
SEC-MS data in MDA-MB-468 breast cancer cells (+/- treatment):
MassIVE Repository
AP-MS data in MDA-MB-468 breast cancer cells (treated with paclitaxel):
MassIVE Repository
AP-MS data in MDA-MB-468 breast cancer cells (treated with vorinostat):
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
Dataset Terms
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Cell Maps for Artificial Intelligence
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