TissueFormer: Extending single-cell foundation models to predict population-level phenotypes

Abstract excerpt

Single-cell RNA sequencing technologies have enabled unprecedented insights into gene expression and opened new pathways for diagnostics and tissue annotation. At present, most computational approaches for interpreting single-cell data predict labels or properties based on isolated single-cell transcriptomic profiles. This approach overlooks the cellular composition within a sample, which is often critical for inf...

Topics

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• Brain
• COVID-19
• Mice
• Neural Networks, Computer
• Sequence Analysis, RNA
• Single-Cell Analysis
• Single-Cell Gene Expression Analysis
• Transcriptome

Identifiers and source

Literature Corpus work

c7f8f7e6-6bbe-53a0-969c-6746d9330c9f

DOI

10.1101/2025.08.17.670735