Recursive clustering for graph-based gene expression data
نویسندگان
چکیده
A recent trend of research uses graphs to modelize experimental microarray data. Recently, we used graph separators to group a set of 40 genes from a yeast database of Saccharomyces cerevisiae into very coherent clusters. Here, we extend our investigation to all 518 genes of S. cerevisiae which have reacted during the sporulation process. We propose a recursive decomposition into coherent clusters as well as a novel visualization of the data as a metagraph of clusters.
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