dannya222's Top Recommendations

Abstract

Recently there has been considerable interest in learning with higher order relations (i.e., three-way or higher) in the unsupervised and semi-supervised settings. Hypergraphs and tensors have been proposed as the natural way of representing these relations and their corresponding algebra as the natural tools for operating on them. In this paper we argue that hypergraphs are not a natural representation for higher order relations, indeed pairwise as well as higher order relations can be handled using graphs. We show that various ...

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<p>Sams has assembled a team of experts in web services to provide you with a detailed reference guide on XML, SOAP, USDL and UDDI. <i>Building Web Services with Java</i> is in its second edition and it includes the newest standards for managing security, transactions, reliability and interoperability in web service applications. Go beyond the explanations of standards and find out how and why these tools were designed as they are and focus on practical examples of each concept. Download your source ...

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Introduction In many applications of graph algorithms, including communication networks, graphics, assembly planning, and VLSI design, graphs are subject to discrete changes, such as additions or deletions of edges or vertices. In the last decade there has been a growing interest in such dynamically changing graphs, and a whole body of algorithms and data structures for dynamic graphs has been discovered. This chapter is intended as an overview of this field. In a typical dynamic graph problem ... ...

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We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques. ...

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Although the interest of a Web page is strictly related to its content and to the subjective readers' cultural background, a measure of the page authority can be provided that only depends on the topological structure of the Web. PageRank is a noticeable way to attach a score to Web pages on the basis of the Web connectivity. In this article, we look inside PageRank to disclose its fundamental properties concerning stability, complexity of computational scheme, and critical role of parameters ...

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Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the detection and characterization of power laws is complicated by the large fluctuations that occur in the tail of the distribution -- the part of the distribution representing large but rare events -- and by the difficulty of identifying the range over which power-law behavior holds. Commonly used methods for analyzing power-law data, such as least-squares fitting, can produce substantially inaccurate estimates of parameters for power-law distributions, ...

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The rich set of interactions between individuals in society1, 2, 3, 4, 5, 6, 7 results in complex community structure, capturing highly connected circles of friends, families or professional cliques in a social network3, 7, 8, 9, 10. Thanks to frequent changes in the activity and communication patterns of individuals, the associated social and communication network is subject to constant evolution7, 11, 12, 13, 14, 15, 16. Our knowledge of the mechanisms governing the underlying community dynamics is limited, but is ...

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A network is said to show assortative mixing if the nodes in the network that have many connections tend to be connected to other nodes with many connections. Here we measure mixing patterns in a variety of networks and find that social networks are mostly assortatively mixed, but that technological and biological networks tend to be disassortative. We propose a model of an assortatively mixed network, which we study both analytically and numerically. Within this model we find that networks percolate ...

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Complex networks from such different fields as biology, technology or sociology share similar organization principles. The possibility of a unique growth mechanism promises to uncover universal origins of collective behaviour. In particular, the emergence of self-similarity in complex networks raises the fundamental question of the growth process according to which these structures evolve. Here we investigate the concept of renormalization as a mechanism for the growth of fractal and non-fractal modular networks. We show that the key principle that gives rise ...

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Complex networks describe a wide range of systems in nature and society. Frequently cited examples include the cell, a network of chemicals linked by chemical reactions, and the Internet, a network of routers and computers connected by physical links. While traditionally these systems have been modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks are governed by robust organizing principles. This article reviews the recent advances in the field of complex networks, focusing on ...

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Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected dynamical units. The first approach to capture the global properties of such systems is to model them as graphs whose nodes represent the dynamical units, and whose links stand for the interactions between them. On the one hand, scientists have to cope with structural issues, such as characterizing the ...

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10.1126/science.1065103 ...

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10.1126/science.287.5461.2115a ...

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Complex networks have been studied extensively owing to their relevance to many real systems such as the world-wide web, the Internet, energy landscapes and biological and social networks1, 2, 3, 4, 5. A large number of real networks are referred to as 'scale-free' because they show a power-law distribution of the number of links per node1, 6, 7. However, it is widely believed that complex networks are not invariant or self-similar under a length-scale transformation. This conclusion originates from the 'small-world' ...

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A number of recent studies have focused on the statistical properties of networked systems such as social networks and the Worldwide Web. Researchers have concentrated particularly on a few properties that seem to be common to many networks: the small-world property, power-law degree distributions, and network transitivity. In this article, we highlight another property that is found in many networks, the property of community structure, in which network nodes are joined together in tightly knit groups, between which there are only ...

