Tensor-Derived Similarity Networks for Characterising Spatial Patterns in Colorectal Cancer

Abstract excerpt

Spatial transcriptomics enables the study of gene expression within the spatial context of tissue architecture, offering new opportunities for understanding tumour heterogeneity. This study proposes a tensor-derived similarity network framework for analysing spatial organisation in colorectal cancer. Gene expression data from four patients are represented as spatially structured tensors and decomposed using a low-...

Topics

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• Algorithms
• Bioinformatics and Genomic Networks
• Cluster Analysis
• Ferroptosis and cancer prognosis
• Gene expression and cancer classification
• Neural Networks, Computer
• Phenotype
• Single-cell and spatial transcriptomics

Identifiers and source

Literature Corpus work

d41a9b41-c49e-5edc-bee8-d9566639d8a7

DOI

10.64898/2026.04.20.719742