Exploring Microbial Genome Sequences to Identify Protein Families on the Grid

  1. Lookup NU author(s)
  2. Dr Yudong Sun
  3. Professor Anil Wipat
  4. Dr Matthew Pocock
  5. Professor Pete Lee
  6. Dr Keith Flanagan
  7. James Worthington
Author(s)Sun Y, Wipat A, Pocock M, Lee P, Flanagan K, Worthington J
Publication type Report
Series TitleSchool of Computing Science Technical Report Series
Year2005
Legacy DateOctober 2005
Report Number931
Pages8
Full text is available for this publication:
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, the analysis of complete genome sequences has become a computationally- and data-intensive problem which is intractable on common computer systems. This paper presents the Microbase project that has developed a Grid-based system to support large-scale comparative analysis of complete microbial genome sequences, and the identification of protein families based on the analysis. The system integrates Grid computing with genomic databases to provide a high-performance environment for efficient genome comparison, analysis and protein family search. A pre-computed dataset of sequence similarities and homologous protein families has been generated which can assist the discovery of new therapeutic agents and provide leads for drug development.
InstitutionSchool of Computing Science, University of Newcastle upon Tyne
Place PublishedNewcastle upon Tyne
URLhttp://www.cs.ncl.ac.uk/publications/trs/papers/931.pdf
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