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Related Experiment Videos

The Omics Dashboard for interactive exploration of gene-expression data.

Suzanne Paley1, Karen Parker2, Aaron Spaulding1

  • 1Bioinformatics Research Group, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA.

Nucleic Acids Research
|October 18, 2017
PubMed
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The Omics Dashboard offers interactive gene-expression analysis, visualizing cellular system responses to stimuli. This tool aids in discovering gene expression changes potentially missed by traditional statistical methods.

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Gene-expression datasets are complex and require advanced analytical tools.
  • Traditional statistical methods may not capture all biologically relevant changes in gene expression.
  • Visualizing gene expression across cellular systems provides a holistic view of cellular responses.

Purpose of the Study:

  • To introduce the Omics Dashboard, a novel software tool for interactive gene-expression data exploration.
  • To demonstrate the utility of the Omics Dashboard in identifying gene expression patterns missed by statistical methods.
  • To showcase the application of the Omics Dashboard in analyzing specific biological case studies.

Main Methods:

  • The Omics Dashboard organizes gene-expression data into a hierarchical structure of cellular systems.

Related Experiment Videos

  • It utilizes graphical panels and X-Y plots to visualize expression levels of systems and subsystems.
  • The tool facilitates a top-down survey of cellular system responses to stimuli.

    • Main Results:

    • The Omics Dashboard enables rapid, interactive exploration of gene-expression datasets.
    • It successfully identified gene expression changes overlooked by conventional statistical analyses in case studies.
    • Case studies on *Thalassiosira pseudonana* lipid production and *Escherichia coli* growth shift demonstrated the tool's effectiveness.

    Conclusions:

    • The Omics Dashboard is a valuable complementary tool for gene-expression analysis.
    • Its visual approach enhances the understanding of cellular system responses.
    • The software aids in discovering subtle yet significant gene expression alterations.