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The structure of scientific collaboration networks is investigated. Two scientists are considered connected if they have authored a paper together and explicit networks of such connections are constructed by using data drawn from a number of databases, including MEDLINE (biomedical research), the Los Alamos e-Print Archive (physics), and NCSTRL (computer science). I show that these collaboration networks form “small worlds,” in which randomly chosen pairs of scientists are typically separated by only a short path of intermediate acquaintances. I further give ...

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10.1126/science.286.5439.509 ...

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In a cell or microorganism, the processes that generate mass, energy, information transfer and cell-fate specification are seamlessly integrated through a complex network of cellular constituents and reactions1. However, despite the key role of these networks in sustaining cellular functions, their large-scale structure is essentially unknown. Here we present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variation in their individual constituents and pathways, these metabolic ...

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For decades, we tacitly assumed that the components of such complex systems as the cell, the society, or the Internet are randomly wired together. In the past decade, an avalanche of research has shown that many real networks, independent of their age, function, and scope, converge to similar architectures, a universality that allowed researchers from different disciplines to embrace network theory as a common paradigm. The decade-old discovery of scale-free networks was one of those events that had helped catalyze the ...

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In memory of Leo Szilard, who passed away on May 30,1964, we present an English translation of his classical paper ober die Enfropieuerminderung in einem thermodynamischen System bei Eingrifen intelligenter Wesen, which appeared in the Zeitschrift fur Physik, 1929,53,840-856. The publication in this journal of this translation was approved by Dr. Szilard before he died, but he never saw the copy. At Mrs. Szilard's request, Dr. Carl Eckart revised the translation.This is one of the earliest, if not the earliest paper, ...

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The Internet has a very complex connectivity recently modeled by the class of scale-free networks. This feature; which appears to be very efficient for a communications network; favors at the same time the spreading of computer viruses. We analyze real data from computer virus infections and find the average lifetime and persistence of viral strains on the Internet. We define a dynamical model for the spreading of infections on scale-free networks; finding the absence of an epidemic threshold and its associated ...

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Cellular automata are used as simple mathematical models to investigate self-organization in statistical mechanics. A detailed analysis is given of "elementary" cellular automata consisting of a sequence of sites with values 0 or 1 on a line; with each site evolving deterministically in discrete time steps according to definite rules involving the values of its nearest neighbors. With simple initial configurations; the cellular automata either tend to homogeneous states; or generate self-similar patterns with fractal dimensions ≃ 1.59 or ≃ 1.69. ...

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We review the recent rapid progress in the statistical physics of evolving networks. Interest has focused mainly on the structural properties of complex networks in communications, biology, social sciences and economics. A number of giant artificial networks of this kind have recently been created, which opens a wide field for the study of their topology, evolution, and the complex processes which occur in them. Such networks possess a rich set of scaling properties. A number of them are scale-free and show ...

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Boolean networks serve as models for complex systems; such as social or genetic networks; where each vertex; based on inputs received from selected vertices; makes its own decision about its state. Despite their simplicity; little is known about the dynamical properties of these systems. Here we propose a method to calculate the period of a finite Boolean system; by identifying the mechanisms determining its value. The proposed method can be applied to systems of arbitrary topology; and can serve as a ...

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Studies of large, randomly assembled binary (Boolean) node automata have demonstrated that such systems can spontaneously exhibit enormously ordered dynamical behavior. An important approach to characterizing these behaviors has consisted of studying ensembles of automata. Ensemble specifications have been based on: 1) choice of Boolean function regulating each node in the automaton; 2) random or biased mappings of the 2 N automata states into themselves; 3) the numbers of inputs, K , per node. This article briefly reviews these ...

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The basis of science is the hypothetico-deductive method and the recording of experiments in sufficient detail to enable reproducibility. We report the development of Robot Scientist "Adam," which advances the automation of both. Adam has autonomously generated functional genomics hypotheses about the yeast Saccharomyces cerevisiae and experimentally tested these hypotheses by using laboratory automation. We have confirmed Adam's conclusions through manual experiments. To describe Adam's research, we have developed an ontology and logical language. The resulting formalization involves over 10,000 different ...

