Enhancing Pan-cancer Spatial Transcriptomics at Single-cell Resolution with STPAINTER

Abstract excerpt

<h4>ABSTRACT</h4> Subcellular spatial transcriptomics technologies offer unprecedented views of tissue architecture but are fundamentally constrained by sparse gene panels and limited detection sensitivity. Current computational enhancement strategies typically rely on tissue-matched single-cell RNA sequencing (scRNA-seq) references and necessitate computationally intensive retraining for each dataset, impeding t...

Topics

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• Algorithms
• Extracellular vesicles in disease
• Gene Expression
• Image Processing, Computer-Assisted
• Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
• Neural Networks, Computer
• Phenotype
• Single-cell and spatial transcriptomics

Identifiers and source

Literature Corpus work

c6467cab-e9be-5d9c-8036-2f2d160b84e1

DOI

10.64898/2026.02.11.704553