Development of advanced techniques for biological network visualization is crucial for successful progress in the areas of systems-level biology and data-intensive bioinformatics. However, current techniques for biological network visualization fall short of expectations for representing extensive biological networks. In order to provide useful network visualization tools, new approaches have to be proposed and applied alongside with those most powerful features of current visualization systems. The resulting representation techniques have to be tested by applying to large-scale examples that would include metabolic, signaling and gene expression events.