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    BMCBI
    2007
    135views more  BMCBI 2007»
    Measuring similarities between gene expression profiles through new data transformations
    13 years 7 months ago
    Measuring similarities between gene expression profiles through new data transformations
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    Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
    Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...
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    IMSCCS
    2006
    IEEE
    148views Theoretical Computer Science» more  IMSCCS 2006»
    Clustering of Gene Expression Data: Performance and Similarity Analysis
    14 years 1 months ago
    Clustering of Gene Expression Data: Performance and Similarity Analysis
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    Background: DNA Microarray technology is an innovative methodology in experimental molecular biology, which has produced huge amounts of valuable data in the profile of gene expre...
    Longde Yin, Chun-Hsi Huang
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    BMCBI
    2011
    192views Artificial Intelligence» more  BMCBI 2011»
    A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
    12 years 11 months ago
    A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
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    Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
    Alfredo A. Kalaitzis, Neil D. Lawrence
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    BMCBI
    2011
    290views Artificial Intelligence» more  BMCBI 2011»
    Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms
    13 years 2 months ago
    Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms
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    Background: The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade...
    Andrew T. Milnthorpe, Mikhail Soloviev
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    CIBCB
    2007
    IEEE
    204views Computational Biology» more  CIBCB 2007»
    Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
    13 years 11 months ago
    Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
    Download  www.jihe.net
    Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
    Ji He, Xinbin Dai, Xuechun Zhao
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