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What's in a crowd? Analysis of face-to-face behavioral networks

Isella, Lorenzo; Stehlé, Juliette; Barrat, Alain; Cattuto, Ciro; Pinton, Jean-François; Broeck, Wouter Van den
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.69%
The availability of new data sources on human mobility is opening new avenues for investigating the interplay of social networks, human mobility and dynamical processes such as epidemic spreading. Here we analyze data on the time-resolved face-to-face proximity of individuals in large-scale real-world scenarios. We compare two settings with very different properties, a scientific conference and a long-running museum exhibition. We track the behavioral networks of face-to-face proximity, and characterize them from both a static and a dynamic point of view, exposing important differences as well as striking similarities. We use our data to investigate the dynamics of a susceptible-infected model for epidemic spreading that unfolds on the dynamical networks of human proximity. The spreading patterns are markedly different for the conference and the museum case, and they are strongly impacted by the causal structure of the network data. A deeper study of the spreading paths shows that the mere knowledge of static aggregated networks would lead to erroneous conclusions about the transmission paths on the dynamical networks.

Phase transition in a class of non-linear random networks

Andrecut, M.; Kauffman, S. A.
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.69%
We discuss the complex dynamics of a non-linear random networks model, as a function of the connectivity k between the elements of the network. We show that this class of networks exhibit an order-chaos phase transition for a critical connectivity k = 2. Also, we show that both, pairwise correlation and complexity measures are maximized in dynamically critical networks. These results are in good agreement with the previously reported studies on random Boolean networks and random threshold networks, and show once again that critical networks provide an optimal coordination of diverse behavior.; Comment: 9 pages, 3 figures, revised version

Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks

Newberry, Mitchell G; Ennis, Daniel B; Savage, Van M
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.69%
Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods--two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths.

Evolution of networks

Dorogovtsev, S. N.; Mendes, J. F. F.
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.68%
We review the recent fast progress in statistical physics of evolving networks. Interest has focused mainly on the structural properties of random complex networks in communications, biology, social sciences and economics. A number of giant artificial networks of such a kind came into existence recently. This opens a wide field for the study of their topology, evolution, and complex processes occurring in them. Such networks possess a rich set of scaling properties. A number of them are scale-free and show striking resilience against random breakdowns. In spite of large sizes of these networks, the distances between most their vertices are short -- a feature known as the small-world'' effect. We discuss how growing networks self-organize into scale-free structures and the role of the mechanism of preferential linking. We consider the topological and structural properties of evolving networks, and percolation in these networks. We present a number of models demonstrating the main features of evolving networks and discuss current approaches for their simulation and analytical study. Applications of the general results to particular networks in Nature are discussed. We demonstrate the generic connections of the network growth processes with the general problems of non-equilibrium physics...

Neutral Networks of Sequence to Shape Maps

Jin, Emma Y.; Qin, Jing; Reidys, Christian M.
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.69%
In this paper we present a novel framework for sequence to shape maps. These combinatorial maps realize exponentially many shapes, and have preimages which contain extended connected subgraphs of diameter n (neutral networks). We prove that all basic properties of RNA folding maps also hold for combinatorial maps. Our construction is as follows: suppose we are given a graph $H$ over the $\{1 >...,n\}$ and an alphabet of nucleotides together with a symmetric relation $\mathcal{R}$, implied by base pairing rules. Then the shape of a sequence of length n is the maximal H subgraph in which all pairs of nucleotides incident to H-edges satisfy $\mathcal{R}$. Our main result is to prove the existence of at least $\sqrt{2}^{n-1}$ shapes with extended neutral networks, i.e. shapes that have a preimage with diameter $n$ and a connected component of size at least $(\frac{1+\sqrt{5}}{2})^n+(\frac{1-\sqrt{5}}{2})^n$. Furthermore, we show that there exists a certain subset of shapes which carries a natural graph structure. In this graph any two shapes are connected by a path of shapes with respective neutral networks of distance one. We finally discuss our results and provide a comparison with RNA folding maps.; Comment: 24 pages,4 figures

