Abstract
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.
| Original language | English |
|---|---|
| Qualification | Master Degree |
| Awarding Institution |
|
| Place of Publication | Espoo |
| Publisher | |
| Publication status | Published - 2005 |
| MoE publication type | G2 Master's thesis, polytechnic Master's thesis |
Keywords
- data visualizing and clustering
- robustness
- network topologies
- bioinformatics
- tiedon visualisointi ja klusterointi
- robustisuus
- verkkotopologiat
- bioinformatiikka