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BMCBI
2006
134views more  BMCBI 2006»
13 years 5 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
BIBE
2007
IEEE
195views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Finding Clusters of Positive and Negative Coregulated Genes in Gene Expression Data
— In this paper, we propose a system for finding partial positive and negative coregulated gene clusters in microarray data. Genes are clustered together if they show the same p...
Kerstin Koch, Stefan Schönauer, Ivy Jansen, J...
BMCBI
2007
126views more  BMCBI 2007»
13 years 5 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...
APBC
2004
164views Bioinformatics» more  APBC 2004»
13 years 6 months ago
Cluster Ensemble and Its Applications in Gene Expression Analysis
Huge amount of gene expression data have been generated as a result of the human genomic project. Clustering has been used extensively in mining these gene expression data to find...
Xiaohua Hu, Illhoi Yoo
BMCBI
2010
115views more  BMCBI 2010»
13 years 5 months ago
Importance of replication in analyzing time-series gene expression data: Corticosteroid dynamics and circadian patterns in rat l
Background: Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However...
Tung T. Nguyen, Richard R. Almon, Debra C. DuBois,...