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    Exploring community structure in biological networks with random graphs

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    View/Open: ExploringCommunityStructure.pdf (18.MB) Bookview

    Creator
    Sah, Pratha
    Singh, Lisa
    Clauset, Aaron
    Bansal, Shweta
    Abstract
    Community structure is ubiquitous in biological networks. There has been an increased interest in unraveling the community structure of biological systems as it may provide important insights into a system’s functional components and the impact of local structures on dynamics at a global scale. Choosing an appropriate community detection algorithm to identify the community structure in an empirical network can be difficult, however, as the many algorithms available are based on a variety of cost functions and are difficult to validate. Even when community structure is identified in an empirical system, disentangling the effect of community structure from other network properties such as clustering coefficient and assortativity can be a challenge.
    Permanent Link
    http://hdl.handle.net/10822/761516
    Date Published
    2014
    Subject
    Computer Science; Biological networks; Bioinformatics;
    Type
    text
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    • Faculty Scholarship - Computer Science Department
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    Georgetown University Seal
    ©2009 - 2018 Georgetown University Library
    37th & O Streets NW
    Washington DC 20057-1174
    202.687.7385
    digitalscholarship@georgetown.edu