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    » Gene Expression Clustering with Functional Mixture Models
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    BMCBI
    2006
    103views more  BMCBI 2006»
    Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression
    13 years 7 months ago
    Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression
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    Background: The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level ...
    Sébastien Lemieux
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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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    CIKM
    2004
    Springer
    118views Information Technology» more  CIKM 2004»
    Mining gene expression datasets using density-based clustering
    14 years 1 months ago
    Mining gene expression datasets using density-based clustering
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    Given the recent advancement of microarray technologies, we present a density-based clustering approach for the purpose of co-expressed gene cluster identification. The underlyin...
    Seokkyung Chung, Jongeun Jun, Dennis McLeod
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    ACAL
    2007
    Springer
    161views Artificial Intelligence» more  ACAL 2007»
    An Integrated QAP-Based Approach to Visualize Patterns of Gene Expression Similarity
    14 years 2 months ago
    An Integrated QAP-Based Approach to Visualize Patterns of Gene Expression Similarity
    Download  www.cs.newcastle.edu.au
    Abstract. This paper illustrates how the Quadratic Assignment Problem (QAP) is used as a mathematical model that helps to produce a visualization of microarray data, based on the r...
    Mario Inostroza-Ponta, Alexandre Mendes, Regina Be...
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    BMCBI
    2007
    146views more  BMCBI 2007»
    Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
    13 years 8 months ago
    Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
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    Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
    Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
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