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Development and validation of GMI signature based random survival forest prognosis model to predict clinical outcome in acute myeloid leukemia

26 Jun 2019

Abstract excerpt

BACKGROUND: Acute myeloid leukemia (AML) is a disease with marked molecular heterogeneity and a high early death rate. Our aim was to investigate an integrated Gene expression, Mirna and miRNA-mRNA Interactions (GMI) signature for improving risk stratification of AML. METHODS: We identified differentially expressed genes by pooling a large number of 861 human AML patients and 75 normal cases. We then used miRWalk...

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PMID: 31242922
DOI: 10.1186/s12920-019-0540-5

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