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    BMCBI
    2006
    148views more  BMCBI 2006»
    Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores
    13 years 10 months ago
    Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores
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    Background: Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epi...
    Jesper Salomon, Darren R. Flower
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    BMCBI
    2006
    130views more  BMCBI 2006»
    Docking protein domains in contact space
    13 years 10 months ago
    Docking protein domains in contact space
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    Background: Many biological processes involve the physical interaction between protein domains. Understanding these functional associations requires knowledge of the molecular str...
    Stefano Lise, Alice Walker-Taylor, David T. Jones
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    BMCBI
    2006
    94views more  BMCBI 2006»
    Noise-injected neural networks show promise for use on small-sample expression data
    13 years 10 months ago
    Noise-injected neural networks show promise for use on small-sample expression data
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    Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
    Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
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    DATAMINE
    2006
    176views more  DATAMINE 2006»
    A Bit Level Representation for Time Series Data Mining with Shape Based Similarity
    13 years 10 months ago
    A Bit Level Representation for Time Series Data Mining with Shape Based Similarity
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    Clipping is the process of transforming a real valued series into a sequence of bits representing whether each data is above or below the average. In this paper, we argue that clip...
    Anthony J. Bagnall, Chotirat (Ann) Ratanamahatana,...
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    JMLR
    2008
    151views more  JMLR 2008»
    Learning to Combine Motor Primitives Via Greedy Additive Regression
    13 years 10 months ago
    Learning to Combine Motor Primitives Via Greedy Additive Regression
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    The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
    Manu Chhabra, Robert A. Jacobs
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