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    BIOCOMP
    2006
    131views Bioinformatics» more  BIOCOMP 2006»
    PAC: Progressive Alignment with Consensus Sequences
    13 years 10 months ago
    PAC: Progressive Alignment with Consensus Sequences
    Download  ww1.ucmss.com
    Computation of multiple sequence alignments is one of the major open problems in computational molecular biology. The purpose of this study was to provide a new method, PAC (Progre...
    Ke Liu, Mansur H. Samadzadeh
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    TCBB
    2008
    76views more  TCBB 2008»
    Hadamard Conjugation for the Kimura 3ST Model: Combinatorial Proof Using Path Sets
    13 years 9 months ago
    Hadamard Conjugation for the Kimura 3ST Model: Combinatorial Proof Using Path Sets
    Download  research.haifa.ac.il
    Under a stochastic model of molecular sequence evolution the probability of each possible pattern of characters is well defined. The Kimura's three-substitution-types (K3ST) m...
    Michael D. Hendy, Sagi Snir
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    ESANN
    2008
    150views Neural Networks» more  ESANN 2008»
    Conditional prediction of time series using spiral recurrent neural network
    13 years 10 months ago
    Conditional prediction of time series using spiral recurrent neural network
    Download  www.dice.ucl.ac.be
    Frequently, sequences of state transitions are triggered by specific signals. Learning these triggered sequences with recurrent neural networks implies storing them as different at...
    Huaien Gao, Rudolf Sollacher
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    BMCBI
    2005
    142views more  BMCBI 2005»
    transAlign: using amino acids to facilitate the multiple alignment of protein-coding DNA sequences
    13 years 9 months ago
    transAlign: using amino acids to facilitate the multiple alignment of protein-coding DNA sequences
    Download  www.biomedcentral.com
    Background: Alignments of homologous DNA sequences are crucial for comparative genomics and phylogenetic analysis. However, multiple alignment represents a computationally difficu...
    Olaf R. P. Bininda-Emonds
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    SDM
    2007
    SIAM
    104views Data Mining» more  SDM 2007»
    Boosting Optimal Logical Patterns Using Noisy Data
    13 years 10 months ago
    Boosting Optimal Logical Patterns Using Noisy Data
    Download  siam.org
    We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
    Noam Goldberg, Chung-chieh Shan
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