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Deep learning-based feature discovery for decoding phenotypic plasticity in pediatric high-grade gliomas single-cell transcriptomics

Author(s): Abicumaran Uthamacumaran

Advancements in AI-powered systems medicine have revolutionized biomarker discovery through emergent and explainable features. By use of complex network dynamics and graph-based machine learning, we identified critical determinants of lineage-specific plasticity across the single-cell transcriptomics of pediatric high-grade glioma (pHGGs) subtypes: IDHWT ...

Article GUID: 40848317


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