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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Use of q-values to Improve a Genetic Algorithm to Identify Robust Gene Signatures
verfasst von : Daniel Urda, Simon Chambers, Ian Jarman, Paulo Lisboa, Leonardo Franco, Jose M. Jerez
Erschienen in: Computational Intelligence Methods for Bioinformatics and Biostatistics
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Several approaches have been proposed for the analysis of DNA microarray datasets, focusing on the performance and robustness of the final feature subsets. The novelty of this paper arises in the use of q-values to pre-filter the features of a DNA microarray dataset identifying the most significant ones and including this information into a genetic algorithm for further feature selection. This method is applied to a lung cancer microarray dataset resulting in similar performance rates and greater robustness in terms of selected features (on average a 36.21% of robustness improvement) when compared to results of the standard algorithm.