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Nucleic Acids Research Advance Access published online on September 18, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp763
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© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Database Issue

EMAGE mouse embryo spatial gene expression database: 2010 update

Lorna Richardson, Shanmugasundaram Venkataraman, Peter Stevenson, Yiya Yang, Nicholas Burton, Jianguo Rao, Malcolm Fisher, Richard A. Baldock, Duncan R. Davidson and Jeffrey H. Christiansen*

MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh EH4 2XU, UK

*To whom correspondence should be addressed. Tel: +44 131 332 2471; Fax +44 131 467 8456; Email: Jeff.Christiansen{at}hgu.mrc.ac.uk

Received August 27, 2009. Accepted August 31, 2009.

EMAGE (http://www.emouseatlas.org/emage) is a freely available online database of in situ gene expression patterns in the developing mouse embryo. Gene expression domains from raw images are extracted and integrated spatially into a set of standard 3D virtual mouse embryos at different stages of development, which allows data interrogation by spatial methods. An anatomy ontology is also used to describe sites of expression, which allows data to be queried using text-based methods. Here, we describe recent enhancements to EMAGE including: the release of a completely re-designed website, which offers integration of many different search functions in HTML web pages, improved user feedback and the ability to find similar expression patterns at the click of a button; back-end refactoring from an object oriented to relational architecture, allowing associated SQL access; and the provision of further access by standard formatted URLs and a Java API. We have also increased data coverage by sourcing from a greater selection of journals and developed automated methods for spatial data annotation that are being applied to spatially incorporate the genome-wide (~19 000 gene) ‘EURExpress’ dataset into EMAGE.


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