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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
BMCBI
2008
133views more  BMCBI 2008»
13 years 5 months ago
A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
Luca Corradi, Marco Fato, Ivan Porro, Silvia Scagl...
CINQ
2004
Springer
116views Database» more  CINQ 2004»
13 years 9 months ago
Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining
Abstract. One of the exciting scientific challenges in functional genomics concerns the discovery of biologically relevant patterns from gene expression data. For instance, it is e...
Ruggero G. Pensa, Jérémy Besson, C&e...
BMCBI
2006
100views more  BMCBI 2006»
13 years 5 months ago
Empirical array quality weights in the analysis of microarray data
Background: Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or &qu...
Matthew E. Ritchie, Dileepa S. Diyagama, Jody Neil...
BMCBI
2007
149views more  BMCBI 2007»
13 years 5 months ago
A unified framework for finding differentially expressed genes from microarray experiments
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...
Jahangheer S. Shaik, Mohammed Yeasin