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» Microarray Gene Expression Data Analysis
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BMCBI
2008
144views more  BMCBI 2008»
15 years 2 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»
14 years 9 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 8 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
AAAI
2007
15 years 4 months ago
Biomind ArrayGenius and GeneGenius: Web Services Offering Microarray and SNP Data Analysis via Novel Machine Learning Methods
Analysis of postgenomic biological data (such as microarray and SNP data) is a subtle art and science, and the statistical methods most commonly utilized sometimes prove inadequat...
Ben Goertzel, Cassio Pennachin, Lúcio de So...
BMCBI
2004
126views more  BMCBI 2004»
15 years 2 months ago
Visualization and analysis of microarray and gene ontology data with treemaps
Background: The increasing complexity of genomic data presents several challenges for biologists. Limited computer monitor views of data complexity and the dynamic nature of data ...
Eric H. Baehrecke, Niem Dang, Ketan Babaria, Ben S...