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Single-cell, Spatial & Cytometry · Single-cell Models

Universal Cell Embeddings

By Stanford SNAP / UCE contributors →

Foundation-model embeddings for single-cell expression

Foundation-model embeddings for single-cell expression. Check species support and gene naming; pretrained embeddings do not eliminate batch effects automatically.

Foundation-model embeddings for single-cell expressionInput: AnnData with counts and compatible gene namesOutput: Cell embeddings in an AnnData output
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Overview

Foundation-model embeddings for single-cell expression. Check species support and gene naming; pretrained embeddings do not eliminate batch effects automatically.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 16/09/2026, 17:33:40

Key Features

  • Foundation-model embeddings for single-cell expression
  • Input: AnnData with counts and compatible gene names
  • Output: Cell embeddings in an AnnData output

Academic Context & Research Evidence

Biological & Workflow Fit

Compute & Hardware
Consult linked installation guidance; workload dependent
Licensing & Academic Use
Review the linked release, model weights, datasets and service terms separately
Documented Evidence
Project or provider documentation; no local performance benchmark

Cite this Tool

Use this citation format when referencing Universal Cell Embeddings in scientific publications and benchmark papers.

@software{uce_2026,
  title = {{Universal Cell Embeddings}},
  author = {{Stanford SNAP / UCE contributors}},
  year = {2026},
  url = {https://github.com/snap-stanford/UCE},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for Universal Cell Embeddings.

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Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeResearch software / model
Access modePublic code / project terms
AI roleScientific machine learning
Input dataAnnData with counts and compatible gene names
Output dataCell embeddings in an AnnData output
Licence conditionsReview the linked release, model weights, datasets and service terms separately
Commercial eligibilityNot independently confirmed
Compute requirementsConsult linked installation guidance; workload dependent
ValidationEvaluate on representative data; no clinical suitability established
TypeNot recorded
Intended useBiological and pharmaceutical research
CompatibilityNot recorded
LimitationsCheck species support and gene naming; pretrained embeddings do not eliminate batch effects automatically.
Evidence levelProject or provider documentation; no local performance benchmark
AvailabilitySee project access and maintenance status
Price / accessSee project terms; compute costs may apply

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

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BEFORE YOU CHOOSE

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FAQ

Where is this product available?

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating Universal Cell Embeddings.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5