Spreading dynamics on small-world networks with connectivity fluctuations and correlations

Vazquez, Alexei
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.69%
Infectious diseases and computer malwares spread among humans and computers through the network of contacts among them. These networks are characterized by wide connectivity fluctuations, connectivity correlations and the small-world property. In a previous work [A. Vazquez, Phys. Rev. Lett. 96, 038702 (2006)] I have shown that the connectivity fluctuations together with the small-world property lead to a novel spreading law, characterized by an initial power law growth with an exponent determined by the average node distance on the network. Here I extend these results to consider the influence of connectivity correlations which are generally observed in real networks. I show that assortative and disassortative connectivity correlations enhance and diminish, respectively, the range of validity of this spreading law. As a corollary I obtain the region of connectivity fluctuations and degree correlations characterized by the absence of an epidemic threshold. These results are relevant for the spreading of infectious diseases, rumors, and information among humans and the spreading of computer viruses, email worms and hoaxes among computer users.; Comment: 10 pages, 1 figure, RevTex. Phys. Rev. E (In press)

Structural distance and evolutionary relationship of networks

Banerjee, Anirban
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.69%
Evolutionary mechanism in a self-organized system cause some functional changes that force to adapt new conformation of the interaction pattern between the components of that system. Measuring the structural differences one can retrace the evolutionary relation between two systems. We present a method to quantify the topological distance between two networks of different sizes, finding that the architectures of the networks are more similar within the same class than the outside of their class. With 43 cellular networks of different species, we show that the evolutionary relationship can be elucidated from the structural distances.; Comment: 16 pages, 6 figures, 1 table

Two metrics for general phylogenetic networks

Cardona, Gabriel; Llabres, Merce; Rossello, Francesc; Valiente, Gabriel
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.69%
We prove that Nakhleh's latest dissimilarity measure for phylogenetic networks separates distinguishable phylogenetic networks, and that a slight modification of it provides a true distance on the class of all phylogenetic networks.; Comment: 9 pages

BiMAT: a MATLAB(R) package to facilitate the analysis and visualization of bipartite networks

Flores, Cesar O.; Poisot, Timothée; Valverde, Sergi; Weitz, Joshua S.
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.69%
The statistical analysis of the structure of bipartite ecological networks has increased in importance in recent years. Yet, both algorithms and software packages for the analysis of network structure focus on properties of unipartite networks. In response, we describe BiMAT, an object-oriented MATLAB package for the study of the structure of bipartite ecological networks. BiMAT can analyze the structure of networks, including features such as modularity and nestedness, using a selection of widely-adopted algorithms. BiMAT also includes a variety of null models for evaluating the statistical significance of network properties. BiMAT is capable of performing multi-scale analysis of structure - a potential (and under-examined) feature of many biological networks. Finally, BiMAT relies on the graphics capabilities of MATLAB to enable the visualization of the statistical structure of bipartite networks in either matrix or graph layout representations. BiMAT is available as an open-source package at http://ecotheory.biology.gatech.edu/cflores.; Comment: 15 pages, 5 figures. Plan to be submitted to a Journal

Perfect Sampling of the Master Equation for Gene Regulatory Networks

Hemberg, Martin; Barahona, Mauricio
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.69%
We present a Perfect Sampling algorithm that can be applied to the Master Equation of Gene Regulatory Networks (GRNs). The method recasts Gillespie's Stochastic Simulation Algorithm (SSA) in the light of Markov Chain Monte Carlo methods and combines it with the Dominated Coupling From The Past (DCFTP) algorithm to provide guaranteed sampling from the stationary distribution. We show how the DCFTP-SSA can be generically applied to genetic networks with feedback formed by the interconnection of linear enzymatic reactions and nonlinear Monod- and Hill-type elements. We establish rigorous bounds on the error and convergence of the DCFTP-SSA, as compared to the standard SSA, through a set of increasingly complex examples. Once the building blocks for GRNs have been introduced, the algorithm is applied to study properly averaged dynamic properties of two experimentally relevant genetic networks: the toggle switch, a two-dimensional bistable system, and the repressilator, a six-dimensional genetic oscillator.; Comment: Minor rewriting; final version to be published in Biophysical Journal

