Deciphering Microenvironmental Heterogeneity by Scalable Niche Guided Module Discovery

Abstract excerpt

<title>Abstract</title> <p>Spatial transcriptomics provides high-dimensional gene expression data while preserving spatial context, offering novel insights into tissue composition and heterogeneity. Each spot or cell in the spatial transcriptome could be reflected as gene modules influenced by its surrounding microenvironment, with module interactions vital for tissue architecture and function. Here, we present S...

Topics

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• Algorithms
• Bioinformatics and Genomic Networks
• Cancer Immunotherapy and Biomarkers
• Microscopy
• Neoplasms
• Phenotype
• Radiomics and Machine Learning in Medical Imaging
• Single-cell and spatial transcriptomics

Identifiers and source

Literature Corpus work

28f45d2d-553f-51ba-926a-8fb09e91286e

DOI

10.21203/rs.3.rs-7243521/v1