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Prediction of tumor location in prostate cancer tissue using a machine learning system on gene expression data.

Osama HamzehAbedalrhman AlkhateebJulia ZhengSrinath KandalamLuis Rueda
Published in: BMC bioinformatics (2020)
The proposed method was able to detect sets of genes that can identify different laterality classes. The resulting genes are found to be strongly correlated with disease progression. HLA-DMB and EIF4G2, which are detected in the set of genes can detect the left laterality, were reported earlier to be in the same pathway called Allograft rejection SuperPath.
Keyphrases
  • prostate cancer
  • gene expression
  • genome wide
  • machine learning
  • genome wide identification
  • dna methylation
  • genome wide analysis
  • deep learning
  • artificial intelligence