Exploration of DNA Microarrays Using Data Mining and a Taboo Search

Luis Alberto Hernández Montiel, José-Antonio León-Borges, Luis David Huerta Hernández


In this article, we present a hybrid method based on data mining techniques and a taboo search applied in the selection and classification of DNA Microarray genes. The method is divided into two stages, in the first stage all non-relevant information in the database is eliminated using five data filtering techniques. With the subsets of genes obtained by this step, a new stage of gene selection is carried out using a taboo search, for the classification process of the selected genes, the SVM, LDA, KNN classifiers are used separately. The method has been implemented to obtain a small subset of high performance genes, the results obtained are compared with other methods reported in the literature, this method is applied in three databases of public domain.


DNA microarrays, normalization, data filtering, selection, classification, local search.

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