Kernel principal component analysis (KPCA) has been applied to data clustering and graphic cut in the last couple of years. This paper discusses the application of KPCA to microarray data clustering. A new algorithm based on KPCA and fuzzy C-means is proposed. Experiments with microarray data show that the proposed algorithms is in general superior to traditional algorithms.
|Original language||English (US)|
|Number of pages||14|
|Journal||Journal of Bioinformatics and Computational Biology|
|State||Published - Apr 1 2005|
All Science Journal Classification (ASJC) codes
- Molecular Biology
- Computer Science Applications