A review that groups AI methods for cancer spatial omics into data-driven, constraint-based, and mechanistic modeling paradigms, calling for more interpretable models and mouse-model-generated perturbational data.
CROST: a comprehensive repository of spatial transcriptomics,
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Emerging AI Approaches for Cancer Spatial Omics
A review that groups AI methods for cancer spatial omics into data-driven, constraint-based, and mechanistic modeling paradigms, calling for more interpretable models and mouse-model-generated perturbational data.