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Machine-learning analysis reveals an important role for negative selection in shaping cancer aneuploidy landscapes.

Juman JubranRachel SlutskyNir RozenblumLior RokachUri Ben-DavidEsti Yeger-Lotem
Published in: Genome biology (2024)
Our quantitative, interpretable machine learning models improve the understanding of the genomic properties that shape cancer aneuploidy landscapes.
Keyphrases
  • machine learning
  • papillary thyroid
  • squamous cell
  • artificial intelligence
  • high resolution
  • gene expression
  • childhood cancer
  • young adults
  • copy number