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CSDA
2008
128views more  CSDA 2008»
13 years 9 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
BMCBI
2006
186views more  BMCBI 2006»
13 years 8 months ago
Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
Background: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments....
Xiaoli Li, Yin-Chet Tan, See-Kiong Ng
IJON
2008
128views more  IJON 2008»
13 years 8 months ago
Independent arrays or independent time courses for gene expression time series data analysis
In this paper we apply three different independent component analysis (ICA) methods, including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to gene exp...
Sookjeong Kim, Jong Kyoung Kim, Seungjin Choi
BMCBI
2006
167views more  BMCBI 2006»
13 years 8 months ago
GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributi
Background: The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficu...
Jason M. Doherty, Lynn K. Carmichael, Jason C. Mil...
JBI
2004
171views Bioinformatics» more  JBI 2004»
13 years 10 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...