Classification of Microarray Data

Methods Mol Biol. 2019:1986:185-205. doi: 10.1007/978-1-4939-9442-7_8.

Abstract

The automatic classification of DNA microarray data is one of the hot topics in the field of bioinformatics, since it is an effective tool for the diagnosis of diseases in patients. The aim of this chapter is to present the most relevant aspects related to the classification of microarrays. We carried out an analysis of the strategies used for the classification of microarray data and a review of the main methods used in the literature. In addition, other related aspects are addressed as the reduction of dimensionality, to try to eliminate redundant information in genes, or the treatment of imbalanced data and missing of data. To conclude, we present an exhaustive review of the main scientific works in journals to show the most successful techniques applied in this discipline as well as the most used datasets to verify their effectiveness.

Keywords: Classification methods; Classification problems; Data preprococessing; Machine learning; Microarray.

MeSH terms

  • Algorithms
  • Decision Trees
  • Oligonucleotide Array Sequence Analysis / methods*
  • ROC Curve
  • Reproducibility of Results