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  • Cluster Analysis of Gene Expression Data

    Author(s)
    Liew, Alan Wee-Chung
    Law, Ngai-Fong
    Yan, Hong
    Griffith University Author(s)
    Liew, Alan Wee-Chung
    Year published
    2009
    Metadata
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    Abstract
    Important insights into gene function can be gained by gene expression analysis. For example, some genes are turned on (expressed) or turned off (repressed) when there is a change in external conditions or stimuli. The expression of one gene is often regulated by the expression of other genes. A detail analysis of gene expression information will provide an understanding about the inter-networking of different genes and their functional roles. DNA microarray technology allows massively parallel, high throughput genome-wide profiling of gene expression in a single hybridization experiment [Lockhart & Winzeler, 2000]. It has ...
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    Important insights into gene function can be gained by gene expression analysis. For example, some genes are turned on (expressed) or turned off (repressed) when there is a change in external conditions or stimuli. The expression of one gene is often regulated by the expression of other genes. A detail analysis of gene expression information will provide an understanding about the inter-networking of different genes and their functional roles. DNA microarray technology allows massively parallel, high throughput genome-wide profiling of gene expression in a single hybridization experiment [Lockhart & Winzeler, 2000]. It has been widely used in numerous studies over a broad range of biological disciplines, such as cancer classification (Armstrong et al., 2002), identification of genes relevant to a certain diagnosis or therapy (Muro et al., 2003), investigation of the mechanism of drug action and cancer prognosis (Kim et al., 2000; Duggan et al., 1999). Due to the large number of genes involved in microarray experiment study and the complexity of biological networks, clustering is an important exploratory technique for gene expression data analysis. In this article, we present a succinct review of some of our work in cluster analysis of gene expression data.
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    Book Title
    Encyclopedia of Artificial Intelligence
    Publisher URI
    http://dx.doi.org/10.4018/978-1-59904-849-9
    DOI
    https://doi.org/10.4018/978-1-59904-849-9.ch045
    Subject
    Pattern Recognition and Data Mining
    Publication URI
    http://hdl.handle.net/10072/26559
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