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Related Experiment Videos

EMAP and EMAGE: a framework for understanding spatially organized data.

Richard A Baldock1, Jonathan B L Bard, Albert Burger

  • 1MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh, UK. Richard.Baldock@hgu.mrc.ac.uk

Neuroinformatics
|March 27, 2004
PubMed
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The Edinburgh MouseAtlas Project (EMAP) offers a 3D spatial framework for mouse embryo development. The associated EMAGE database maps gene expression data, aiding research into complex spatial patterns and developmental biology.

Area of Science:

  • Developmental Biology
  • Bioinformatics
  • Genomics

Background:

  • The Edinburgh MouseAtlas Project (EMAP) provides a time-series of 3D volumetric models of mouse embryos.
  • These models offer a context-free spatial framework for mapping anatomical structures and experimental data.
  • Existing methods for spatial data analysis lack integrated temporal and anatomical context.

Purpose of the Study:

  • To describe the principles behind the Edinburgh MouseAtlas Project (EMAP) and the Edinburgh Mouse Atlas Gene-Expression Database (EMAGE).
  • To provide a practical introduction to using EMAP and EMAGE tools for spatial data analysis.
  • To introduce new techniques for whole-body gene expression data capture and mapping.

Main Methods:

  • Development of a time-series of mouse embryo volumetric models (EMAP).

Related Experiment Videos

  • Creation of a time-dependent anatomical ontology linked to the spatial models.
  • Integration of gene expression data into the EMAGE database with mapping and query tools.

    • Main Results:

    • EMAP provides a comprehensive spatial and temporal framework for mouse embryo anatomy.
    • EMAGE enables spatially mapped gene expression data analysis, facilitating comparisons.
    • New techniques for whole-body gene expression data capture and mapping have been developed.

    Conclusions:

    • EMAP and EMAGE provide powerful, integrated tools for analyzing complex spatial and temporal biological data.
    • These resources enhance the study of gene expression patterns during mouse embryonic development.
    • The framework supports advanced data visualization, collation, and query for developmental biology research.