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    PSB
    2004
    73views Applied Computing» more  PSB 2004»
    Modeling Gene Expression from Microarray Expression Data with State-Space Equations
    13 years 6 months ago
    Modeling Gene Expression from Microarray Expression Data with State-Space Equations
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    Fang-Xiang Wu, Wen-Jun Zhang, Anthony J. Kusalik
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    BMCBI
    2004
    139views more  BMCBI 2004»
    Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
    13 years 5 months ago
    Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
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    Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge r...
    Jeffrey P. Townsend
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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
    2002
    188views more  BMCBI 2002»
    The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
    13 years 5 months ago
    The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
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    Background: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic an...
    David M. Mutch, Alvin Berger, Robert Mansourian, A...
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    BMCBI
    2007
    167views more  BMCBI 2007»
    A stochastic differential equation model for transcriptional regulatory networks
    13 years 5 months ago
    A stochastic differential equation model for transcriptional regulatory networks
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    Background: This work explores the quantitative characteristics of the local transcriptional regulatory network based on the availability of time dependent gene expression data se...
    Adriana Climescu-Haulica, Michelle D. Quirk
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