Abstract:
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Recent technical advances enable us to measure spatially resolved transcriptome and proteome at single-cell resolution. This opens up exciting opportunities to characterize the spatial organization of cells and molecules, and link spatial motifs to disease phenotypes. This talk will provide an overview of statistical and computational challenges that arise from large-scale spatial omics data. I will then discuss how to extend ideas from graph neural networks, computer vision and spatial point processes to tackle these new questions.
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