# dataverse 10.18130 V3 B35XWX d4d

Datasheet for Dataset - Human Readable Format

🎯

## Motivation

Why was the dataset created?

Purposes

- Response
    Release AI-ready CM4AI functional genomics data with provenance graphs and rich metadata for research use as part of the NIH Bridge2AI Functional Genomics Grand Challenge.

Funders

Grantor | Grant Name | Grant Number
--- | --- | ---
National Institutes of Health (NIH) - Bridge2AI Program | - | -

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## Composition

What do the instances represent?

Instances

Data Type | Representation
--- | ---
Transcriptomic profiles from perturb-seq (single-cell RNA-seq under genetic perturbations) | Single-cell perturb-seq experiments in undifferentiated KOLF2.1J iPSCs
Proteomic/complexome measurements in KOLF2.1J iPSCs and iPSC-derived NPCs, neurons, and cardiomyocyt... | Size-exclusion chromatography mass spectrometry (SEC-MS) profiles
Cell imaging data from MDA-MB-468 breast cancer cells with and without chemotherapy (vorinostat, pac... | Immunofluorescence (IF) microscopy images

Distribution Formats

- Description
    RO-Crate

Distribution Dates

Description
Released 2025-03-20 (DC.date)
Dataset citation date referenced in description (2025-03-04)

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## Collection Process

How was the data acquired?

ID *
doi:10.18130/V3/B35XWX
Name
Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
Title
Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
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).
Page
https://dataverse.lib.virginia.edu/dataset.xhtml?persistentId=doi:10.18130/V3/B35XWX
Issued
2025-03-20
Language
en
Status
bibo:draft
Conforms To
https://w3id.org/ro/crate
Keywords

- Medicine, Health and Life Sciences
- Cell Maps for Artificial Intelligence
- CM4AI
- Bridge2AI
- perturb-seq
- SEC-MS
- immunofluorescence
- RO-Crate
- FAIRSCAPE
- functional genomics
- KOLF2.1J iPSCs
- NPCs
- neurons
- cardiomyocytes
- MDA-MB-468
- vorinostat
- paclitaxel

Created By

- 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

Collection Mechanisms

- Description
    Experimental data collection including single-cell perturb-seq, SEC-MS proteomics, and immunofluorescence microscopy across specified cell types and treatment conditions.

Acquisition Methods

1. Description
     Experimental measurements acquired via laboratory assays (sequencing, mass spectrometry, fluorescence microscopy).
   Was Directly Observed
     True
   Was Reported By Subjects
     False
   Was Inferred Derived
     False

Preprocessing Strategies

- Description
    Packaged with provenance graphs and rich metadata as RO-Crate using the FAIRSCAPE framework to enable AI-ready use.

Raw Sources

- Description
    Spatial proteomics raw image data are included (copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University).

🚀

## Uses

What (other) tasks could the dataset be used for?

License And Use Terms

Description
  - Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
  - Attribution is required to the copyright holders and the authors.
  - Copyright (c) 2025 The Regents of the University of California except where otherwise noted.
  - Spatial proteomics raw image data copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University.

📤

## Distribution

How will the dataset be distributed?

DOI
doi:10.18130/V3/B35XWX
License
https://creativecommons.org/licenses/by-nc-sa/4.0/
🔄

## Maintenance

How will the dataset be maintained?

Updates

Description
  - Data will be augmented regularly through the end of the project; updates will appear on the Dataverse landing page.

Generated on 2025-11-09 10:17:35 using Bridge2AI Data Sheets Schema