Article

Inferring single-cell spatial gene expression with tissue morphology via explainable deep learning

2024-06-14

Abstract excerpt

Deep learning models trained with spatial omics data uncover complex patterns and relationships among cells, genes, and proteins in a high-dimensional space. State-of-the-art in silico spatial multi-cell gene expression methods using histological images of tissue stained with hematoxylin and eosin (H&E) allow us to characterize cellular heterogeneity. We developed a vision transformer (ViT) framework to map histo...

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Literature Corpus work: 6dec4f1d-bb67-5140-9cf6-98316f9ec6a8
DOI: 10.1101/2024.06.12.598686

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