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» E-CAST: A Data Mining Algorithm for Gene Expression Data
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BMCBI
2007
135views more  BMCBI 2007»
13 years 8 months ago
Detecting multivariate differentially expressed genes
Background: Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariat...
Roland Nilsson, José M. Peña, Johan ...
BMCBI
2004
181views more  BMCBI 2004»
13 years 7 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
SAC
2004
ACM
14 years 1 months ago
Time-frequency feature detection for time-course microarray data
Gene clustering based on microarray data provides useful functional information to the working biologists. Many current gene-clustering algorithms rely on Euclidean-based distance...
Jiawu Feng, Paolo Emilio Barbano, Bud Mishra
BMCBI
2006
103views more  BMCBI 2006»
13 years 8 months ago
Correction of scaling mismatches in oligonucleotide microarray data
Background: Gene expression microarray data is notoriously subject to high signal variability. Moreover, unavoidable variation in the concentration of transcripts applied to micro...
Martino Barenco, Jaroslav Stark, Daniel Brewer, Da...
ISMB
2000
13 years 9 months ago
Analysis of Gene Expression Microarrays for Phenotype Classification
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
Andrea Califano, Gustavo Stolovitzky, Yuhai Tu