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» Robust test method for time-course microarray experiments
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ICPR
2006
IEEE
14 years 8 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
BMCBI
2002
128views more  BMCBI 2002»
13 years 7 months ago
Correlating overrepresented upstream motifs to gene expression: a computational approach to regulatory element discovery in euka
Background: Gene regulation in eukaryotes is mainly effected through transcription factors binding to rather short recognition motifs generally located upstream of the coding regi...
Michele Caselle, Ferdinando Di Cunto, Paolo Prover...
BMCBI
2006
123views more  BMCBI 2006»
13 years 7 months ago
How to decide? Different methods of calculating gene expression from short oligonucleotide array data will give different result
Background: Short oligonucleotide arrays for transcript profiling have been available for several years. Generally, raw data from these arrays are analysed with the aid of the Mic...
Frank F. Millenaar, John Okyere, Sean T. May, Mart...
ICASSP
2011
IEEE
12 years 11 months ago
Robust changepoint detection based on multivariate rank statistics
We introduce a novel statistical test for unsupervised detection of changepoints in multidimensional sequences of temporal observations. The test statistic is based on a multivari...
Alexandre Lung-Yut-Fong, Céline Lévy...
ESANN
2008
13 years 9 months ago
A method for robust variable selection with significance assessment
Our goal is proposing an unbiased framework for gene expression analysis based on variable selection combined with a significance assessment step. We start by discussing the need ...
Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Ales...