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    AROBOTS
    2002
    131views more  AROBOTS 2002»
    Automated Derivation of Primitives for Movement Classification
    13 years 7 months ago
    Automated Derivation of Primitives for Movement Classification
    Download  www.cc.gatech.edu
    Abstract. We describe a new method for representing human movement compactly, in terms of a linear superimposition of simpler movements termed primitives. This method is a part of ...
    Ajo Fod, Maja J. Mataric, Odest Chadwicke Jenkins
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    BMCBI
    2004
    162views more  BMCBI 2004»
    Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant m
    13 years 7 months ago
    Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant m
    Download  www.biomedcentral.com
    Background: Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression p...
    Rajalakshmi Gurunathan, Bernard Van Emden, Sethura...
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    BMCBI
    2004
    205views more  BMCBI 2004»
    A combinational feature selection and ensemble neural network method for classification of gene expression data
    13 years 7 months ago
    A combinational feature selection and ensemble neural network method for classification of gene expression data
    Download  www.biomedcentral.com
    Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
    Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
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    BMCBI
    2004
    158views more  BMCBI 2004»
    A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
    13 years 7 months ago
    A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
    Download  www.biomedcentral.com
    Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
    Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
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    BMCBI
    2004
    169views more  BMCBI 2004»
    A power law global error model for the identification of differentially expressed genes in microarray data
    13 years 7 months ago
    A power law global error model for the identification of differentially expressed genes in microarray data
    Download  www.biomedcentral.com
    Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
    Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
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