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From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks
Open accessAbstract
Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.
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Modular gateway-ness connectivity and structural core organization in maritime network science
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Metadata
- Authors
- Cannistraci, C. V., Alanis-Lobato, G., & Ravasi, T.
- Venue
- Scientific Reports
- Published
- 2013-04-08
- Volume
- 3
- Issue
- 1
- Pages
- 1613-1613
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2066692087
- Cited by
- 401
- References
- 39
- FWCI
- 13.39
- Type
- journal article
- Language
- en
- Open access
- gold
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