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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2008
114views more  BMCBI 2008»
15 years 6 months ago
A visual analytics approach for understanding biclustering results from microarray data
Background: Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from mi...
Rodrigo Santamaría, Roberto Therón, ...
IDA
2005
Springer
15 years 11 months ago
Biological Cluster Validity Indices Based on the Gene Ontology
With the invention of biotechnological high throughput methods like DNA microarrays and the analysis of the resulting huge amounts of biological data, clustering algorithms gain ne...
Nora Speer, Christian Spieth, Andreas Zell
BMCBI
2008
144views more  BMCBI 2008»
15 years 6 months ago
WGCNA: an R package for weighted correlation network analysis
Background: Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method ...
Peter Langfelder, Steve Horvath
BMCBI
2010
121views more  BMCBI 2010»
15 years 1 months ago
G-stack modulated probe intensities on expression arrays - sequence corrections and signal calibration
Background: The brightness of the probe spots on expression microarrays intends to measure the abundance of specific mRNA targets. Probes with runs of at least three guanines (G) ...
Mario Fasold, Peter F. Stadler, Hans Binder
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
15 years 11 months ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba