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    CIBB
    2008
    122views Artificial Intelligence» more  CIBB 2008»
    Splice Site Prediction Using Artificial Neural Networks
    14 years 11 months ago
    Splice Site Prediction Using Artificial Neural Networks
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    A system for utilizing an artificial neural network to predict splice sites in genes has been studied. The neural network uses a sliding window of nucleotides over a gene and predi...
    Øystein Johansen, Tom Ryen, Trygve Eftest&o...
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    BIOCOMP
    2006
    109views Bioinformatics» more  BIOCOMP 2006»
    An Artificial Neural Network based Model to Analyze Malarial Data and Predict Organ Failure
    14 years 11 months ago
    An Artificial Neural Network based Model to Analyze Malarial Data and Predict Organ Failure
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    Health Care Management is one of the most important and most important research areas of the new millennium. The main purpose of this work was to analyze the data on malaria patie...
    Dinesh P. Mital, Shankar Srinivasan, Syed Haque, R...
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    BMCBI
    2007
    141views more  BMCBI 2007»
    Artificial neural network models for prediction of intestinal permeability of oligopeptides
    14 years 9 months ago
    Artificial neural network models for prediction of intestinal permeability of oligopeptides
    Download  www.biomedcentral.com
    Background: Oral delivery is a highly desirable property for candidate drugs under development. Computational modeling could provide a quick and inexpensive way to assess the inte...
    Eunkyoung Jung, Junhyoung Kim, Minkyoung Kim, Dong...
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    VLSISP
    2002
    124views more  VLSISP 2002»
    Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network
    14 years 9 months ago
    Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network
    Download  dec.bournemouth.ac.uk
    In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
    Bogdan Gabrys
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    NIPS
    1997
    83views Information Technology» more  NIPS 1997»
    Training Methods for Adaptive Boosting of Neural Networks
    14 years 11 months ago
    Training Methods for Adaptive Boosting of Neural Networks
    Download  www.iro.umontreal.ca
    Holger Schwenk, Yoshua Bengio
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