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Paper ID: 2681

Mining spatial gene expression data for association rules
van Hemert,J.I. Baldock,R.A. ,

Appeared in: Lecture Notes in Bioinformatics,
Page Numbers:66--76
Publisher: Springer Verlag
Year: 2007
ISBN/ISSN:
Contributing Organisation(s):
Field of Science: e-Science

URL: http://dx.doi.org/10.1007/978-3-540-71233-6_6

Abstract: We analyse data from the Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) which is a high quality data source for spatio-temporal gene expression patterns. Using a novel process whereby generated patterns are used to probe spatially-mapped gene expression domains, we are able to get unbiased results as opposed to using annotations based predefined anatomy regions. We describe two processes to form association rules based on spatial configurations, one that associates spatial regions, the other associates genes.

Keywords: data mining, biomedical, DGEMap, e-Science,


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