Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

11

BIRD
2007
Springer

favoriteEmaildiscussreport

154views Bioinformatics» more BIRD 2007»

Mining Spatial Gene Expression Data for Association Rules

13 years 10 months ago

Mining Spatial Gene Expression Data for Association Rules

Download www.vanhemert.co.uk

Abstract. We analyse data from the Edinburgh Mouse Atlas GeneExpression 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.

Jano I. van Hemert, Richard A. Baldock

Real-time Traffic

Bioinformatics | BIRD 2007 | Gene Expression | Gene Expression Patterns | Spatially-mapped Gene Expression |

claim paper

Related Content

» GenMiner mining nonredundant association rules from integrated gene expression data and an...

» Distanceenhanced association rules for gene expression

» Integrated analysis of gene expression by association rules discovery

» Semantic Mining and Analysis of Gene Expression Data

» Mining Association Rule Bases from Integrated Genomic Data and Annotations

» GenMiner Mining Informative Association Rules from Genomic Data

» Mining Topk Covering Rule Groups for Gene Expression Data

» Scalable RuleBased Gene Expression Data Classification

» Unifying Framework for Rule Semantics Application to Gene Expression Data

Post Info
More Details (n/a)

Added	07 Jun 2010
Updated	07 Jun 2010
Type	Conference
Year	2007
Where	BIRD
Authors	Jano I. van Hemert, Richard A. Baldock

Comments (0)