A Clustering Algorithm for Gene Expression Data Based on Graph Theory

The development of the biological technology provides people the opportunities to obtain the information which hides in the gene expression data, however, the huge gene number and the complex biological network increase the difficulty of the comprehending and explaining of these information. Therefore, people introduced clustering algorithms to discover the significative gene patterns, and then we propose and analyze a clustering algorithm which based on graph theory. Proved by the experiment, this algorithm not only can analyze the gene expression data fast, but also get good clustering quality.