Bioinformatics analysis

Bioinformatics analysis with graph-based clustering to detect gastric cancer-related pathways

P. Liu, Wang, X., Hu, C. H., and Hu, T. H., Bioinformatics analysis with graph-based clustering to detect gastric cancer-related pathways, vol. 11, pp. 3497-3504, 2012.

Despite a dramatic reduction in incidence and mortality rates, gastric cancer still remains one of the most common malignant tumors worldwide, especially in China. We sought to identify a set of discriminating genes that could be used for characterization and prediction of response to gastric cancer. Using bioinformatics analysis, two gastric cancer datasets, GSE19826 and GSE2685, were merged to find novel target genes and domains to explain pathogenesis; we selected differentially expressed genes in these two datasets and analyzed their correlation in order to construct a network.

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