TissueNarrator: Generative Modeling of Spatial Transcriptomics with Large Language Models.

ABSTRACT: The intricate spatial organization and molecular communication among cells are fundamental to multicellular systems. Spatial transcriptomics (ST) enables gene expression profiling while preserving spatial context, providing rich data for studying cellular interactions and tissue dynamics. However, most existing computational approaches focus on embedding-based tasks and provide limited generative capacity for simulating cell behavior in situ. Moreover, accurately interpreting spatial interactions requires extensive biological knowledge, which current models do not incorporate. Here, we introduce TissueNarrator, a framework that reformulates spatial omics analysis as a language modeling problem. By representing tissue sections as spatial sentences - rank-based gene lists augmented wi

SUBMITTER: Liu S 

PROVIDER: S-EPMC12697357 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature