Exploring biological network structure with clustered random networks |
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Authors: | Shweta Bansal Shashank Khandelwal and Lauren Ancel Meyers |
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Institution: | (1) Center for Infectious Disease Dynamics, Penn State University, University Park, PA 16802, USA;(2) Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA;(3) Section of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA;(4) External Faculty, Santa Fe Institute, Santa Fe, NM 87501, USA |
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Abstract: | Background Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among
proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful
insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions)
and the extent of clustering (the tendency for a set of three nodes to be interconnected) are two of many well-studied network
properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties,
however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand
the impact of various topological properties on dynamics. |
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