Time series data clustered by self-organizing maps. Wildtype barley (Hordeum vulgare) caryopses were harvested every second day over a growth period of about 20 days post anthesis and analyzed for the dynamical changes of several central metabolites. The data set was mapped onto a network that was previously created in VANTED. Each node represents a metabolite, connected by solid and dashed lines that represent single and lumped enzyme reactions, respectively. Data are means of two independent plants, the standard error of the mean (SEM) is shown as a polygon around the line. A self-organizing map algorithm was performed to cluster the metabolites into three groups by similar behavior over time, which is visualized by the background color.
Junker et al. BMC Bioinformatics 2006 7:109 doi:10.1186/1471-2105-7-109