Network analysis of transmembrane protein structures

Most studies have shown that globular proteins exist in small-world networks. The present study is an attempt to determine differences in network parameters between transmembrane and globular proteins. Each protein is represented as an undirected graph, where residues represent nodes and inter-residue interactions as the edges. This was then compared to the degree-preserved random controls, to observe if any variation existed. Results indicate that there is a significant difference in shortest path lengths between transmembrane and globular proteins. Hydrophobic amino acids were found to be more spatially distributed in the transmembrane than in globular proteins causing significantly higher values of shortest path lengths (L). Assortativity values too, were found to be significantly higher in the transmembrane than in globular proteins which is due to the highly connected amino acid residues being exposed to the solvent in transmembrane proteins. On analyzing the closeness centrality, it was found that globular proteins have significantly higher values than the transmembrane proteins. We therefore conclude that transmembrane proteins possess small-world characteristics similar to that of globular proteins.     

The effect of gossip on social networks

In this article, we develop a simple model for the effect of gossip spread on social network structure. We define gossip as information passed between two individuals A and B about a third individual C which affects the strengths of all three relationships: it strengthens A‐B and weakens both B‐C and A‐C. We find, in both an analytic derivation and model simulations, that if gossip does not spread beyond simple triads, it destroys them but if gossip propagates through large dense clusters, it strengthens them. Additionally, our simulations show that the effect of gossip on network metrics (clustering coefficient, average‐path‐length, and sum‐of‐strengths) varies with network structure and average‐node‐degree. © 2010 Wiley Periodicals, Inc. Complexity 16: 39‐47, 2011     

Pricing and hedging in a single period market with random interval valued assets

In this article, a new financial market model, in which securities have random interval valued payoffs, is proposed. As an extension of traditional random market model, some concepts, such as robust arbitrage opportunities, risk-neutral pricing measures and robust replicative strategies, are given and discussed parallel to those in traditional market analysis. With these new concepts, problems of pricing and hedging are analyzed. It is shown that the requirement of no robust arbitrage opportunities is equivalent to the existence of risk-neutral pricing measures. Taking no robust arbitrage as the valuation principle, the problem of pricing a contingent claim with random interval valued payoff is discussed. All no robust arbitrage prices of the claim form an interval, whose endpoints can be got from the risk-neutral pricing measures or from robust replicative strategies.     

复杂网络上动力系统同步的研究进展

本文简要介绍复杂网络的基本概念并详细总结了近年来复杂网络上动力学系统的同步的研究进展,主要内容有复杂网络同步的稳定性分析,复杂网络上动力学系统同步的特点,网络的几何特征量对同步稳定性的影响,以及提高网络同步能力的方法等。最后文章提出了这一领域的几个有待解决的问题及可能的发展方向。     

Methyl-RNA: an evolutionary bridge between RNA and DNA?

Given the apparent limitation of double-stranded RNA (dsRNA) genomes to about 30 kb, together with the complexity of DNA synthesis, it appears difficult for a dsRNA genome to encode all the information required before the transition from an RNA to a DNA genome. Ribonucleotide reductase itself, which synthesizes deoxyribonucleotides from ribonucleotides, requires complex protein radical chemistry, and RNA world genomes may have reached their limits of coding capacity well before such complex enzymes had evolved. The transition from RNA to DNA thus appears to require intermediate steps, and we suggest that the naturally occurring 2'-O-methylated RNA, with chemical properties intermediate between RNA and DNA, is a suitable candidate.     

The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region

The initial version of the model used in this study, Village 1.0, was implemented by Tim Kohler and a team of developers mostly from Washington State University. The original model addressed environmental constraints only and did not attempt to model social interaction. In a recent paper we employed Cultural Algorithms as a framework in which to add selected social considerations. In this paper we extend our previous model by adding the ability of agents to perform symmetrically initiated or asymmetrically initiated generalized reciprocal exchange. We have developed a state model for agents' knowledge and, given agents' different responses based on this knowledge. Experiments have shown that the network structure of the systems without reciprocity was the simplest but least resilient. As we allowed agents more opportunities to exchange resources we produced more complex network structures, larger populations, and more resilient systems. Furthermore, allowing the agents to buffer their requests by using a finite state model improved the relative resilience of these larger systems. Introducing reciprocity that can be triggered by both requestors and donors produced the largest number of successful donations. This represents the synergy produced by using the information from two complementary situations within the network. Thus, the network has more information with which it can work and tended to be more resilient than otherwise.     

A BRIEF INTRODUCTION TO SCALE‐FREE NETWORKS

ABSTRACT. This article provides a brief introduction to scale‐free networks. The notion of a scale‐free network is defined and some examples given. Properties frequently exhibited by scale‐free networks are discussed. The importance of the phenomenon of preferential attachment in generating scale‐free networks is illustrated with two examples for the spread of a persistent disease. The models are similar in that they both yield a total infected population (1) which is geometrically distributed, and growing exponentially in expectation; and (2) in which the average distance from the original source of infection grows in a similar way over time. However one model, which has preferential attachment (infection), yields a scale‐free network, while the other which has homogeneous infectivity does not. The possible application of the theory of scale‐free networks to resource management is briefly discussed.     

Fermat Dynamics, Matrix Arithmetics, Finite Circles, and Finite Lobachevsky Planes

Congruences generalizing Fermat's little theorem are proved for the traces of powers of integer matrices. Their relations to Lobachevsky geometries over finite fields and combinatorics of the matrix squaring operation as well as to the corresponding Riemann surfaces with their Kepler cubes are discussed.