Abstract
Interpretation of DNA microarray data sets requires tools that enable us to obtain appropriate coexpression clusters. Here, we propose tools of network analysis to systematically analyze gene coexpression using many DNA microarray data sets of Arabidopsis instead of cluster analysis.
Computational analysis was performed using correlation coefficient data file between gene expressions that was calculated from 771 DNA microarrays. Genes which show high correlation coefficient and are highly specific to targeted genes over adequate threshold were selected as coexpressed candidate genes. The present tools were applied to genes related to secondary metabolism in Arabidopsis to validate adequate threshold setting.
In the majority of the applied genes related to secondary metabolism, coexpressed candidate genes were successfully expected by setting adequate threshold of correlation coefficient and specificity to each target gene.
