Visualizing Temporal Dynamics at the Genomic and Metabolic Level

We present an application for integrated visualization of gene expression data from time series experiments in gene regulation networks and metabolic networks. Such integration is necessary, since it provides the link between the measurements at the transcriptional level and the observable characteristics of an organism at the functional level. Our application can (i) visualize the data from time series experiments in the context of a regulatory network and a metabolic network; (ii) identify and visualize active regulatory subnetworks from the gene expression data; (iii) perform a statistical test to identify and subsequently visualize affected metabolic subnetworks. Initial results show that our integrated approach speeds up data analysis, and that it can reproduce results of a traditional approach that involves many manual and time-consuming steps.