Exploring Microbial Genome Sequences to Identify Protein Families on the Grid

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 developm...

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Bibliographic Details
Published in:IEEE journal of biomedical and health informatics 2007-07, Vol.11 (4), p.435-442
Main Authors: Yudong Sun, Wipat, A., Pocock, M., Lee, P.A., Flanagan, K., Worthington, J.T.
Format: Article
Language:English
Subjects:
Antibiotics
Bacterial Proteins - classification
Bacterial Proteins - genetics
Bioinformatics
Chromosome Mapping - methods
Computer architecture
Computer interfaces
Databases, Protein
Distributed computing
Distributed databases
Drugs
Genome analysis
Genome, Bacterial - genetics
Genomics
grid
Information Storage and Retrieval - methods
Internet
Large-scale systems
microbial genomes
Multigene Family - genetics
Protein engineering
protein families
Web services
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Summary: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.
ISSN:1089-7771
2168-2194
1558-0032
2168-2208
DOI:10.1109/TITB.2007.892913