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Related Experiment Video

Updated: Mar 31, 2026

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
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Developing the eHistology Atlas.

Lorna Richardson1, Liz Graham1, Julie Moss1

  • 1MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK.

Database : the Journal of Biological Databases and Curation
|October 27, 2015
PubMed
Summary
This summary is machine-generated.

The eHistology Atlas provides high-resolution digital images of mouse development histology slides. This resource links anatomical annotations to gene expression databases for enhanced research accessibility.

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Area of Science:

  • Developmental Biology
  • Bioinformatics
  • Digital Pathology

Background:

  • The 'Atlas of Mouse Development' by Matthew H. Kaufman is a key resource in mouse developmental biology.
  • Access to high-resolution histology slides and associated annotations is crucial for detailed anatomical studies.
  • Integrating diverse biological data resources enhances research capabilities.

Purpose of the Study:

  • To create a digital, web-accessible resource of high-resolution histology slides from 'The Atlas of Mouse Development'.
  • To link digitized histology images with standardized anatomical ontologies and gene expression databases.
  • To leverage advanced imaging technology for a dynamic and extensible biological atlas.

Main Methods:

  • Digitization of original histology slides from 'The Atlas of Mouse Development'.
  • Capture and assignment of anatomy annotations to a standard reference anatomy ontology.
  • Development of a web environment utilizing IIP3D technology for image data delivery.
  • Integration with existing biological databases such as Edinburgh Mouse Atlas Gene-Expression (EMAGE) and Mouse Genome Informatics (MGI) gene-expression database (GXD).

Main Results:

  • Generation of a new resource, the eHistology Atlas, offering high-resolution color images of mouse development slides.
  • Successful linking of anatomical annotations to a reference ontology, enabling data interoperability.
  • Establishment of connectivity with key gene expression databases (EMAGE and GXD).
  • Implementation of IIP3D technology for efficient delivery and potential future expansion of the image dataset.

Conclusions:

  • The eHistology Atlas provides a valuable, high-resolution digital repository of mouse developmental histology.
  • The resource enhances research by linking visual anatomy data with gene expression information.
  • The underlying technology supports future data integration and expansion, promoting a dynamic research tool.