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Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data.

Da XuJialin ZhangHanxiao XuYu-Sen ZhangWei ChenRui GaoMatthias Dehmer
Published in: BMC genomics (2020)
The proposed novel feature selection method is robust and effective for gene selection, classification, and visualization. The framework McbfsNW is practical and helpful for the identification of biomarkers and targets on genomic data. It is believed that the same methods and principles are extensible and applicable to other different kinds of data sets.
Keyphrases
  • machine learning
  • deep learning
  • big data
  • electronic health record
  • copy number
  • artificial intelligence
  • data analysis
  • gene expression
  • bioinformatics analysis