Classification algorithms for phenotype prediction in genomics and proteomics

Habtom W. Ressom, Rency S. Varghese, Zhen Zhang, Jianhua Xuan, Robert Clarke

Research output: Contribution to journalReview articlepeer-review

53 Scopus citations


This paper gives an overview of statistical and machine learning-based feature selection and pattern classification algorithms and their application in molecular cancer classification or phenotype prediction. In particular, the paper focuses on the use of these computational methods for gene and peak selection from microarray and mass spectrometry data, respectively. The selected features are presented to a classifier for phenotype prediction.

Original languageEnglish (US)
Pages (from-to)691-708
Number of pages18
JournalFrontiers in Bioscience
Issue number2
StatePublished - 2008


  • Classification
  • Feature selection
  • Gene expression
  • Mass spectrometry
  • Microarray
  • Review

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)


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