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Issue No. 05 - September/October (2011 vol. 8)
ISSN: 1545-5963
pp: 1385-1392
Marco Muselli , Consiglio Nazionale delle Ricerche, Genova
Alberto Bertoni , Università degli Studi di Milano, Milano
Marco Frasca , Università degli Studi di Milano, Milano
Alessandro Beghini , Università degli Studi di Milano, Milano
Francesca Ruffino , Università degli Studi di Milano, Milano
Giorgio Valentini , Università degli Studi di Milano, Milano
Gene selection methods aim at determining biologically relevant subsets of genes in DNA microarray experiments. However, their assessment and validation represent a major difficulty since the subset of biologically relevant genes is usually unknown. To solve this problem a novel procedure for generating biologically plausible synthetic gene expression data is proposed. It is based on a proper mathematical model representing gene expression signatures and expression profiles through Boolean threshold functions. The results show that the proposed procedure can be successfully adopted to analyze the quality of statistical and machine learning-based gene selection algorithms.
Gene selection, feature selection, mathematical models, gene expression, Boolean functions.

A. Beghini, M. Muselli, F. Ruffino, M. Frasca, G. Valentini and A. Bertoni, "A Mathematical Model for the Validation of Gene Selection Methods," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. , pp. 1385-1392, 2010.
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