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BMCBI
2010
92views more  BMCBI 2010»
15 years 7 months ago
Integrating gene expression and GO classification for PCA by preclustering
Background: Gene expression data can be analyzed by summarizing groups of individual gene expression profiles based on GO annotation information. The mean expression profile per g...
Jorn R. de Haan, Ester Piek, René C. van Sc...
BMCBI
2008
144views more  BMCBI 2008»
15 years 7 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
2007
176views more  BMCBI 2007»
15 years 7 months ago
Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue
Background: Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, fait...
Marc Strickert, Nese Sreenivasulu, Björn Usad...
BMCBI
2006
198views more  BMCBI 2006»
15 years 7 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...
BMCBI
2006
119views more  BMCBI 2006»
15 years 7 months ago
Hidden Markov Model Variants and their Application
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
Stephen Winters-Hilt
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