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    BMCBI
    2010
    164views more  BMCBI 2010»
    Merged consensus clustering to assess and improve class discovery with microarray data
    14 years 9 months ago
    Merged consensus clustering to assess and improve class discovery with microarray data
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    Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
    T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
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    BMCBI
    2006
    98views more  BMCBI 2006»
    In search of functional association from time-series microarray data based on the change trend and level of gene expression
    14 years 11 months ago
    In search of functional association from time-series microarray data based on the change trend and level of gene expression
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    Background: The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional l...
    Feng He, An-Ping Zeng
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    SDM
    2007
    SIAM
    139views Data Mining» more  SDM 2007»
    Dynamic Algorithm for Graph Clustering Using Minimum Cut Tree
    15 years 1 months ago
    Dynamic Algorithm for Graph Clustering Using Minimum Cut Tree
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    We present an efficient dynamic algorithm for clustering undirected graphs, whose edge property is changing continuously. The algorithm maintains clusters of high quality in pres...
    Barna Saha, Pabitra Mitra
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    BMCBI
    2006
    90views more  BMCBI 2006»
    Dissecting trait heterogeneity: a comparison of three clustering methods applied to genotypic data
    14 years 11 months ago
    Dissecting trait heterogeneity: a comparison of three clustering methods applied to genotypic data
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    Background: Trait heterogeneity, which exists when a trait has been defined with insufficient specificity such that it is actually two or more distinct traits, has been implicated...
    Tricia A. Thornton-Wells, Jason H. Moore, Jonathan...
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    CORR
    2010
    Springer
    219views Education» more  CORR 2010»
    Clustering high dimensional data using subspace and projected clustering algorithms
    14 years 12 months ago
    Clustering high dimensional data using subspace and projected clustering algorithms
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    : Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerate...
    Rahmat Widia Sembiring, Jasni Mohamad Zain, Abdull...
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