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» The Expression Problem Revisited
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108
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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
135
Voted
BMCBI
2010
158views more  BMCBI 2010»
15 years 3 months ago
Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing
Background: Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorit...
Corey M. Yanofsky, David R. Bickel
137
Voted
BMCBI
2008
142views more  BMCBI 2008»
15 years 3 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
124
Voted
BMCBI
2008
158views more  BMCBI 2008»
15 years 3 months ago
Analyzing M-CSF dependent monocyte/macrophage differentiation: Expression modes and meta-modes derived from an independent compo
Background: The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and ...
Dominik Lutter, Peter Ugocsai, Margot Grandl, Evel...
127
Voted
BMCBI
2007
138views more  BMCBI 2007»
15 years 3 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...