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.
- Feature selection
- Gene expression
- Mass spectrometry
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)