Machine learning-based characterization of cuprotosis-related biomarkers and immune in ltration in s disease

HIGHLIGHTS

  • who: October and colleagues from the University of Toledo, United States have published the Article: Machine learning-based characterization of cuprotosis-related biomarkers and immune in ltration in s disease, in the Journal: (JOURNAL)
  • what: Our results identified three characteristic cuprotosis-related genes ATP7A, SLC31A1, and DBT involved in the immune process of Parkinson`s disease.
  • how: GSVA results showed that TNFA_SIGNALING signals G2/M cell cycle checkpoints and E2F transcriptional genes were higher in the C2 subtype than in the C1 subtype.
  • future: More research is needed on how to . . .

     

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