Evolutionary and Ecological Trees and Networks

Hernandez-Garcia, E.; Herrada, E. A.; Rozenfeld, A. F.; Tessone, C. J.; Eguiluz, V. M.; Duarte, C. M.; Arnaud-Haond, S.; Serrao, E.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.69%
Evolutionary relationships between species are usually represented in phylogenies, i.e. evolutionary trees, which are a type of networks. The terminal nodes of these trees represent species, which are made of individuals and populations among which gene flow occurs. This flow can also be represented as a network. In this paper we briefly show some properties of these complex networks of evolutionary and ecological relationships. First, we characterize large scale evolutionary relationships in the Tree of Life by a degree distribution. Second, we represent genetic relationships between individuals of a Mediterranean marine plant, Posidonia oceanica, in terms of a Minimum Spanning Tree. Finally, relationships among plant shoots inside populations are represented as networks of genetic similarity.; Comment: 6 pages, 5 figures. To appear in Proceedings of the Medyfinol06 Conference

Modeling Endogenous Social Networks: the Example of Emergence and Stability of Cooperation without Refusal

Chavalarias, David
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.7%
Aggregated phenomena in social sciences and economics are highly dependent on the way individuals interact. To help understanding the interplay between socio-economic activities and underlying social networks, this paper studies a sequential prisoner's dilemma with binary choice. It proposes an analytical and computational insight about the role of endogenous networks in emergence and sustainability of cooperation and exhibits an alternative to the choice and refusal mechanism that is often proposed to explain cooperation. The study focuses on heterogeneous equilibriums and emergence of cooperation from an all-defector state that are the two stylized facts that this model successfully reconstructs.; Comment: 36 p

Density-based and transport-based core-periphery structures in networks

Lee, Sang Hoon; Cucuringu, Mihai; Porter, Mason A.
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.71%
Networks often possess mesoscale structures, and studying them can yield insights into both structure and function. It is most common to study community structure, but numerous other types of mesoscale structures also exist. In this paper, we examine core-periphery structures based on both density and transport. In such structures, core network components are well-connected both among themselves and to peripheral components, which are not well-connected to anything. We examine core-periphery structures in a wide range of examples of transportation, social, and financial networks---including road networks in large urban areas, a rabbit warren, a dolphin social network, a European interbank network, and a migration network between counties in the United States. We illustrate that a recently developed transport-based notion of node coreness is very useful for characterizing transportation networks. We also generalize this notion to examine core versus peripheral edges, and we show that the resulting diagnostic is also useful for transportation networks. To examine the properties of transportation networks further, we develop a family of generative models of roadlike networks. We illustrate the effect of the dimensionality of the embedding space on transportation networks...

Criticality of spreading dynamics in hierarchical cluster networks without inhibition

Kaiser, Marcus; Goerner, Matthias; Hilgetag, Claus C.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.69%
An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable network activations within a limited critical range. In this range, the activity of neural populations in the network persists between the extremes of quickly dying out, or activating the whole network. The nerve fiber network of the mammalian cerebral cortex possesses a modular organization extending across several levels of organization. Using a basic spreading model without inhibition, we investigated how functional activations of nodes propagate through such a hierarchically clustered network. The simulations demonstrated that persistent and scalable activation could be produced in clustered networks, but not in random networks of the same size. Moreover, the parameter range yielding critical activations was substantially larger in hierarchical cluster networks than in small-world networks of the same size. These findings indicate that a hierarchical cluster architecture may provide the structural basis for the stable and diverse functional patterns observed in cortical networks.

