Customizable views on semantically integrated networks for systems biology

Motivation: The rise of high-throughput technologies in the post-genomic era has led to the production of large amounts of biological data. Many of these datasets are freely available on the Internet. Making optimal use of these data is a significant challenge for bioinformaticians. Various strategies for integrating data have been proposed to address this challenge. One of the most promising approaches is the development of semantically rich integrated datasets. Although well suited to computational manipulation, such integrated datasets are typically too large and complex for easy visualization and interactive exploration. Results: We have created an integrated dataset for Saccharomyces cerevisiae using the semantic data integration tool Ondex, and have developed a view-based visualization technique that allows for concise graphical representations of the integrated data. The technique was implemented in a plug-in for Cytoscape, called OndexView. We used OndexView to investigate telomere maintenance in S. cerevisiae.