Paper Talk

1145-Kasumi: Learning Persistent Patterns in Spatial Data


Listen Later

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
前往小宇宙评论区与主播互动
...more
View all episodesView all episodes
Download on the App Store

Paper TalkBy 淼淼Elva