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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
    14 years 11 months ago
    Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
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    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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    ICMLA
    2008
    149views Machine Learning» more  ICMLA 2008»
    Microarray Classification from Several Two-Gene Expression Comparisons
    14 years 11 months ago
    Microarray Classification from Several Two-Gene Expression Comparisons
    Download  www.cis.jhu.edu
    We describe our contribution to the ICMLA2008 "Automated Micro-Array Classification Challenge". The design of our classifier is motivated by the special scenario encounte...
    Donald Geman, Bahman Afsari, Aik Choon Tan, Daniel...
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    BMCBI
    2007
    133views more  BMCBI 2007»
    Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
    14 years 9 months ago
    Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
    Download  www.biomedcentral.com
    Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
    Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
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    102
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    ICMLA
    2010
    133views Machine Learning» more  ICMLA 2010»
    Smoothing Gene Expression Using Biological Networks
    14 years 7 months ago
    Smoothing Gene Expression Using Biological Networks
    Download  math.bu.edu
    Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
    Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
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    BMCBI
    2010
    123views more  BMCBI 2010»
    Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context
    14 years 9 months ago
    Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context
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    Background: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little ov...
    Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Ha...
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