Schizophrenia and cell senescence candidate genes screening, machine learning, diagnostic models, and drug prediction

HIGHLIGHTS

• who: ufeffYuufeff ufeffFengufeff and collaborators from the University of Cagliari, Italy have published the research work: Schizophrenia and cell senescence candidate genes screening, machine learning, diagnostic models, and drug prediction, in the Journal: (JOURNAL)
• what: In the current study, the gene_expression data, its survival time, and survival status were integrated using glmnet and RandomForest of the R software, and regression analysis were carried out using the Random Forest and lasso-cox methods.
• how: In this study the CIBERSORT algorithm was used to assess the proportion of 22 immune cells in schizophrenia samples and . . .
  

   

  

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