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» On the Effectiveness of Gene Selection for Microarray Classi...
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BMCBI
2005
116views more  BMCBI 2005»
13 years 8 months ago
Can Zipf's law be adapted to normalize microarrays?
Background: Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for ...
Timothy Lu, Christine M. Costello, Peter J. P. Cro...
ICPR
2004
IEEE
14 years 9 months ago
Feature Selection and Gene Clustering from Gene Expression Data
In this article we describe an algorithm for feature selection and gene clustering from high dimensional gene expression data. The method is based on measuring similarity between ...
D. Dutta Majumder, Pabitra Mitra
BMCBI
2005
135views more  BMCBI 2005»
13 years 8 months ago
A robust two-way semi-linear model for normalization of cDNA microarray data
Background: Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative e...
Deli Wang, Jian Huang, Hehuang Xie, Liliana Manzel...
GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
14 years 2 months ago
Evolutionary selection of minimum number of features for classification of gene expression data using genetic algorithms
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
Alper Küçükural, Reyyan Yeniterzi...
BMCBI
2008
121views more  BMCBI 2008»
13 years 8 months ago
GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments
Background: High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical proce...
Andreas Keller, Christina Backes, Maher Al-Awadhi,...