Tensor-Derived Similarity Networks for Characterising Spatial Patterns in Colorectal Cancer (opens in new tab)

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-rank canonical polyadic model to extract latent spatial molecular features. Thes...