首页    期刊浏览 2025年02月20日 星期四
登录注册

文章基本信息

  • 标题:From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks
  • 本地全文:下载
  • 作者:Carlo Vittorio Cannistraci ; Gregorio Alanis-Lobato ; Timothy Ravasi
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2013
  • 卷号:3
  • 期号:1
  • DOI:10.1038/srep01613
  • 语种:English
  • 出版社:Springer Nature
  • 摘要: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.
国家哲学社会科学文献中心版权所有