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» Semantic Mining and Analysis of Gene Expression Data
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BMCBI
2008
134views more  BMCBI 2008»
13 years 9 months ago
Clustering cancer gene expression data: a comparative study
Background The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have propose...
Marcílio Carlos Pereira de Souto, Ivan G. C...
BMCBI
2007
169views more  BMCBI 2007»
13 years 9 months ago
Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and i
Background: Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targ...
Abdallah Sayyed-Ahmad, Kagan Tuncay, Peter J. Orto...
SDM
2007
SIAM
98views Data Mining» more  SDM 2007»
13 years 10 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
2006
211views more  BMCBI 2006»
13 years 9 months ago
Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding s
Background: Gene expression profiling has become a useful biological resource in recent years, and it plays an important role in a broad range of areas in biology. The raw gene ex...
Xian Wang, Ao Li, Zhaohui Jiang, Huanqing Feng
BMCBI
2005
122views more  BMCBI 2005»
13 years 8 months ago
GenClust: A genetic algorithm for clustering gene expression data
Background: Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designe...
Vito Di Gesù, Raffaele Giancarlo, Giosu&egr...