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» Microarray Gene Expression Data Analysis
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GECCO
2004
Springer
104views Optimization» more  GECCO 2004»
15 years 3 months ago
A Genetic Approach for Gene Selection on Microarray Expression Data
Abstract. Microarrays allow simultaneous measurement of the expression levels of thousands of genes in cells under different physiological or disease states. Because the number of...
Yong-Hyuk Kim, Su-Yeon Lee, Byung Ro Moon
BMCBI
2004
150views more  BMCBI 2004»
14 years 9 months ago
Graph-based iterative Group Analysis enhances microarray interpretation
Background: One of the most time-consuming tasks after performing a gene expression experiment is the biological interpretation of the results by identifying physiologically impor...
Rainer Breitling, Anna Amtmann, Pawel Herzyk
BMCBI
2005
113views more  BMCBI 2005»
14 years 9 months ago
Pathway level analysis of gene expression using singular value decomposition
Background: A promising direction in the analysis of gene expression focuses on the changes in expression of specific predefined sets of genes that are known in advance to be rela...
John K. Tomfohr, Jun Lu, Thomas B. Kepler
BMCBI
2008
126views more  BMCBI 2008»
14 years 9 months ago
Relating gene expression data on two-component systems to functional annotations in Escherichia coli
Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionall...
Anne M. Denton, Jianfei Wu, Megan K. Townsend, Pre...
BIBE
2007
IEEE
127views Bioinformatics» more  BIBE 2007»
15 years 1 months ago
Gene Selection via Matrix Factorization
The recent development of microarray gene expression techniques have made it possible to offer phenotype classification of many diseases. However, in gene expression data analysis...
Fei Wang, Tao Li