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The BioExtract Server: a web-based bioinformatic workflow platform.

Carol M Lushbough1, Douglas M Jennewein, Volker P Brendel

  • 1Department of Computer Science, University of South Dakota, Vermillion, SD 57069, USA. clushbou@usd.edu

Nucleic Acids Research
|May 7, 2011
PubMed
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The BioExtract Server offers a web-based platform for creating reproducible genomic data analysis workflows. Researchers can integrate diverse data sources and analytic tools for efficient bioinformatics research.

Area of Science:

  • Bioinformatics
  • Genomic Data Analysis
  • Computational Biology

Background:

  • Genomic data analysis requires complex workflows involving multiple data sources and tools.
  • Reproducibility and shareability of bioinformatics workflows are critical for scientific validation.
  • Existing systems may lack flexibility in integrating diverse data and computational resources.

Purpose of the Study:

  • To introduce the BioExtract Server, an open, web-based system for creating and executing bioinformatic workflows.
  • To provide researchers with a unified platform for genomic data analysis, integrating data querying and tool execution.
  • To enhance the reproducibility and shareability of scientific workflows in bioinformatics.

Main Methods:

  • The BioExtract Server records user tasks to build scientific workflows.

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  • It integrates data from multiple sources like NCBI, EMBL-Bank, UniProt, and UniRef.
  • Users can execute preinstalled tools, web services (EMBOSS, BioMoby, KEGG), and local command-line tools via a Java applet.

    • Main Results:

    • The system enables the creation of reproducible and sharable bioinformatic workflows.
    • It facilitates querying distributed genomic databases and saving results as searchable data extracts.
    • Researchers can execute a wide array of local and web-accessible analytic tools within a single platform.

    Conclusions:

    • The BioExtract Server provides a flexible and integrated solution for complex genomic data analysis.
    • It empowers researchers to build, share, and execute reproducible bioinformatics workflows, accelerating discovery.
    • The platform's ability to integrate diverse data and tools enhances the efficiency and reliability of genomic research.