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    BMCBI
    2008
    123views more  BMCBI 2008»
    Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
    14 years 9 months ago
    Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
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    Background: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing a...
    Firoz Anwar, Syed Murtuza Baker, Taskeed Jabid, Md...
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    IJON
    2010
    148views more  IJON 2010»
    Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machin
    14 years 6 months ago
    Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machin
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    Several solutions have been proposed to exploit the availability of heterogeneous sources of biomolecular data for gene function prediction, but few attention has been dedicated t...
    Matteo Re, Giorgio Valentini
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    KBS
    2006
    231views more  KBS 2006»
    Predicting football results using Bayesian nets and other machine learning techniques
    14 years 9 months ago
    Predicting football results using Bayesian nets and other machine learning techniques
    Download  www.eecs.qmul.ac.uk
    Bayesian networks (BNs) provide a means for representing, displaying, and making available in a usable form the knowledge of experts in a given Weld. In this paper, we look at the...
    A. Joseph, Norman E. Fenton, Martin Neil
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    NN
    2006
    Springer
    163views Neural Networks» more  NN 2006»
    Machine learning approaches for estimation of prediction interval for the model output
    14 years 9 months ago
    Machine learning approaches for estimation of prediction interval for the model output
    Download  www.unesco-ihe.org
    A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
    Durga L. Shrestha, Dimitri P. Solomatine
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    ICDM
    2008
    IEEE
    120views Data Mining» more  ICDM 2008»
    Prediction of Skin Penetration Using Machine Learning Methods
    15 years 4 months ago
    Prediction of Skin Penetration Using Machine Learning Methods
    Download  homepages.feis.herts.ac.uk
    Improving predictions of the skin permeability coefficient is a difficult problem. It is also an important issue with the increasing use of skin patches as a means of drug deliv...
    Yi Sun, Gary P. Moss, Maria Prapopoulou, Rod Adams...
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