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Penalized mixture cure models for identifying genomic features associated with outcome in acute myeloid leukemia

US National Library of Medicine grant open #nih-5R01LM013879-04

Summary

Molecular features associated with time-to-event outcomes, such as overall or disease-free survival, may be prognostically relevant or potential therapeutic targets. Therefore, analyzing data from high-throughput genomic assays with clinical follow-up data has been of growing interest. The Cancer Genome Atlas (TCGA) Project has collected baseline demographic, clinical characteristics, and follow-up data for 11,125 patients for 32 different cancer types and corresponding tissue samples were processed for examining SNPs, copy number, methylation, miRNA expression, and mRNA expression. Because th

Penalized mixture cure models for identify…
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