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    CSB
    2003
    IEEE
    98views Bioinformatics» more  CSB 2003»
    Minimum Redundancy Feature Selection from Microarray Gene Expression Data
    14 years 1 months ago
    Minimum Redundancy Feature Selection from Microarray Gene Expression Data
    Download  ranger.uta.edu
    Chris H. Q. Ding, Hanchuan Peng
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    BIOINFORMATICS
    2005
    72views more  BIOINFORMATICS 2005»
    Use of within-array replicate spots for assessing differential expression in microarray experiments
    13 years 8 months ago
    Use of within-array replicate spots for assessing differential expression in microarray experiments
    Download  www.statsci.org
    Motivation. Spotted arrays are often printed with probes in duplicate or triplicate, but current methods for assessing differential expression are not able to make full use of the...
    Gordon K. Smyth, Joëlle Michaud, Hamish S. Sc...
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    JIFS
    2002
    134views more  JIFS 2002»
    Classification of gene expression data using fuzzy logic
    13 years 8 months ago
    Classification of gene expression data using fuzzy logic
    Download  www.mit.edu
    Microarray technologies have allowed the measurement of expression of multiple genes simultaneously. Gene expression levels can be used to classify tissues into diagnostic or progn...
    Lucila Ohno-Machado, Staal A. Vinterbo, Griffin We...
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    BMCBI
    2010
    115views more  BMCBI 2010»
    Importance of replication in analyzing time-series gene expression data: Corticosteroid dynamics and circadian patterns in rat l
    13 years 8 months ago
    Importance of replication in analyzing time-series gene expression data: Corticosteroid dynamics and circadian patterns in rat l
    Download  www.biomedcentral.com
    Background: Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However...
    Tung T. Nguyen, Richard R. Almon, Debra C. DuBois,...
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    AINA
    2008
    IEEE
    279views Computer Networks» more  AINA 2008»
    Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
    14 years 3 months ago
    Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
    Download  tintin.sfsu.edu
    The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
    Connie Phong, Raul Singh
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