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相关论文: How small are building blocks of complex networks

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Complex networks can often be decomposed into less complex sub-networks whose structures can give hints about the functional organization of the network as a whole. However, these structural motifs can only tell one part of the functional…

分子网络 · 定量生物学 2015-05-20 Jifeng Qian , Arend Hintze , Christoph Adami

Machine learning models for functional materials design require precise and informative representations of material systems. Common representations encode atomic composition and bonding but often do not include local coordination…

材料科学 · 物理学 2026-03-17 Anoj Aryal , Weiyi Gong , Huta Banjade , Qimin Yan

One of the most important concepts in biological network analysis is that of network motifs, which are patterns of interconnections that occur in a given network at a frequency higher than expected in a random network. In this work we are…

离散数学 · 计算机科学 2020-05-29 Diego P Rubert , Eloi Araujo , Marco A Stefanes , Jens Stoye , Fábio V Martinez

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs---a combination of local network features. One technique to…

Uncovering higher-order spatiotemporal dependencies within human mobility networks offers valuable insights into the analysis of urban structures. In most existing studies, human mobility networks are typically constructed by aggregating…

社会与信息网络 · 计算机科学 2024-05-08 Shuyang Shi , Ding Lyu , Lin Wang , Xiaofan Wang , Guanrong Chen

Complex networks as the World Wide Web, the web of human sexual contacts or criminal networks often do not have an engineered architecture but instead are self-organized by the actions of a large number of individuals. From these local…

无序系统与神经网络 · 物理学 2007-05-23 Holger Ebel , Joern Davidsen , Stefan Bornholdt

Networks are structures that pervade many natural and man-made phenomena. Recent findings have characterized many networks as not random structures, but as efficent complex formations. Current research has examined complex networks as…

无序系统与神经网络 · 物理学 2007-05-23 Sean P. Gorman , Rajendra Kulkarni

Spatio-temporal network dynamics is an emergent property of many complex systems which remains poorly understood. We suggest a new approach to its study based on the analysis of dynamical motifs -- small subnetworks with periodic and…

无序系统与神经网络 · 物理学 2007-05-23 Valentin P. Zhigulin

Among all characteristics exhibited by natural and man-made networks the small-world phenomenon is surely the most relevant and popular. But despite its significance, a reliable and comparable quantification of the question `how small is a…

物理与社会 · 物理学 2019-11-27 Gorka Zamora-López , Romain Brasselet

Over the last two decades, network theory has shown to be a fruitful paradigm in understanding the organization and functioning of real-world complex systems. One technique helpful to this endeavor is identifying functionally influential…

物理与社会 · 物理学 2022-01-24 Francesco Picciolo , Franco Ruzzenenti , Petter Holme , Rossana Mastrandrea

Modular structure is ubiquitous among complex networks. We note that most such systems are subject to multiple structural and functional constraints, e.g., minimizing the average path length and the total number of links, while maximizing…

物理与社会 · 物理学 2007-11-05 Raj Kumar Pan , Sitabhra Sinha

The analysis of small recurrent substructures, so called network motifs, has become a standard tool of complex network science to unveil the design principles underlying the structure of empirical networks. In many natural systems network…

定量方法 · 定量生物学 2015-07-08 Pavel V. Paulau , Christoph Feenders , Bernd Blasius

Generative mechanisms which lead to empirically observed structure of networked systems from diverse fields like biology, technology and social sciences form a very important part of study of complex networks. The structure of many…

物理与社会 · 物理学 2015-12-03 Snehal M. Shekatkar , G. Ambika

Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it…

社会与信息网络 · 计算机科学 2014-09-02 Bojin Zheng , Hongrun Wu , Li Kuang , Jun Qin , Wenhua Du , Jianmin Wang , Deyi Li

We introduce a growing network model in which a new node attaches to a randomly-selected node, as well as to all ancestors of the target node. This mechanism produces a sparse, ultra-small network where the average node degree grows…

统计力学 · 物理学 2009-11-10 P. L. Krapivsky , S. Redner

We study complex networks in which the nodes of the network are tagged with different colors depending on the functionality of the nodes (colored graphs), using information theory applied to the distribution of motifs in such networks. We…

定量方法 · 定量生物学 2011-11-08 Christoph Adami , Jifeng Qian , Matthew Rupp , Arend Hintze

Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical…

统计力学 · 物理学 2016-08-31 Reka Albert , Albert-Laszlo Barabasi

This paper focuses on the modeling of musical melodies as networks. Notes of a melody can be treated as nodes of a network. Connections are created whenever notes are played in sequence. We analyze some main tracks coming from different…

声音 · 计算机科学 2017-09-29 Stefano Ferretti

The identification of motifs--subgraphs that appear significantly more often in a particular network than in an ensemble of randomized networks--has become a ubiquitous method for uncovering potentially important subunits within networks…

分子网络 · 定量生物学 2010-08-27 Reid Ginoza , Andrew Mugler

Meso-scale structures (communities) are used to understand the macro-scale properties of complex networks, such as their functionality and formation mechanisms. Micro-scale structures are known to exist in most complex networks (e.g., large…

物理与社会 · 物理学 2019-08-28 Sophie Wharrie , Lamiae Azizi , Eduardo G. Altmann