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Sci Rep. 2013;3:1613. doi: 10.1038/srep01613.

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

Author information

1
Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia. kalokagathos.agon@gmail.com

Abstract

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.

PMID:
23563395
PMCID:
PMC3619147
DOI:
10.1038/srep01613
[Indexed for MEDLINE]
Free PMC Article

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