SRLST: a unified multimodal representation learning framework for spatial transcriptomics analysis
Across distinct experimental datasets, SRLST consistently outperforms existing methods in delineating cortical organization, identifying small discontinuous tissue compartments, and capturing complex intratumor heterogeneity.