Schwarzkopf, Yonathan; Rakos, Attila; Mukamel, David
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.69%
A model for epidemic spreading on rewiring networks is introduced and analyzed for the case of scale free steady state networks. It is found that contrary to what one would have naively expected, the rewiring process typically tends to suppress epidemic spreading. In particular it is found that as in static networks, rewiring networks with degree distribution exponent $\gamma >3$ exhibit a threshold in the infection rate below which epidemics die out in the steady state. However the threshold is higher in the rewiring case. For $2<\gamma \leq 3$ no such threshold exists, but for small infection rate the steady state density of infected nodes (prevalence) is smaller for rewiring networks.; Comment: 7 pages, 7 figures

Systems biology beyond degree, hubs and scale-free networks: the case for multiple metrics in complex networks

Roy, Soumen
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.71%
Modeling and topological analysis of networks in biological and other complex systems, must venture beyond the limited consideration of very few network metrics like degree, betweenness or assortativity. A proper identification of informative and redundant entities from many different metrics, using recently demonstrated techniques, is essential. A holistic comparison of networks and growth models is best achieved only with the use of such methods.; Comment: To appear in Systems and Synthetic Biology (Springer)

Modelling slowly changing dynamic gene-regulatory networks

Abbruzzo, Antonino; Wit, Ernst
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.7%
Dynamic gene-regulatory networks are complex since the number of potential components involved in the system is very large. Estimating dynamic networks is an important task because they compromise valuable information about interactions among genes. Graphical models are a powerful class of models to estimate conditional independence among random variables, e.g. interactions in dynamic systems. Indeed, these interactions tend to vary over time. However, the literature has been focused on static networks, which can only reveal overall structures. Time-course experiments are performed in order to tease out significant changes in networks. It is typically reasonable to assume that changes in genomic networks are few because systems in biology tend to be stable. We introduce a new model for estimating slowly changes in dynamic gene-regulatory networks which is suitable for a high-dimensional dataset, e.g. time-course genomic data. Our method is based on i) the penalized likelihood with $\ell_1$-norm, ii) the penalized differences between conditional independence elements across time points and iii) the heuristic search strategy to find optimal smoothing parameters. We implement a set of linear constraints necessary to estimate sparse graphs and penalized changing in dynamic networks. These constraints are not in the linear form. For this reason...

Quantifying Stochastic Effects in Biochemical Reaction Networks using Partitioned Leaping

Harris, Leonard A.; Piccirilli, Aaron M.; Majusiak, Emily R.; Clancy, Paulette
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.69%
"Leaping" methods show great promise for significantly accelerating stochastic simulations of complex biochemical reaction networks. However, few practical applications of leaping have appeared in the literature to date. Here, we address this issue using the "partitioned leaping algorithm" (PLA) [L.A. Harris and P. Clancy, J. Chem. Phys. 125, 144107 (2006)], a recently-introduced multiscale leaping approach. We use the PLA to investigate stochastic effects in two model biochemical reaction networks. The networks that we consider are simple enough so as to be accessible to our intuition but sufficiently complex so as to be generally representative of real biological systems. We demonstrate how the PLA allows us to quantify subtle effects of stochasticity in these systems that would be difficult to ascertain otherwise as well as not-so-subtle behaviors that would strain commonly-used "exact" stochastic methods. We also illustrate bottlenecks that can hinder the approach and exemplify and discuss possible strategies for overcoming them. Overall, our aim is to aid and motivate future applications of leaping by providing stark illustrations of the benefits of the method while at the same time elucidating obstacles that are often encountered in practice.; Comment: v3: Final accepted version. 15 pages...

Stochastic models and numerical algorithms for a class of regulatory gene networks

Fournier, Thomas; Gabriel, Jean-Pierre; Mazza, Christian; Pasquier, Jerome; Galbete, Jose; Mermod, Nicolas
Tipo: Artigo de Revista Científica