Heterogeneity-driven adaptive scale graph learning for subcellular spatial transcriptomics
Wanwan Shi, Cong Shen, Ying Liu, Qiu Xiao, Jiawei Luo
This paper introduces HAST, a framework for spatial transcriptomics that adapts graph learning scales to tissue heterogeneity, improving spatial structure identification and tumor region characterization.
bioRxiv · May 21, 2026 · PreprintBioinformatics