Towards the Visualization of Multivariate Biochemical Networks

Sammanfattning:  Many open challenges exist when dealing with different biological networks. Theyare crucial for the understanding of living beings. Complete drawings of these typicallylarge networks usually suffer from clutter and visual overload. In order toovercome this issue, the networks are divided into single, hierarchically structuredpathways. However, this subdivision makes it harder to navigate and understand theconnections between pathways. Another challenge is to visualize ontologies andhierarchical clusterings, which are important tools to study high-throughput datathat are automatically generated nowadays. Both of these methods produce differenttypes of large graphs. Although these methods are used to explore the samedata set, they are usually considered independently. Therefore, a combined viewshowing the results of both methods is desired. Additionally, real life data sets,including biological networks, usually have additional attributes related to the considerednetwork. Investigating means to visualize such multivariate data togetherwith the network drawing is also one of the ongoing challenges in biology, but alsoin other fields.The aim of this thesis is to lay out the foundations towards defining techniquesfor the visualization of multivariate biochemical networks. An overall understandingof the problems related to biochemical networks should be acquired to achievethis aim. More importantly, a contribution to the aforementioned challenges is necessary.Two research goals have been defined to accomplish our aim: for the firstgoal, we should improve shortcomings of the approach of dividing larger biologicalnetworks into smaller pieces and contribute to the problem of a visualization ofdifferent types of interconnected biological networks. The second goal is a contributionfor the visualization of multivariate biological networks.Initially, a brief survey on techniques to visualize multivariate networks is presentedin this thesis. Then, various visualization and interaction techniques are presentedthat address the challenges in biochemical network analysis. Three differentsoftware tools were implemented to demonstrate our research efforts. We discussall features of our systems in detail, describe the visualization and interaction techniquesas well as disadvantages and scalability issues if present.