Building Workflows that Traverse the Bioinformatics Data Landscape

Robert Stevens, Paul Fisher, Jun Zhao, Carole Goble, Andy Brass

    Research output: Chapter in Book/Conference proceedingChapter

    Abstract

    Summary: The bioinformatics data landscape confronts scientists with significant problems when performing data analyses. The nature of these analyses is, in part, driven by the data landscape. This raises issues in managing the scientific process of in silico experimentation in bioinformatics. The myGrid project has addressed these issues through workflows. Although raising some issues of their own, workflows have allowed scientists to effectively traverse the bioinformatics landscape. The high-throughput nature of workflows, however, has forced us to move from a task of data gathering to data gathering and management. Utilizing workflows in this manner has enabled a systematic, unbiased, and explicit approach that is less susceptible to premature triage. This has profoundly changed the nature of bioinformatics analysis. Taverna is illustrated through an example from the study of trypanosomiasis resistance in the mouse model. In this study novel biological results were obtained from traversing the bioinformatics landscape with workflow. © 2008 John Wiley & Sons, Ltd.
    Original languageEnglish
    Title of host publicationData Mining Techniques in Grid Computing Environments|Data Min. Tech. in Grid Computing Environments
    PublisherJohn Wiley & Sons Ltd
    Pages141-163
    Number of pages22
    DOIs
    Publication statusPublished - 22 Jun 2009

    Keywords

    • Bioinformatics data landscape
    • Building workflows and bioinformatics data landscape
    • KEGG pathway database
    • MyGrid's Taverna and workflow management system
    • SCUFL model and Taverna workflow
    • Taverna in bioinformatics experiment
    • Taverna user interface and workflow design support
    • Workflow case study

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