Abstract
The emergence of systems biology necessitates development of platforms to organise and interpret plentitude of biological data. We present a system to integrate data across multiple bioinformatics databases and enable mining across various conceptual levels of biological information. The results are represented as complex networks. Context dependent mining of these networks is achieved by use of distances. Our approach is demonstrated with three applications: full metabolic network retrieval with network topology study, exploration of properties and relationships of a set of selected proteins, and combined visualisation and exploration of gene expression data with related pathways and ontologies.
Original language | English |
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Pages (from-to) | 54-77 |
Journal | International Journal of Data Mining and Bioinformatics |
Volume | 2 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2008 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Bioinformatics
- Complex networks
- Data mining
- Heterogeneous database integration
- Systems biology