Eurographics/ IEEE-VGTC Symposium on Visualization 2008 A. Vilanova, A. Telea, G. Scheuermann, andT. Möller (Guest Editors) Volume 27 (2008), Number 3 Visualizing Genome Expression and Regulatory Network Dynamics in Genomic and Metabolic Context M. A. Westenberg 1 , S. A. F. T. van Hijum 2,3 , O. P. Kuipers 2 , J. B. T. M. Roerdink 1 1 Institute for Mathematics and Computing Science, University of Groningen, P.O. Box 407, 9700 AK Groningen, The Netherlands 2 Department of Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, P.O. Box 14, 7950 AA Haren, The Netherlands 3 Interfacultary Centre for Functional Genomics, Ernst-Moritz-Arndt-Universität, Greifswald 17489, Germany Abstract DNA microarrays are used to measure the expression levels of thousands of genes simultaneously. In a time series experiment, the gene expressions are measured as a function of time. We present an application for integrated visualization of genome expression and network dynamics in both regulatory networks and metabolic pathways. Integration of these two levels of cellular processes is necessary, since it provides the link between the measure- ments at the transcriptional level (gene expression levels approximated from microarray data) and the phenotype (the observable characteristics of an organism) at the functional and behavioral level. The integration requires visualization approaches besides traditional clustering and statistical analysis methods. Our application can (i) visualize the data from time series experiments in the context of a regulatory network and KEGG metabolic path- ways; (ii) identify and visualize active regulatory subnetworks from the gene expression data; (iii) perform a statistical test to identify and subsequently visualize pathways that are affected by differentially expressed genes. We present a case study, which demonstrates that our approach and application both facilitates and speeds up data analysis tremendously in comparison to a more traditional approach that involves many manual, laborious, and error-prone steps. Categories and Subject Descriptors (according to ACM CCS): I.3.8 [Computer Graphics]: Applications, J.3 [Life and Medical Sciences]: Biology and genetics 1. Introduction Integration of biological interaction processes, which not only take place at genomic, proteomic, and metabolomic lev- els, but also between these levels, is important in systems biology. Software frameworks are established that visualize such interaction networks, and which offer interactive explo- ration to a researcher [BBO * 06]. In this paper, we consider visualization of gene regula- tory networks and pathways. Gene regulatory networks can be represented by graphs, in which nodes represent genes, and edges represent interactions between a gene product (a regulator protein) and its target genes. The nodes may have several attributes, such as position on the chromosome, and gene expression attributes for multiple time points together with p-values indicating statistical significance. Biologists also study how genes, gene products, enzyme reactions, and compounds form together a pathway, which is made up of chemical reactions that catalyze transforma- tion of compounds. Compounds are central building blocks in cellular components, energy storage, and are often used in intra- and extra-cellular signalling. A well-established an- notation system of pathways is provided by the Kyoto Ency- clopedia of Genes and Genomes (KEGG) [OGK * 00]. It cov- ers a wide range of organisms, and its manually constructed pathway drawings are similar to textbook pictures. Despite the existence of many tools for visualizing the various types of biological networks, a recent review paper c  2008 The Author(s) Journal compilation c 2008 The Eurographics Association and Blackwell Publishing Ltd. Published by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.