Towards the Visualization of Multivariate Biochemical Networks
Ilir Jusufi · 2012
Many open challenges exist when dealing with different biological networks. They are crucial for the understanding of living beings. Complete drawings of these typically large networks usually suffer from clutter and visual overload. In order to overcome this issue, the networks are divided into single, hierarchically structured pathways. However, this subdivision makes it harder to navigate and understand the connections between pathways. Another challenge is to visualize ontologies and hierarchical clusterings, which are important tools to study high-throughput data that are automatically generated nowadays. Both of these methods produce different types of large graphs. Although these methods are used to explore the same data set, they are usually considered independently. Therefore, a combined view showing the results of both methods is desired. Additionally, real life data sets, including biological networks, usually have additional attributes related to the considered network. Investigating means to visualize such multivariate data together with the network drawing is also one of the ongoing challenges in biology, but also in other fields.