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BMCBI
2006
165views more  BMCBI 2006»
13 years 7 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin
JIPS
2007
134views more  JIPS 2007»
13 years 7 months ago
An Efficient Functional Analysis Method for Micro-array Data Using Gene Ontology
: Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of ...
Dong-wan Hong, Jong-keun Lee, Sung-soo Park, Sang-...
BMCBI
2008
96views more  BMCBI 2008»
13 years 7 months ago
Use of normalization methods for analysis of microarrays containing a high degree of gene effects
Background: High-throughput microarrays are widely used to study gene expression across tissues and developmental stages. Analysis of gene expression data is challenging in these ...
Terri T. Ni, William J. Lemon, Yu Shyr, Tao P. Zho...
GECCO
2000
Springer
123views Optimization» more  GECCO 2000»
13 years 11 months ago
Genomic computing: explanatory modelling for functional genomics
Many newly discovered genes are of unknown function. DNA microarrays are a method for determining the expression levels of all genes in an organism for which a complete genome seq...
Richard J. Gilbert, Jem J. Rowland, Douglas B. Kel...
BMCBI
2005
189views more  BMCBI 2005»
13 years 7 months ago
Quantitative inference of dynamic regulatory pathways via microarray data
Background: The cellular signaling pathway (network) is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway ar...
Wen-Chieh Chang, Chang-Wei Li, Bor-Sen Chen