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    BMCBI
    2010
    124views more  BMCBI 2010»
    A factor model to analyze heterogeneity in gene expression
    13 years 10 months ago
    A factor model to analyze heterogeneity in gene expression
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    Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
    Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...
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    ICML
    2006
    IEEE
    167views Machine Learning» more  ICML 2006»
    On a theory of learning with similarity functions
    14 years 10 months ago
    On a theory of learning with similarity functions
    Download  www.cc.gatech.edu
    Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
    Maria-Florina Balcan, Avrim Blum
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    EMNLP
    2007
    133views Natural Language Processing» more  EMNLP 2007»
    Finding Good Sequential Model Structures using Output Transformations
    13 years 11 months ago
    Finding Good Sequential Model Structures using Output Transformations
    Download  acl.ldc.upenn.edu
    In Sequential Viterbi Models, such as HMMs, MEMMs, and Linear Chain CRFs, the type of patterns over output sequences that can be learned by the model depend directly on the modelâ...
    Edward Loper
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    BMCBI
    2007
    97views more  BMCBI 2007»
    In situ analysis of cross-hybridisation on microarrays and the inference of expression correlation
    13 years 10 months ago
    In situ analysis of cross-hybridisation on microarrays and the inference of expression correlation
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    Background: Microarray co-expression signatures are an important tool for studying gene function and relations between genes. In addition to genuine biological co-expression, corr...
    Tineke Casneuf, Yves Van de Peer, Wolfgang Huber
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    BMCBI
    2008
    142views more  BMCBI 2008»
    Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification
    13 years 10 months ago
    Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification
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    Background: In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produ...
    Irene Kouskoumvekaki, Zhiyong Yang, Svava Ó...
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