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Exploring microbial genome sequences to identify protein families on the grid.
Authors:Yudong Sun  Anil Wipat  Matthew Pocock  Peter A Lee  Keith Flanagan  James T Worthington
Affiliation:Newcastle University, Newcastle Upon Tyne, NE1 7RU, UK. yudong.sun@comlab.ox.ac.uk
Abstract: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.
Keywords:
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