An Improved Algorithm for Clustering Gene Expression Data Using Minimum Spanning Trees

Abstract:

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Genes are classified in order to understanding the categories of animals and plants, and to getting the knowledge about their connatural structures in the research of the biology. It is important to use clustering methods to recognize and classify modes of gene expression data effectively for studying the relationship between different species of genes. In this paper, an improved algorithm for clustering gene expression data based on Minimum Spanning Tree (MST) is proposed. The improved algorithm mainly uses direct clustering and recursive calculation method to shorten the running time. According to the results of the experiments, Through the use of multiple data sets, the results show that the improved algorithm than the original algorithm is greatly increased in the running time.

Info:

Periodical:

Edited by:

Honghua Tan

Pages:

2656-2661

DOI:

10.4028/www.scientific.net/AMM.29-32.2656

Citation:

W. L. Zhao and Z. G. Zhang, "An Improved Algorithm for Clustering Gene Expression Data Using Minimum Spanning Trees", Applied Mechanics and Materials, Vols. 29-32, pp. 2656-2661, 2010

Online since:

August 2010

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Price:

$35.00

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