Customizable views on semantically integrated networks for systems biology
Jochen Weile1, Matthew Pocock, Simon J Cockell
1School of Computing Science, Faculty of Science Agriculture and Engineering, Newcastle University, Newcastle upon Tyne, UK.
Bioinformatics (Oxford, England)
|March 19, 2011
Summary
We developed OndexView, a Cytoscape plugin, to visualize large Saccharomyces cerevisiae datasets. This tool aids in exploring complex biological data, such as telomere maintenance, for bioinformaticians.
Area of Science:
- Bioinformatics
- Systems Biology
- Computational Biology
Background:
- High-throughput technologies generate vast biological data, posing challenges for bioinformaticians.
- Integrating semantically rich datasets is a promising approach but often results in large, complex data.
- Interactive exploration and visualization of these integrated datasets remain difficult.
Purpose of the Study:
- To develop a method for visualizing and interactively exploring large, semantically integrated biological datasets.
- To create a tool that facilitates the investigation of complex biological processes using integrated data.
Main Methods:
- Utilized the semantic data integration tool Ondex to create an integrated dataset for Saccharomyces cerevisiae.
- Developed a view-based visualization technique implemented as a Cytoscape plug-in named OndexView.
- Applied OndexView to study telomere maintenance in S. cerevisiae.
Main Results:
- Successfully created an integrated Saccharomyces cerevisiae dataset and a visualization tool, OndexView.
- OndexView enables concise graphical representations of complex, integrated biological data.
- Demonstrated the utility of OndexView in investigating telomere maintenance pathways.
Conclusions:
- OndexView provides an effective solution for visualizing and exploring large, integrated biological datasets.
- The tool facilitates deeper insights into biological processes by enabling interactive data analysis.
- The Ondex yeast dataset and OndexView are publicly available for the research community.
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