In this study, we aimed to uncover novel biomarkers in acute myeloid leukemia (AML) that could serve as prognostic indicators or therapeutic targets. We analyzed AML microarray datasets from the Gene Expression Omnibus (GEO) repository, identifying key differentially expressed genes (DEGs) through the robust rank aggregation (RRA) approach. The functions of these DEGs were elucidated through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses.
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