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SDM
2007
SIAM
98views Data Mining» more  SDM 2007»
15 years 5 months ago
Lattice based Clustering of Temporal Gene-Expression Matrices
Individuals show different cell classes when they are in the different stages of a disease, have different disease subtypes, or have different response to a treatment or envir...
Yang Huang, Martin Farach-Colton
BMCBI
2008
142views more  BMCBI 2008»
15 years 4 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
BMCBI
2007
118views more  BMCBI 2007»
15 years 4 months ago
A new advance in alternative splicing databases: from catalogue to detailed analysis of regulation of expression and function of
Background: Most human genes produce several transcripts with different exon contents by using alternative promoters, alternative polyadenylation sites and alternative splice site...
Pierre de la Grange, Martin Dutertre, Margot Corre...
BMCBI
2006
126views more  BMCBI 2006»
15 years 4 months ago
OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments
Background: Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no...
Morgan N. Price, Adam P. Arkin, Eric J. Alm
BMCBI
2006
183views more  BMCBI 2006»
15 years 4 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...