Elastic Nets for Detection of Up-Regulated Genes in Microarrays
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.
KeywordsElastic net microarrays up-regulated genes clusters
Unable to display preview. Download preview PDF.
- 1.Molla, M., Waddell, M., Page, D., Shavlik, J.: Using machine learning to design and interpret gene-expression microarrays. Artificial Intelligence Magazine 25, 23–44 (2004)Google Scholar
- 4.Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S., Dmitrovsky, E., Lander, E., Golub, T.: Interpreting patterns of expression with self-organizing maps: Methods and application to hematopoietic differentiation. Genetics 96, 2907–2912 (1999)Google Scholar
- 7.Duda, R., Hart, P., Stork, D.: Pattern classification. John Wiley Sons Inc. (2001)Google Scholar