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Canonical residual physics-informed neural networks and algorithmic perturbation landscapes map cell-fate transitions in longitudinal H3K27M glioma
Pediatric high-grade glioma is a dynamically heterogeneous disease in which therapeutic selection pressures, microenvironmental selection and developmental plasticity can reorganize cellular-state structure over time. Here we investigated these adaptive behaviors in glioma dynamics from single-cell
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