Optimal microrna sequencing depth to predict cancer patient survival with random forest and cox models

HIGHLIGHTS

• who: Ru00e9my Jardillier and colleagues from the UnivGrenoble Alpes, CEA, Inserm, IRIG, BioSantu00e9, BCI, Grenoble, France UnivGrenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, Institute of Engineering University Grenoble Alpes have published the research: Optimal microRNA Sequencing Depth to Predict Cancer Patient Survival with Random Forest and Cox Models, in the Journal: Genes 2022, 13, 2275. of 11/Dec/2020
• what: In the context of survival data the goal of this work is to benchmark the impact of the number of patients and of the sequencing depth of miRNA-seq and mRNA-seq on the predictive . . .
  

   

  

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