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BMCBI
2006
183views more  BMCBI 2006»
14 years 9 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
BMCBI
2007
168views more  BMCBI 2007»
14 years 9 months ago
GOSim - an R-package for computation of information theoretic GO similarities between terms and gene products
Background: With the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data. During the...
Holger Fröhlich, Nora Speer, Annemarie Poustk...
KDD
2002
ACM
183views Data Mining» more  KDD 2002»
15 years 10 months ago
E-CAST: A Data Mining Algorithm for Gene Expression Data
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
14 years 11 months ago
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
Microarray experiments have been extensively used for simultaneously measuring DNA expression levels of thousands of genes in genome research. A key step in the analysis of gene e...
Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvri...
APBC
2004
164views Bioinformatics» more  APBC 2004»
14 years 11 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