Figure 3.

Fuzzy clustering of the expression data along seed development series. The six clusters showing the expression patterns during Arabidopsis seed development. The gene expression values were standardized to have a mean value of zero and a standard deviation of one for each gene profile. The transformed expressions were then clustered using the fuzzy c-means (FCM) clustering algorithm implemented in the Bioconductor Mfuzz package [89]. Based on preliminary analysis, we found six clusters can well represent different expression patterns inherent in the dataset, and another FCM parameter m = 1.75. A membership value in the range of 0-1 was assigned in clustering and the cluster cores consisting of genes with membership value > = 0.90 were coloured pink.