Machine learning and bioinformatics-based insights into the potential targets of saponins in paris polyphylla smith against non-small cell lung cancer

HIGHLIGHTS

• who: October and colleagues from the Anhui University, China have published the paper: Machine learning and bioinformatics-based insights into the potential targets of saponins in Paris polyphylla smith against non-small cell lung cancer, in the Journal: (JOURNAL)
• what: The authors searched for differential genes through gene_expression data published in GEO, and explored possible pathways using Disease Ontology (DO), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis after normalization of differential genes; further screened and validated potential signature genes RHEBL1 and RNPC3 in non-small cell lung cancer. This . . .
  

   

  

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