Study On The Gene Chip Based On The Clustering Algorithm

Microarray technology is the chief tool for functional genomics research.Adopting the high efficient and parallel DNA hybridization technology, wecan achieve abundant data from each experiment, so the data analysis ofmicroarrays becomes a challenge and significant task. Clustering is the mostuseful and widely used method of microarray data analysis. Abundant usefulinformation can be obtained through the microarray clustering. There aremany successful examples that have been applied to a wide of biomedicalresearch in the various fields.This paper main research clustering algorithm based on gene chipresearch. In the study of gene chip data, the commonly used clusteringalgorithms are Hierarchical clustering, K-means clustering, SOM (Selforganizing map) and PCA (principle component analysis),and proposed aimprovement algorithm which based on the existing algorithm and has moreperfect performance—based on multi-dimensional Pseudo F-statisticsdynamic K-means clustering algorithm.In the clustering analysis application of gene chip data, this paper hasachieved the five algorithms and expression these five algorithms clusterresults direct-viewingly. Further, according to the cluster results of thecommon data set in the gene chip data research to carry on under these fivealgorithms to various algorithms performance has analyzed and compared.