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Classification of Microarray Data

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Book cover Microarray Bioinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1986))

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.

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Notes

  1. 1.

    http://www.ebi.ac.uk/arrayexpress/.

  2. 2.

    http://www.ncbi.nlm.nih.gov/geo/.

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Authors and Affiliations

  1. Computer Science Department, Universidade da Coruña, A Coruña, Spain

    Noelia Sánchez-Maroño, Oscar Fontenla-Romero & Beatriz Pérez-Sánchez

Authors
  1. Noelia Sánchez-Maroño
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  2. Oscar Fontenla-Romero
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  3. Beatriz Pérez-Sánchez
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Corresponding author

Correspondence to Noelia Sánchez-Maroño .

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Editors and Affiliations

  1. CITIC, Universidade da Coruña, A Coruña, Spain

    Verónica Bolón-Canedo

  2. CITIC, Universidade da Coruña, A Coruña, Spain

    Amparo Alonso-Betanzos

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Sánchez-Maroño, N., Fontenla-Romero, O., Pérez-Sánchez, B. (2019). Classification of Microarray Data. In: Bolón-Canedo, V., Alonso-Betanzos, A. (eds) Microarray Bioinformatics. Methods in Molecular Biology, vol 1986. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9442-7_8

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  • DOI: https://doi.org/10.1007/978-1-4939-9442-7_8

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9441-0

  • Online ISBN: 978-1-4939-9442-7

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