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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., Availability: The Ondex yeast dataset and the OndexView plug-in for Cytoscape are accessible at http://bsu.ncl.ac.uk/ondexview.

The analysis of microbial genome sequences can identify protein families that provide potential drug targets for new antibiotics. With the rapid accumulation of newly sequenced genomes, this analysis has become a computationally intensive and data-intensive problem. This paper describes the development of a Web-service-enabled, component-based, architecture to support the large-scale comparative analysis of complete microbial genome sequences and the subsequent identification of orthologues and protein families (Microbase). The system is coordinated through the use of Web-service-based notifications and integrates distributed computing resources together with genomic databases to realize all-against-all comparisons for a large volume of genome sequences and to present the data in a computationally amenable format through a Web service interface. We demonstrate the use of the system in searching for orthologues and candidate protein families, which ultimately could lead to the identification of potential therapeutic targets.