HIGHLIGHTS
SUMMARY
In gliomas, the expression of certain marker genes is strongly associated with survival, and in many studies, marker gene_expression levels were better predictors of survival than histological assessments. Microarray gene_expression clustering analysis revealed a diagnostic group of Int. Both single-gene-centered and genome-wide profiling have generated a wealth of information on glioma-associated transcriptomic landscapes and enabled the development of computational models for glioma progression basing on gene_expression data. The authors then compared biomarker capacities of single-gene_expression profiles with activation levels of these algorithmically deduced gene-centric pathways in human gliomas . . .
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