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Incremental wrapper-based gene selection from microarray data for cancer classification

 

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Opened Access Incremental wrapper-based gene selection from microarray data for cancer classification
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Author: Ruiz, Roberto
Riquelme Santos, José Cristóbal
Aguilar Ruiz, Jesús Salvador
Department: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Date: 2006
Published in: Pattern Recognition, 39 (12), 2383-2392.
Document type: Article
Abstract: Gene expression microarray is a rapidly maturing technology that provides the opportunity to assay the expression levels of thousands or tens of thousands of genes in a single experiment. We present a new heuristic to select relevant gene subsets in order to further use them for the classification task. Our method is based on the statistical significance of adding a gene from a ranked-list to the final subset. The efficiency and effectiveness of our technique is demonstrated through extensive comparisons with other representative heuristics. Our approach shows an excellent performance, not only at identifying relevant genes, but also with respect to the computational cost.
Cite: Ruíz, R., Riquelme Santos, J.C. y Aguilar Ruiz, J.S. (2006). Incremental wrapper-based gene selection from microarray data for cancer classification. Pattern Recognition, 39 (12), 2383-2392.
Size: 390.5Kb
Format: PDF

URI: http://hdl.handle.net/11441/43247

DOI: 10.1016/j.patcog.2005.11.001

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