| dc.creator | Lévano Huamaccto, Marcos | |
| dc.creator | Mellado Gatica, Alejandro | |
| dc.creator | Jayne, C | |
| dc.creator | Yue, S | |
| dc.creator | Iliadis, L | |
| dc.date | 2012 | |
| dc.date | 2021-04-30T16:30:25Z | |
| dc.date | 2021-04-30T16:30:25Z | |
| dc.date.accessioned | 2021-06-14T22:00:40Z | |
| dc.date.available | 2021-06-14T22:00:40Z | |
| dc.identifier | ENGINEERING APPLICATIONS OF NEURAL NETWORKS,Vol.311,183-192,2012 | |
| dc.identifier | http://repositoriodigital.uct.cl/handle/10925/2714 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3298615 | |
| dc.description | 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. | |
| dc.language | en | |
| dc.publisher | SPRINGER-VERLAG BERLIN | |
| dc.source | ENGINEERING APPLICATIONS OF NEURAL NETWORKS | |
| dc.subject | Elastic net | |
| dc.subject | microarrays | |
| dc.subject | up-regulated genes | |
| dc.subject | clusters | |
| dc.title | Elastic Nets for Detection of Up-Regulated Genes in Microarrays | |
| dc.type | Meeting | |
