Abstract
Fuzzy clustering is a useful tool for identifying relevant subsets of microarray data. This paper proposes a fuzzy clustering method for microarray data analysis. An advantage of the method is that it used a combination of the fuzzy c-means and the principal component analysis to identify the groups of genes that show similar expression patterns. It allows a gene to belong to more than a gene expression pattern with different membership grades. The method is suitable for the analysis of large amounts of noisy microarray data. © 2008 IMechE.
| Original language | English |
|---|---|
| Pages (from-to) | 1143-1148 |
| Journal | Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine |
| Volume | 222 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 1 Oct 2008 |
Research Keywords
- fuzzy c-means
- fuzzy clustering
- gene expression data analysis
- principal component analysis
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