Abstract
A combination of gene ranking, dimensional reduction, and recursive feature elimination (RFE) using a BP-MLP artificial neural network (ANN) was used to select genes for DNA microarray classification. Use of k-means cluster analysis for dimensional reduction and maximum sensitivity for RFE resulted in 64-gene models with fewer invariant and correlated features when compared with PCA and mimimum error. In conclusion, k-means cluster analysis and sensitivity may be better suited for classifying diseases for which gene expression is more strongly influenced by pathway heterogeneity.
| Original language | English (US) |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 267-276 |
| Number of pages | 10 |
| Volume | 3849 LNAI |
| State | Published - 2006 |
| Externally published | Yes |
| Event | 6th International Workshop - Fuzzy Logic and Applications - Crema, Italy Duration: Sep 15 2005 → Sep 17 2005 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3849 LNAI |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 6th International Workshop - Fuzzy Logic and Applications |
|---|---|
| Country | Italy |
| City | Crema |
| Period | 9/15/05 → 9/17/05 |
ASJC Scopus subject areas
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science
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Cite this
Peterson, L. E., & Coleman, M. A. (2006). Comparison of gene identification based on artificial neural network pre-processing with k-means cluster and principal component analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3849 LNAI, pp. 267-276). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3849 LNAI).