Graph informed biomarker discovery framework using transcriptomic machine learning for glioblastoma prognosis

Abstract Identifying reproducible, interpretable prognostic signals from high-dimensional transcriptomics remains challenging because gene-level models often ignore network context. We developed Graph-Informed Biomarker Discovery (GIBD), a locked transcriptomics-only framework for primary glioblasto...

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Bibliografiske detaljer

Principais autores:	Osama Mahmoud, Mahmoud Mounir, Walaa Gad
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2026-06-01
Serier:	Scientific Reports
Fag:	Glioblastoma Transcriptomics Prognostic modeling Graph-informed machine learning Weighted protein–protein interaction External validation
Online adgang:	https://doi.org/10.1038/s41598-026-58062-4
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