Article

PathCLAST: Pathway-Augmented Contrastive Learning with Attention for Spatial Transcriptomics

2025-07-04

Abstract excerpt

<h4> A bstract </h4> <h4>Motivation</h4> Spatial transcriptomics provides high-resolution insights into tissue architecture and disease progression. While recent computational methods have advanced spatial domain identification, many focus primarily on gene expression alone, which may limit biological interpretability and underexploit complementary data such as histological images and known gene-pathway associ...

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Literature Corpus work: 2ed161ed-8907-5456-8469-aaa636c77e28
DOI: 10.1101/2025.06.30.662247

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