MotifNetwork: Genome-wide domain analysis using grid-enabled workflows

Jeffrey L. Tilson, Alan Blatecky, Gloria Rendon, Mao Feng Ger, Eric Jakobsson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It has been recently demonstrated that the understanding of gene interactions, gene function and ultimately gene and organism evolutionary processes, is facilitated by determination of relationships among the constituent "domains" and "motifs." This understanding, however, comes at the expense of substantial computation necessary to support the required data mining. The detailed computations behind a typical domain and motif analysis are described in our recently developed grid-enabled environment called the MotifNetwork. In this work, the MotifNetwork is applied, for the first time, to large genome-wide association analysis of the entire Apis mellifera (honeybee) genome. Several impediments to this computation are identified including weaknesses in workflow creation and enactment capabilities and limitations in hardware capacity. Nonetheless, though generated in a non-optimum fashion, preliminary results of the honeybee analysis are presented. Lastly, suggestions for future work are summarized.

Original languageEnglish (US)
Title of host publicationProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Pages872-879
Number of pages8
DOIs
StatePublished - 2007
Event7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE - Boston, MA, United States
Duration: Jan 14 2007Jan 17 2007

Publication series

NameProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

Conference

Conference7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Country/TerritoryUnited States
CityBoston, MA
Period1/14/071/17/07

Keywords

  • Grid computing
  • High throughput genomics
  • Parallel processing
  • Workflow systems

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Bioengineering

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