EMAP and EMAGE: a framework for understanding spatially organized data

Richard A Baldock, Jonathan B L Bard, Albert Burger, Nicolas Burton, Jeff Christiansen, Guanjie Feng, Bill Hill, Derek Houghton, Matthew Kaufman, Jianguo Rao, James Sharpe, Allyson Ross, Peter Stevenson, Shanmugasundaram Venkataraman, Andrew Waterhouse, Yiya Yang, Duncan R Davidson

Research output: Contribution to journalArticlepeer-review

Abstract

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.
Original languageEnglish
Pages (from-to)309-25
Number of pages17
JournalNeuroinformatics
Volume1
Issue number4
DOIs
Publication statusPublished - 2003

Keywords

  • Animals
  • Programming Languages
  • Computer Graphics
  • Gene Expression
  • Mice
  • Online Systems
  • Computational Biology
  • Information Storage and Retrieval
  • Atlases as Topic
  • Databases, Factual
  • Embryo, Mammalian
  • Image Processing, Computer-Assisted
  • Models, Anatomic

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