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» E-CAST: A Data Mining Algorithm for Gene Expression Data
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PR
2008
88views more  PR 2008»
13 years 7 months ago
Modified global k
Clustering in gene expression data sets is a challenging problem. Different algorithms for clustering of genes have been proposed. However due to the large number of genes only a ...
Adil M. Bagirov
BMCBI
2010
216views more  BMCBI 2010»
13 years 2 months ago
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies
Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...
RECOMB
2008
Springer
14 years 8 months ago
Detecting Disease-Specific Dysregulated Pathways Via Analysis of Clinical Expression Profiles
We present a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. These subnetworks provide a signat...
Igor Ulitsky, Richard M. Karp, Ron Shamir
ICPR
2006
IEEE
14 years 9 months ago
Exploiting the Geometry of Gene Expression Patterns for Unsupervised Learning
Typical gene expression clustering algorithms are restricted to a specific underlying pattern model while overlooking the possibility that other information carrying patterns may ...
Rave Harpaz, Robert M. Haralick
BIOINFORMATICS
2007
66views more  BIOINFORMATICS 2007»
13 years 8 months ago
Gene expression network analysis and applications to immunology
We address the problem of using expression data and prior biological knowledge to identify differentially expressed pathways or groups of genes. Following an idea of Ideker et al...
Serban Nacu, Rebecca Critchley-Thorne, Peter Lee, ...