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ISNN
2004
Springer
14 years 1 months ago
A Novel Clustering Analysis Based on PCA and SOMs for Gene Expression Patterns
This paper proposes a novel clustering analysis algorithm based on principal component analysis (PCA) and self-organizing maps (SOMs) for clustering the gene expression patterns. T...
Hong-Qiang Wang, De-Shuang Huang, Xing-Ming Zhao, ...
IJSI
2008
122views more  IJSI 2008»
13 years 8 months ago
Mining Gene Expression Data using Domain Knowledge
Biology is now an information-intensive science and various research areas, like molecular biology, evolutionary biology or environmental biology, heavily depend on the availabilit...
Nicolas Pasquier, Claude Pasquier, Laurent Brisson...
BMCBI
2008
133views more  BMCBI 2008»
13 years 8 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...
EVOW
2005
Springer
14 years 1 months ago
Order Preserving Clustering over Multiple Time Course Experiments
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Stefan Bleuler, Eckart Zitzler
BMCBI
2010
115views more  BMCBI 2010»
13 years 8 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,...