Pattern classification in DNA microarray data of multiple tumor types
Resource
Pattern Recognition 39 (12): 2426-2438
Journal
Pattern Recognition
Journal Volume
39
Journal Issue
12
Pages
2426-2438
Date Issued
2006
Author(s)
Abstract
In this paper, we propose a genetic algorithm with silhouette statistics as discriminant function (GASS) for gene selection and pattern recognition. The proposed method evaluates gene expression patterns for discriminating heterogeneous cancers. Distance metrics and classification rules have also been analyzed to design a GASS with high classification accuracy. Moreover, the proposed method is compared to previously published methods. Various experimental results show that our method is effective for classifying the NCI60, the GCM and the SRBCTs datasets. Moreover, GASS outperforms other existing methods in both the leave-one-out cross validations and the independent test for novel data. ? 2006 Pattern Recognition Society.
Subjects
Cancer classification; Gene expression profiling; Genetic algorithm; Silhouette statistics
Other Subjects
Data reduction; Data structures; DNA; Genes; Genetic algorithms; Pattern recognition; Cancer classification; Gene expression profiling; Silhouette statistics; Tumors
Type
journal article
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