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This study maps epigenetic and transcriptional changes in myeloma progression from precursor to advanced stages, identifying key transcription factors involved in disease development.

gMCStool identifies metabolic vulnerabilities in cancer by predicting synthetic lethal interactions using genome-scale metabolic networks and RNA-seq data.

The paper improves prediction of lethal gene dependencies using the HUGE method, achieving 75x higher statistical power than existing methods in cancer genomics.