The Clustering Algorithm Study of Gene Expression Data

Rui He; Chun Mei Lin

doi:10.4028/www.scientific.net/AMR.183-185.93

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 183-185The Clustering Algorithm Study of Gene Expression...

The Clustering Algorithm Study of Gene Expression Data

Abstract:

This paper proposes an evolutionary self-organized clustering method of genes based on undirected graph expression. In this method, we use the vertices of the graph to represent genes, and regard the weight between two vertices as similarity measurement of two genes. Thus, the similarities among genes can be extracted according to the space feature of graph with immune evolutionary method. To demonstrate the effectiveness of the proposed method, the method is tested on yeast cell cycle expression dataset; the results suggest that this method is capable of clustering genes.

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Periodical:

Advanced Materials Research (Volumes 183-185)

Pages:

93-98

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.183-185.93

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Online since:

January 2011

Authors:

Rui He, Chun Mei Lin

Keywords:

Clustering, Gene Expression Data, Immune Algorithm, Undirected Graph

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