120 research outputs found
Growing Scale-Free Networks with Tunable Clustering
We extend the standard scale-free network model to include a ``triad
formation step''. We analyze the geometric properties of networks generated by
this algorithm both analytically and by numerical calculations, and find that
our model possesses the same characteristics as the standard scale-free
networks like the power-law degree distribution and the small average geodesic
length, but with the high-clustering at the same time. In our model, the
clustering coefficient is also shown to be tunable simply by changing a control
parameter - the average number of triad formation trials per time step.Comment: Accepted for publication in Phys. Rev.
Hierarchical characterization of complex networks
While the majority of approaches to the characterization of complex networks
has relied on measurements considering only the immediate neighborhood of each
network node, valuable information about the network topological properties can
be obtained by considering further neighborhoods. The current work discusses on
how the concepts of hierarchical node degree and hierarchical clustering
coefficient (introduced in cond-mat/0408076), complemented by new hierarchical
measurements, can be used in order to obtain a powerful set of topological
features of complex networks. The interpretation of such measurements is
discussed, including an analytical study of the hierarchical node degree for
random networks, and the potential of the suggested measurements for the
characterization of complex networks is illustrated with respect to simulations
of random, scale-free and regular network models as well as real data
(airports, proteins and word associations). The enhanced characterization of
the connectivity provided by the set of hierarchical measurements also allows
the use of agglomerative clustering methods in order to obtain taxonomies of
relationships between nodes in a network, a possibility which is also
illustrated in the current article.Comment: 19 pages, 23 figure
Statistical mechanics of complex networks
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 links. While traditionally these systems were modeled as random
graphs, it is increasingly recognized that the topology and evolution of real
networks is governed by robust organizing principles. Here we review the recent
advances in the field of complex networks, focusing on the statistical
mechanics of network topology and dynamics. After reviewing the empirical data
that motivated the recent interest in networks, we discuss the main models and
analytical tools, covering random graphs, small-world and scale-free networks,
as well as the interplay between topology and the network's robustness against
failures and attacks.Comment: 54 pages, submitted to Reviews of Modern Physic
Active/Passive, ‘Diminished’/‘Beautiful’, ‘Light’ from Above and Below: Rereading Shekhinah’s Sexual Desire in Zohar al Shir ha-Shirim (Song of Songs)
In Zohar al Shir ha-Shirim, the Zohar’s reading of Song of Songs, Shekhinah, echoing themes associated with the Shulamite of the biblical text, consistently initiates cosmic union. Sexual desire in the zoharic texts is a form of capital necessary to facilitate sefirotic intercourse, although scholarly readings of the zoharic corpus often identify Shekhinah as a passive receptacle. This, however, is only true if the endemic contradictions within the texts are glossed over. In Song of Songs, the Shulamite’s sexual ‘initiative’ is core. This was not lost on the author(s) of Zohar al Shir ha-Shirim, who, in struggling to explain Shekhinah’s sefirotic role in line with the erotics of Song of Songs, inescapably echoed the ‘depatriarchalizing’ themes of the biblical text. As this article demonstrates, in Zohar al Shir ha-Shirim, Shekhinah is active and repeatedly encourages and frustrates cosmic sexual intercourse. Zohar al Shir ha-Shirim shows that it is possible to reread Shekhinah’s role beyond the androcentrism of the authors as well as scholarly assumptions about her passivity
Targeting Huntington’s disease through histone deacetylases
Huntington’s disease (HD) is a debilitating neurodegenerative condition with significant burdens on both patient and healthcare costs. Despite extensive research, treatment options for patients with this condition remain limited. Aberrant post-translational modification (PTM) of proteins is emerging as an important element in the pathogenesis of HD. These PTMs include acetylation, phosphorylation, methylation, sumoylation and ubiquitination. Several families of proteins are involved with the regulation of these PTMs. In this review, I discuss the current evidence linking aberrant PTMs and/or aberrant regulation of the cellular machinery regulating these PTMs to HD pathogenesis. Finally, I discuss the evidence suggesting that pharmacologically targeting one of these protein families the histone deacetylases may be of potential therapeutic benefit in the treatment of HD
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