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    APBC
    2007
    75views Bioinformatics» more  APBC 2007»
    Inferring Gene Regulatory Networks by Machine Learning Methods
    13 years 6 months ago
    Inferring Gene Regulatory Networks by Machine Learning Methods
    Download  www.comp.nus.edu.sg
    Jochen Supper, Holger Fröhlich, Christian Spi...
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    BMCBI
    2010
    143views more  BMCBI 2010»
    Learning gene regulatory networks from only positive and unlabeled data
    13 years 5 months ago
    Learning gene regulatory networks from only positive and unlabeled data
    Download  www.biomedcentral.com
    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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    BIOCOMP
    2006
    233views Bioinformatics» more  BIOCOMP 2006»
    Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
    13 years 6 months ago
    Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
    Download  ww1.ucmss.com
    Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
    Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia
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    ECCB
    2003
    IEEE
    183views Computational Biology» more  ECCB 2003»
    Gene networks inference using dynamic Bayesian networks
    13 years 10 months ago
    Gene networks inference using dynamic Bayesian networks
    Download  bioinformatics.oxfordjournals.org
    This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
    Bruno-Edouard Perrin, Liva Ralaivola, Aurél...
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    IDA
    2009
    Springer
    123views Information Technology» more  IDA 2009»
    Estimating Hidden Influences in Metabolic and Gene Regulatory Networks
    13 years 3 months ago
    Estimating Hidden Influences in Metabolic and Gene Regulatory Networks
    Download  www.helmholtz-muenchen.de
    We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory net...
    Florian Blöchl, Fabian J. Theis
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