Cell Maps for Artificial Intelligence - June 2026 Data Release (Beta)

Version 1.0 DOI ↗ License ↗ 19.9 TB Released 2026-06-30

Datasheet Summary

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. 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; AP-MS data in MDA-MB-468 breast cancer cells in the presence of chemotherapy (vorinostat and paclitaxel); and IF images in MDA-MB-468 breast... [read full description]

Dataset Statistics
19.9 TB Total Size
53,877 Datasets
1,976 Computations
6 Software
Available Formats: .d .d directory group .tsv .xml TSV csv executable fastq.gz h5 h5ad (+2 more)
AI-Readiness Score (View Details)
100%
Overall
Fairness
4/4
Provenance
4/4
Characterization
5/5
Explainability
3/3
Ethics
4/4
Sustainability
4/4
Computability
4/4

Release Overview

Release Date
2026-06-30
Size
19.9 TB
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. 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; AP-MS data in MDA-MB-468 breast cancer cells in the presence of chemotherapy (vorinostat and paclitaxel); 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.
Authors
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
Publisher
https://dataverse.lib.virginia.edu/
Principal Investigator
Trey Ideker
Contact Email
Data Governance Committee
Jilian Parker
Ethical Review
Vardit Ravistky ravitskyv@thehastingscenter.org and Jean-Christophe Belisle-Pipon jean-christophe_belisle-pipon@sfu.ca.
Copyright
Terms of Use
Attribution is required to the copyright holders and the authors. Any publications referencing this data or derived data products should cite the Related Publications below, as well as directly citing this data collection.
HL7 Confidentiality Level
Unrestricted
Keywords
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, Artificial intelligence, Breast cancer, CRISPR perturbation, Cell maps, IPSC, Machine learning, Mass spectroscopy, Perturb-seq, Protein-protein interaction, cell maps
Cite As
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; Metallo C; Muralidharan M; Nourreddine S; Niestroy J; Obernier K; Pan E; Park, S; Polacco B; Pratt D; Qian G; Schaffer, LV; Sigaeva A; Thaker S; Zhang Y; Zhao, X; 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 2026 Data Release (Beta)", https://doi.org/10.18130/V3/HIGT4C , https://dataverse.lib.virginia.edu/, V1
Funding
National Institutes of Health: 1OT2OD032742-01, R01HG012351, R01NS131560, U54CA274502, #S10 OD026929. Department of Defense: W81XWH-22-1-0401. CIRM training: EDUC4-12804. Dutch Research Council: NWO, 019.231EN.013. National Cancer Institute: P30CA023100
Completeness
These data are not yet in completed final form, and 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.
Related Publications

Human Subjects & Regulatory

Human Subjects Research: None - data collected from commercially available cell lines
De-identified Samples: Yes
FDA Regulated: No
IRB Protocol ID: N/A
Institutional Review Board: N/A
Human Subjects Exemptions:

Exempt — research with commercially available de-identified human cell lines does not constitute human subjects research.

AI Ready Details

Intended Uses:
AI-ready datasets to support research in functional genomics, AI/machine learning model training, cellular process analysis, cell architectural changes, and interactions in presence of specific disease processes, treatment conditions, or genetic perturbations. A major goal is to enable biologically-driven, interpretable ML applications, for example as proposed in Ma et al. 2018 (PMID: 29505029) and Kuenzi et al. 2020 (PMID: 33096023).
Limitations:
This is an interim release. It 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:
Data in this release was derived from commercially available de-identified human cell lines, and does not represent all biological variants which may be seen in the population at large.
Maintenance Plan:
Dataset will be regularly updated and augmented on a quarterly basis through the end of the project (November, 2026). Long term preservation in the https://dataverse.lib.virginia.edu/, supported by committed institutional funds.
Data Collection:
Data collection processes are generally described in Clark T et al. (2024) "Cell Maps for Artificial Intelligence: AI-Ready Maps of Human Cell Architecture from Disease-Relevant Cell Lines" bioRxiv 2024.05.21.589311; doi: https://doi.org/10.1101/2024.05.21.589311. Additional data collection details will be subsequently published once finalized.
Data Collection Type:
Perturb-seq; IF imaging; SEC-MS; AP-MS
Missing Data:
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.
Collection Timeframe:
9/1/2022- 6/1/2026

Composition (Datasets 9)

EndoTag AP-MS Profiling of Chromatin Modifier Interactome Rewiring in MDA-MB-468 Cells Upon Paclitaxel Perturbation

Content Summary

📊 Files (556)
Formats: raw (549), tsv (2), pdf (1), txt (1), fasta (1), xml (1)
Access: No link (1), Available (555)
💻 Software & Instruments (1)
Software: 0
Instruments: 1
🧪 Inputs (234)
Derived From: MDA-MB-468. Unknown.
Datasets: 117
Sample (117)
⚙️ Other Components
Experiments: 118
AP-MS LFQ (118)
Sample → raw, Sample → fasta, pdf, raw, tsv, txt, xml
Computations: 0
Schemas: 2
Other: 59

