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    BMCBI
    2006
    186views more  BMCBI 2006»
    Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
    13 years 7 months ago
    Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
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    Background: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments....
    Xiaoli Li, Yin-Chet Tan, See-Kiong Ng
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    BMCBI
    2007
    154views more  BMCBI 2007»
    h-Profile plots for the discovery and exploration of patterns in gene expression data with an application to time course data
    13 years 7 months ago
    h-Profile plots for the discovery and exploration of patterns in gene expression data with an application to time course data
    Download  www.biomedcentral.com
    Background: An ever increasing number of techniques are being used to find genes with similar profiles from microarray studies. Visualization of gene expression profiles can aid t...
    Yvonne E. Pittelkow, Susan R. Wilson
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    BIOTECHNO
    2008
    IEEE
    124views Bioinformatics» more  BIOTECHNO 2008»
    Grouping Levels of Exposure with Same Observable Effects before Class Prediction in Toxicogenomics
    14 years 1 months ago
    Grouping Levels of Exposure with Same Observable Effects before Class Prediction in Toxicogenomics
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    —Gene expression profiling in toxicogenomics is often used to find molecular signature of toxicants. The range of doses chosen in toxicogenomics studies does not always represe...
    Vincent Guillemot, Cathy Philippe, Arthur Tenenhau...
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    BMCBI
    2008
    115views more  BMCBI 2008»
    Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
    13 years 7 months ago
    Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
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    Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
    Sudhakar Jonnalagadda, Rajagopalan Srinivasan
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    ESANN
    2008
    149views Neural Networks» more  ESANN 2008»
    A method for robust variable selection with significance assessment
    13 years 9 months ago
    A method for robust variable selection with significance assessment
    Download  web.mit.edu
    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...
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