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» Clustering gene expression patterns
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BMCBI
2005
190views more  BMCBI 2005»
14 years 9 months ago
An Entropy-based gene selection method for cancer classification using microarray data
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Xiaoxing Liu, Arun Krishnan, Adrian Mondry
BMCBI
2007
132views more  BMCBI 2007»
14 years 10 months ago
Analysis of probe level patterns in Affymetrix microarray data
Background: Microarrays have been used extensively to analyze the expression profiles for thousands of genes in parallel. Most of the widely used methods for analyzing Affymetrix ...
Alexander C. Cambon, Abdelnaby Khalyfa, Nigel G. F...
BMCBI
2002
99views more  BMCBI 2002»
14 years 9 months ago
FunSpec: a web-based cluster interpreter for yeast
Background: For effective exposition of biological information, especially with regard to analysis of large-scale data types, researchers need immediate access to multiple categor...
Mark D. Robinson, Jörg Grigull, Naveed Mohamm...
BMCBI
2010
153views more  BMCBI 2010»
14 years 10 months ago
GOAL: A software tool for assessing biological significance of genes groups
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
BMCBI
2008
159views more  BMCBI 2008»
14 years 10 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...