096-TrimNN: Analyzing Cellular Communities

Paper Talk · Sep 28, 2025 · 35m

This article introduces TrimNN, a novel graph-based deep learning framework designed to characterize cellular community (CC) motifs within complex tissues using spatial transcriptomics and proteomics data. Unlike traditional top-down clustering approaches, TrimNN employs a bottom-up strategy to identify conserved spatial patterns of cell interactions, offering improved interpretability and generalizability. The research demonstrates TrimNN's effectiveness in revealing phenotype-associated CC motifs in studies of colorectal cancer and Alzheimer's disease, showing its potential for discovering…