1145-Kasumi: Learning Persistent Patterns in Spatial Data

This paper introduce Kasumi, a novel computational framework designed to analyze spatial omics data by identifying persistent local patterns within tissues. Unlike traditional methods that rely solely on cell-type clustering, Kasumi uses unsupervised multi-view modeling to capture complex, non-linear relationships between cells and their molecular markers. This approach allows researchers to repre...去小宇宙查看完整单集简介
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