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BMCBI
2006
134views more  BMCBI 2006»
13 years 8 months ago
An approach for clustering gene expression data with error information
Background: Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated g...
Brian Tjaden
BMCBI
2005
152views more  BMCBI 2005»
13 years 8 months ago
CoPub Mapper: mining MEDLINE based on search term co-publication
Background: High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to ...
Blaise T. F. Alako, Antoine Veldhoven, Sjozef van ...
BMCBI
2007
126views more  BMCBI 2007»
13 years 8 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
BMCBI
2007
140views more  BMCBI 2007»
13 years 8 months ago
Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets
Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles...
Michael Gormley, William Dampier, Adam Ertel, Bilg...
BMCBI
2004
135views more  BMCBI 2004»
13 years 8 months ago
Determination of the differentially expressed genes in microarray experiments using local FDR
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...
Julie Aubert, Avner Bar-Hen, Jean-Jacques Daudin, ...