A novel ensemble approach for multicategory classification of DNA microarray data using biological relevant gene sets

Authors:
Miguel Reboiro-Jato;Daniel Glez-Peña;Fernando Dí-az;Florentino Fdez-Riverola
Affiliations:
Department Informática,University of Vigo, Escuela Superior de Ingenierí-a Informática, Edificio Politécnico, Campus Universitario, As Lagoas s/n, Ourense 32004, Spain;Department Informática,University of Vigo, Escuela Superior de Ingenierí-a Informática, Edificio Politécnico, Campus Universitario, As Lagoas s/n, Ourense 32004, Spain;Department Informática, University of Valladolid, Escuela Universitaria de Informática, Plaza Santa Eulalia, 9-11, Segovia 40005, Spain;Department Informática,University of Vigo, Escuela Superior de Ingenierí-a Informática, Edificio Politécnico, Campus Universitario, As Lagoas s/n, Ourense 32004, Spain
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2012

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Expert Systems with Applications: An International Journal
A novel ensemble of classifiers that use biological relevant gene sets for microarray classification

Applied Soft Computing

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Abstract

An important emerging medical application domain for microarray technology is clinical decision support in the form of diagnosis of diseases. For this task, several computational methods ranging from statistical alternatives to more complex hybrid systems have been previously proposed in the literature. In this work we study the utilisation of several ensemble alternatives for the task of classifying microarray data by using prior knowledge known to be biologically relevant to the target disease. The experimental results using different datasets and several gene sets show that the proposal is able to outperform previous approaches by introducing diversity as different gene sets.