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    » Inferring differentiation pathways from gene expression
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    BMCBI
    2007
    143views more  BMCBI 2007»
    Gene selection for classification of microarray data based on the Bayes error
    13 years 8 months ago
    Gene selection for classification of microarray data based on the Bayes error
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    Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
    Ji-Gang Zhang, Hong-Wen Deng
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    JMLR
    2010
    125views more  JMLR 2010»
    On utility of gene set signatures in gene expression-based cancer class prediction
    13 years 3 months ago
    On utility of gene set signatures in gene expression-based cancer class prediction
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    Machine learning methods that can use additional knowledge in their inference process are central to the development of integrative bioinformatics. Inclusion of background knowled...
    Minca Mramor, Marko Toplak, Gregor Leban, Tomaz Cu...
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    BMCBI
    2010
    143views more  BMCBI 2010»
    Learning gene regulatory networks from only positive and unlabeled data
    13 years 8 months ago
    Learning gene regulatory networks from only positive and unlabeled data
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    Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
    Luigi Cerulo, Charles Elkan, Michele Ceccarelli
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    BMCBI
    2006
    202views more  BMCBI 2006»
    Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks
    13 years 8 months ago
    Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks
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    Background: The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the sea...
    David J. Reiss, Nitin S. Baliga, Richard Bonneau
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    BMCBI
    2008
    126views more  BMCBI 2008»
    c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
    13 years 8 months ago
    c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
    Download  www.biomedcentral.com
    Background: Computational methods for characterizing novel transcription factor binding sites search for sequence patterns or "motifs" that appear repeatedly in genomic ...
    Katerina Kechris, Hao Li
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