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» Combining Affymetrix microarray results
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89
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BMCBI
2007
126views more  BMCBI 2007»
15 years 15 days ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
15 years 6 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
103
Voted
BMCBI
2004
208views more  BMCBI 2004»
15 years 7 days ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov
84
Voted
BMCBI
2007
62views more  BMCBI 2007»
15 years 15 days ago
Missing channels in two-colour microarray experiments: Combining single-channel and two-channel data
Background: There are mechanisms, notably ozone degradation, that can damage a single channel of two-channel microarray experiments. Resulting analyses therefore often choose betw...
Andy G. Lynch, David E. Neal, John D. Kelly, Glyn ...
KES
2006
Springer
15 years 10 days ago
Combined Gene Selection Methods for Microarray Data Analysis
In recent years, the rapid development of DNA Microarray technology has made it possible for scientists to monitor the expression level of thousands of genes in a single experiment...
Hong Hu, Jiuyong Li, Hua Wang, Grant Daggard