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Genetics

A vision foundation model for single-cell biology via spatial gene cartography

Ridvan Yesiloglu, Sakib Mostafa, James Zou, Ash Alizadeh, Jiajun Wu, Lei Xing, Ehsan Adeli, Md Tauhidul Islam

Featured July 17, 2026

Original Paper

AI-generated analysis — This is SciGrove's AI interpretation of the paper, not peer-reviewed content. Always refer to the original paper.

Simply

By turning a cell's gene activity into a picture where related genes sit close together, scVision helps computers 'see' and understand cell types and their programs much better than older methods.

In depth
The paper introduces scVision, a novel foundation model for single-cell biology that reframes gene expression analysis as a computer vision problem. Instead of treating genes as unordered tokens, scVision uses optimal transport to arrange genes into a fixed 2D image, called an scImage, where co-expressed genes are spatially proximate. A vision transformer is then pretrained on these images, enabling it to learn biologically meaningful representations that preserve both quantitative expression levels and gene-gene relationships.

Key Takeaways

  • 1
    scVision represents single-cell gene expression as a continuous-valued scImage, spatially organizing co-expressed genes using optimal transport, which preserves biological relationships and quantitative expression.
  • 2
    The model, a vision transformer pretrained on 72 million human cells, achieves superior zero-shot performance in cell-type annotation and gene-program discovery across diverse held-out datasets, outperforming existing token-based foundation models and classical baselines.
  • 3
    The spatial representation enhances interpretability, allowing attention maps to directly highlight active gene programs and enabling novel spatial masking experiments to perturb co-regulated gene neighborhoods.

Conceptual Flow

HIGH LEVEL
1
Methodology: Turning Cells into Pictures

The method takes a cell's gene list and draws it as a picture, putting genes that work together close to each other, then a smart computer program learns from these pictures.

Cell's Gene List
Arrange Genes Spatially
Cell Gene Picture
2
Results: Better Cell Understanding

This new picture-based method helps identify cell types and their hidden programs more accurately, even for new cells the computer has never seen before.

Cell Gene Picture
Find Cell Type & Programs
Accurate Cell ID
Active Gene Programs

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