Title: A novel ensemble approach for multicategory classification of DNA microarray data using biological relevant gene sets
Authors: Miguel Reboiro-Jato; Daniel Glez-Peña; Fernando Díaz; Florentino Fdez-Riverola
Addresses: Department Informática,University of Vigo, Escuela Superior de Ingeniería Informática, Edificio Politécnico, Campus Universitario, As Lagoas s/n, Ourense 32004, Spain ' Department Informática,University of Vigo, Escuela Superior de Ingeniería 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 Ingeniería Informática, Edificio Politécnico, Campus Universitario, As Lagoas s/n, Ourense 32004, Spain
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.
Keywords: DNA microarray data; multicategory classification; ensemble classifiers; gene sets; knowledge integration; kappa statistic; clinical decision support; disease diagnosis; bioinformatics; prior knowledge; biological relevance.
DOI: 10.1504/IJDMB.2012.050267
International Journal of Data Mining and Bioinformatics, 2012 Vol.6 No.6, pp.602 - 616
Published online: 17 Dec 2014 *
Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article