The current biological data is very diverse. It is located in different databases and it is presented in different ways. There are several biological databases with good visualization tools. However, there are very few tools that are able to retrieve data across multiple databases. It is thus very difficult to get a clear and overall picture of the complicated biological data. In this thesis we develop a Java application that is able to retrieve data from several biological databases. Based on the latest research it is assumed that a hierarchical modularity is present in metabolic networks. This fact has a very important role in the robustness arid error-tolerance of metabolic networks. However, it is unknown how this structure changes when we combine such networks with other types of biological interactions. We use the Sammon's mapping projection algorithm to investigate the structure of biological networks in Saccharomyces cerevisiae. First, we cluster metabolic pathways. Next, we combine metabolic pathways with protein-protein interaction networks. In high hierarchy levels there occur very strong mergers. In lower hierarchy levels the mergers are considerably weaker. Between high and low hierarchy levels there do not occur any mergers.
|Place of Publication||Espoo|
|Publication status||Published - 2005|
|MoE publication type||G2 Master's thesis, polytechnic Master's thesis|
- data visualizing and clustering
- network topologies
- tiedon visualisointi ja klusterointi