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» Analysis of variance components in gene expression data
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BMCBI
2008
138views more  BMCBI 2008»
14 years 10 months ago
Combining transcriptional datasets using the generalized singular value decomposition
Background: Both microarrays and quantitative real-time PCR are convenient tools for studying the transcriptional levels of genes. The former is preferable for large scale studies...
Andreas W. Schreiber, Neil J. Shirley, Rachel A. B...
BMCBI
2007
148views more  BMCBI 2007»
14 years 9 months ago
WeederH: an algorithm for finding conserved regulatory motifs and regions in homologous sequences
Background: This work addresses the problem of detecting conserved transcription factor binding sites and in general regulatory regions through the analysis of sequences from homo...
Giulio Pavesi, Federico Zambelli, Graziano Pesole
BMCBI
2004
106views more  BMCBI 2004»
14 years 9 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...
BMCBI
2005
161views more  BMCBI 2005»
14 years 9 months ago
Non-linear mapping for exploratory data analysis in functional genomics
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
Francisco Azuaje, Haiying Wang, Alban Chesneau
108
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GECCO
2007
Springer
197views Optimization» more  GECCO 2007»
15 years 4 months ago
Computational intelligence techniques: a study of scleroderma skin disease
This paper presents an analysis of microarray gene expression data from patients with and without scleroderma skin disease using computational intelligence and visual data mining ...
Julio J. Valdés, Alan J. Barton