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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 5 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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    BMCBI
    2004
    169views more  BMCBI 2004»
    A power law global error model for the identification of differentially expressed genes in microarray data
    13 years 5 months ago
    A power law global error model for the identification of differentially expressed genes in microarray data
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    Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
    Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
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    BMCBI
    2004
    158views more  BMCBI 2004»
    A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
    13 years 5 months ago
    A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
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    Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
    Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
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    BMCBI
    2005
    113views more  BMCBI 2005»
    Normal uniform mixture differential gene expression detection for cDNA microarrays
    13 years 5 months ago
    Normal uniform mixture differential gene expression detection for cDNA microarrays
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    Background: One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the ...
    Nema Dean, Adrian E. Raftery
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    BMCBI
    2010
    176views more  BMCBI 2010»
    Reverse engineering gene regulatory network from microarray data using linear time-variant model
    13 years 5 months ago
    Reverse engineering gene regulatory network from microarray data using linear time-variant model
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    nd: Gene regulatory network is an abstract mapping of gene regulations in living cells that can help to predict the system behavior of living organisms. Such prediction capability...
    Mitra Kabir, Nasimul Noman, Hitoshi Iba
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