Article

Generative Self-Supervised Graphs Enhance Integration, Imputation and Domains Identification of Spatial Transcriptomics

2024-01-22

Abstract excerpt

<title>Abstract</title> <p>Recent advances in spatial transcriptomics (ST) have opened new avenues for preserving spatial information while measuring gene expression. However, the challenge of seamlessly integrating this data into accurate and transferable representation persists. Here, we introduce a generative self-supervised graph (GSG) learning framework to accomplish an effective joint embedding of spatial l...

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Literature Corpus work: 226e99f4-5e56-5230-89b2-1c106d5dc42c
DOI: 10.21203/rs.3.rs-3583635/v1

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