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Mining spatial gene expression data for association rules

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TitleMining spatial gene expression data for association rules
Publication TypeConference Paper
Year of Publication2007
Authorsvan Hemert, JI, Baldock, RA
Conference NameLecture Notes in Bioinformatics
PublisherSpringer Verlag
EditorHochreiter, S, Wagner, R
Keywordsbiomedical; data mining; DGEMap; e-Science

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.

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