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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Elastic Nets for Detection of Up-Regulated Genes in Microarrays
verfasst von : Marcos Levano, Alejandro Mellado
Erschienen in: Engineering Applications of Neural Networks
Verlag: Springer Berlin Heidelberg
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DNA analysis by microarrays is a powerful tool that allows replication of the RNA of hundreds of thousands of genes at the same time, generating a large amount of data in multidimensional space that must be analyzed using informatics tools. Various clustering techniques have been applied to analyze the microarrays, but they do not offer a systematic form of analysis. This paper proposes the use of Zinovyev’s
Elastic Net
in an iterative way to find patterns of up-regulated genes. The new method proposed has been evaluated with up-regulated genes of the Escherichia Coli k12 bacterium and is compared with the Self-Organizing Maps (SOM) technique frequently used in this kind of analysis. The results show that the proposed method finds
87%
of the up-regulated genes, compared to
65%
of genes found by the SOM. A comparative analysis of Receiver Operating Characteristic with SOM shows that the proposed method is
12%
more effective.