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  • Deciphering 3D organization of chromosomes using Hi-C data

    Author(s)
    Hofmann, A
    Heermann, DW
    Griffith University Author(s)
    Hofmann, Andreas
    Year published
    2018
    Metadata
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    Abstract
    In order to interpret data from Hi-C studies genome-wide contact probability maps need to be translated into models of functional 3D genome organization. Here, we first present an overview of computational methods to analyze contact probability maps in terms of features such as the level and shape of compartmentalization. Next, we describe approaches to modeling 3D genome organization based on Hi-C data.In order to interpret data from Hi-C studies genome-wide contact probability maps need to be translated into models of functional 3D genome organization. Here, we first present an overview of computational methods to analyze contact probability maps in terms of features such as the level and shape of compartmentalization. Next, we describe approaches to modeling 3D genome organization based on Hi-C data.
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    Book Title
    Methods in Molecular Biology
    Volume
    1837
    DOI
    https://doi.org/10.1007/978-1-4939-8675-0_19
    Subject
    Other chemical sciences
    Biological sciences
    Biochemistry and cell biology
    Publication URI
    http://hdl.handle.net/10072/382754
    Collection
    • Book chapters

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