25 research outputs found
Map equation for link community
Community structure exists in many real-world networks and has been reported
being related to several functional properties of the networks. The
conventional approach was partitioning nodes into communities, while some
recent studies start partitioning links instead of nodes to find overlapping
communities of nodes efficiently. We extended the map equation method, which
was originally developed for node communities, to find link communities in
networks. This method is tested on various kinds of networks and compared with
the metadata of the networks, and the results show that our method can identify
the overlapping role of nodes effectively. The advantage of this method is that
the node community scheme and link community scheme can be compared
quantitatively by measuring the unknown information left in the networks
besides the community structure. It can be used to decide quantitatively
whether or not the link community scheme should be used instead of the node
community scheme. Furthermore, this method can be easily extended to the
directed and weighted networks since it is based on the random walk.Comment: 9 pages,5 figure
Are better conducting molecules more rigid?
We investigate the electronic origin of the bending stiffness of conducting
molecules. It is found that the bending stiffness associated with electronic
motion, which we refer to as electro-stiffness, , is governed by
the molecular orbital overlap and the gap width between HOMO and LUMO
levels, and behaves as . To study the
effect of doping, we analyze the electron filling-fraction dependence on
and show that doped molecules are more flexible. In addition, to
estimate the contribution of to the total stiffness, we consider
molecules under a voltage bias, and study the length contraction ratio as a
function of the voltage. The molecules are shown to be contracted or dilated,
with increasing nonlinearly with the applied bias
Pattern Formation in a Two-Dimensional Array of Oscillators with Phase-Shifted Coupling
We investigate the dynamics of a two-dimensional array of oscillators with
phase-shifted coupling. Each oscillator is allowed to interact with its
neighbors within a finite radius. The system exhibits various patterns
including squarelike pinwheels, (anti)spirals with phase-randomized cores, and
antiferro patterns embedded in (anti)spirals. We consider the symmetry
properties of the system to explain the observed behaviors, and estimate the
wavelengths of the patterns by linear analysis. Finally, we point out the
implications of our work for biological neural networks
Path finding strategies in scale-free networks
We numerically investigate the scale-free network model of Barab{\'a}si and
Albert [A. L. Barab{\'a}si and R. Albert, Science {\bf 286}, 509 (1999)]
through the use of various path finding strategies. In real networks, global
network information is not accessible to each vertex, and the actual path
connecting two vertices can sometimes be much longer than the shortest one. A
generalized diameter depending on the actual path finding strategy is
introduced, and a simple strategy, which utilizes only local information on the
connectivity, is suggested and shown to yield small-world behavior: the
diameter of the network increases logarithmically with the network size
, the same as is found with global strategy. If paths are sought at random,
is found.Comment: 4 pages, final for
Error and attack tolerance of complex networks
Many complex systems, such as communication networks, display a surprising
degree of robustness: while key components regularly malfunction, local
failures rarely lead to the loss of the global information-carrying ability of
the network. The stability of these complex systems is often attributed to the
redundant wiring of the functional web defined by the systems' components. In
this paper we demonstrate that error tolerance is not shared by all redundant
systems, but it is displayed only by a class of inhomogeneously wired networks,
called scale-free networks. We find that scale-free networks, describing a
number of systems, such as the World Wide Web, Internet, social networks or a
cell, display an unexpected degree of robustness, the ability of their nodes to
communicate being unaffected by even unrealistically high failure rates.
However, error tolerance comes at a high price: these networks are extremely
vulnerable to attacks, i.e. to the selection and removal of a few nodes that
play the most important role in assuring the network's connectivity.Comment: 14 pages, 4 figures, Late
Centralized Modularity of N-Linked Glycosylation Pathways in Mammalian Cells
Glycosylation is a highly complex process to produce a diverse repertoire of
cellular glycans that are attached to proteins and lipids. Glycans are involved
in fundamental biological processes, including protein folding and clearance,
cell proliferation and apoptosis, development, immune responses, and
pathogenesis. One of the major types of glycans, N-linked glycans, is formed by
sequential attachments of monosaccharides to proteins by a limited number of
enzymes. Many of these enzymes can accept multiple N-linked glycans as
substrates, thereby generating a large number of glycan intermediates and their
intermingled pathways. Motivated by the quantitative methods developed in
complex network research, we investigated the large-scale organization of such
N-linked glycosylation pathways in mammalian cells. The N-linked glycosylation
pathways are extremely modular, and are composed of cohesive topological
modules that directly branch from a common upstream pathway of glycan
synthesis. This unique structural property allows the glycan production between
modules to be controlled by the upstream region. Although the enzymes act on
multiple glycan substrates, indicating cross-talk between modules, the impact
of the cross-talk on the module-specific enhancement of glycan synthesis may be
confined within a moderate range by transcription-level control. The findings
of the present study provide experimentally-testable predictions for
glycosylation processes, and may be applicable to therapeutic glycoprotein
engineering
Exploring local structural organization of metabolic networks using subgraph patterns
Metabolic networks of many cellular organisms share global statistical features. Their connectivity distributions follow the long-tailed power law and show the small-world property. In addition, their modular structures are organized in a hierarchical manner. Although the global topological organization of metabolic networks is well understood, their local structural organization is still not clear. Investigating local properties of metabolic networks is necessary to understand the nature of metabolism in living organisms. To identify the local structural organization of metabolic networks, we analysed the subgraphs of metabolic networks of 43 organisms from three domains of life. We first identified the network motifs of metabolic networks and identified the statistically significant subgraph patterns. We then compared metabolic networks from different domains and found that they have similar local structures and that the local structure of each metabolic network has its own taxonomical meaning. Organisms closer in taxonomy showed similar local structures. In addition, the common substrates of 43 metabolic networks were not randomly distributed, but were more likely to be constituents of cohesive subgraph patterns