EndoTag-AP-MS Profiling of Chromatin Modifier Interactome Rewiring in MDA-MB-468 Cells Upon Vorinostat Perturbation

Content Summary

📊 Files (719)
Formats: pdf (1), txt (1), fasta (1), tsv (2), xml (1), raw (712)
Access: No link (1), Available (718)
💻 Software & Instruments (1)
Software: 0
Instruments: 1
🧪 Inputs (276)
Derived From: MDA-MB-468. Unknown.
Datasets: 138
Sample (138)
⚙️ Other Components
Experiments: 139
AP-MS LFQ (139)
Sample → raw, Sample → fasta, pdf, tsv, txt, xml
Computations: 0
Schemas: 2
Other: 69

Paclitaxel IF Images

Content Summary

📊 Files (17686)
Formats: csv (1), image/jpeg (17684)
Access: No link (1), Available (17685)
💻 Software & Instruments (0)
🧪 Inputs (3)
Derived From: MDA-MB-468 Cell Line. Homo sapiens.
Datasets: 2
Sample (1), csv (1)
⚙️ Other Components
Experiments: 468
Immunofluorescence Imaging (468)
Sample → image/jpeg
Computations: 0
Schemas: 1
Other: 470

Untreated IF Images

Content Summary

📊 Files (15906)
Formats: csv (1), image/jpeg (15904)
Access: No link (1), Available (15905)
💻 Software & Instruments (0)
🧪 Inputs (3)
Derived From: MDA-MB-468 Cell Line. Homo sapiens.
Datasets: 2
Sample (1), csv (1)
⚙️ Other Components
Experiments: 468
Immunofluorescence Imaging (468)
Sample → image/jpeg
Computations: 0
Schemas: 1
Other: 470

Vorinostat IF Images

Content Summary

📊 Files (17850)
Formats: csv (1), image/jpeg (17848)
Access: No link (1), Available (17849)
💻 Software & Instruments (0)
🧪 Inputs (3)
Derived From: MDA-MB-468 Cell Line. Homo sapiens.
Datasets: 2
Sample (1), csv (1)
⚙️ Other Components
Experiments: 468
Immunofluorescence Imaging (468)
Sample → image/jpeg
Computations: 0
Schemas: 1
Other: 470

SEC-MS characterization of KOLF2 neuronal and cardiomyocyte differentiation

Content Summary

📊 Files (863)
Formats: csv (1), xml (1), tsv (1), Bruker .d (859)
Access: No link (1), Available (862)
💻 Software & Instruments (3)
Software: 2
Instruments: 1
🧪 Inputs (2)
Derived From: KOLF2.1J Cell Line. Homo sapiens.
Datasets: 1
Sample (1)
⚙️ Other Components
Experiments: 12
SEC-MS (11), SEC-MS library acquisition (1)
Sample → Bruker .d
Computations: 2
tsv → csv, Bruker .d → tsv, xml
Schemas: 2
Other: 1

SEC-MS of MDA-MB468 following treatment of vorinostat or paclitaxel.

Content Summary

📊 Files (19)
Formats: Bruker .d (9), TSV (9)
Access: Available (19)
💻 Software & Instruments (2)
Software: 1
Instruments: 1
🧪 Inputs (2)
Derived From: MDA-MB-468 Cell Line. Homo sapiens.
Datasets: 1
Sample (1)
⚙️ Other Components
Experiments: 9
Size Exclusion Chromatography-Mass Spectrometry (9)
Sample → Bruker .d
Computations: 9
Bruker .d → TSV
Schemas: 9
Other: 4

Perturbation Cell Atlas of Human Induced Pluripotent Stem Cells - Raw Sequence Data

Content Summary

📊 Files (284)
Formats: fastq.gz (192), h5 (90), pdf (1)
Access: No link (1), Embargoed (283)
💻 Software & Instruments (3)
Software: 2
Instruments: 1
🧪 Inputs (384)
Derived From: KOLF2.1J Cell Line. Homo sapiens.
Datasets: 192
Sample (192)
⚙️ Other Components
Experiments: 192
RNA-Seq (192)
Sample → fastq.gz
Computations: 90
fastq.gz → h5
Schemas: 1
Other: 1

Perturbation Cell Atlas of Human Induced Pluripotent Stem Cells - Perturb Seq

Content Summary

📊 Files (3)
Formats: h5ad (2)
Access: No link (1), Available (2)
💻 Software & Instruments (1)
Software: 1
Instruments: 0
🧪 Inputs (90)
Datasets: 90
Perturbation Cell Atlas of Human Induced Pluripotent Stem Cells - Raw Sequence Data (h5) (90)
⚙️ Other Components
Experiments: 0
Computations: 1
Perturbation Cell Atlas of Human Induced Pluripotent Stem Cells - Raw Sequence Data h5 → h5ad
Schemas: 1
Other: 0

Distribution Information

Publisher:
https://dataverse.lib.virginia.edu/
Release Date:
2026-06-30
Version:
1.0