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For centuries, scientists have attempted to identify and document analytical laws that underlie physical phenomena in nature. Despite the prevalence of computing power, the process of finding natural laws and their corresponding equations has resisted automation. A key challenge to finding analytic relations automatically is defining algorithmically what makes a correlation in observed data important and insightful. We propose a principle for the identification of nontriviality. We demonstrated this approach by automatically searching motion-tracking data captured from various physical systems, ranging ...

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doi: 10.1086/415929 ...

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doi: 10.1086/394562 ...

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Synchronization phenomena in large populations of interacting elements are the subject of intense research efforts in physical; biological; chemical; and social systems. A successful approach to the problem of synchronization consists of modeling each member of the population as a phase oscillator. In this review; synchronization is analyzed in one of the most representative models of coupled phase oscillators; the Kuramoto model. A rigorous mathematical treatment; specific numerical methods; and many variations and extensions of the original model that have appeared ...

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The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact. ...

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Zusammenfassung Der Beschreibung der zeitlichen Entwicklung lebender Systeme kann eine reine Differentialanalyse nicht genügen. In solchen Fällen muss man sich an Stelle der gewöhnlichen Differentialgleichungen der integraldifferentiellen, bezw. der Integralgleichungen bedienen. Zur leichteren Veranschaulichung der mathematischen Darstellung betrachtet Verfasser zuerst diejenigen Systeme, deren innerer Zustand sich durch ein einziges Parameterc bestimmen lässt. Die zeitliche Entwicklung eines leblosen Systems dieser Klasse werde durch die Differentialgleichung (I) dargestellt, wot=Zeit, undk eine Funktion der äusseren Parametera, ?, ?. ist. Im Falle eines jeden Systems ...

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This paper considers the nature of a non-linear, two-dimensional solution of the Navier-Stokes equations when the rate of amplification of the disturbance, at a given wave-number and Reynolds number, is sufficiently small. Two types of problem arise: (i) to follow the growth of an unstable, infinitesimal disturbance (supercritical problem), possibly to a state of stable equilibrium; (ii) for values of the wave-number and Reynolds number for which no unstable infinitesimal disturbance exists, to follow the decay of a finite disturbance from ...

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A much-needed theoretical analysis deals with whether the principle known as 'costly punishment' helps to maintain cooperation in human society. It will prompt a fresh wave of experiments and theory. ...

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Synchronization processes in populations of locally interacting elements are the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understanding synchronization phenomena in natural systems now take advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also take an overview of the new emergent features coming out from ...

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Unanticipated changes to complex software systems can introduce anomalies such as duplicated code, suboptimal inheritance relationships and a proliferation of run-time downcasts. Refactoring to eliminate these anomalies may not be an option, at least in certain stages of software evolution. Classboxes are modules that restrict the visibility of changes to selected clients only, thereby offering more freedom in the way unanticipated changes may be implemented, and thus reducing the need for convoluted design anomalies. In this paper we demonstrate ...

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<p> Methods of squaring and multiplying large integers are discussed. The obvious O(n/sup 2/) methods turn out to be best for small numbers. Existing O(n/sup log/ /sup 3/log/ /sup 2/)/spl ap/O(n/sup 1.585/) methods become better as the numbers get bigger. New methods that are O(/sup log5/log/ /sup 3/)/spl ap/0(n/sup 1.465/), O(n/sup log/ /sup 7/log/ /sup 4/)/spl ap/O(n/sup 1.404/), and O(n/sup log/ /sup 9/log/ /sup 5/)/spl ap/O(n/sup 1.365/) presented. In actual experiments, all of these methods turn out to be faster than ...

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Abstract.   We investigate the connection between the dynamics of synchronization and the modularity on complex networks. Simulating the Kuramoto's model in complex networks we determine patterns of meta-stability and calculate the modularity of the partition these patterns provide. The results indicate that the more stable the patterns are, the larger tends to be the modularity of the partition defined by them. This correlation works pretty well in homogeneous networks (all nodes have similar connectivity) but fails when networks contain hubs, mainly ...

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Abstract  An ad-hoc network is temporarily formed by a group of mobile hosts communicating over wireless channels without any fixed network interaction and centralized administration. When a mobile host communicates with other mobile hosts in an ad-hoc network, the routes are established via the intermediate mobile hosts as forwarding nodes. Under such a network environment an adaptive approach for routing management will be proposed in this paper. In this approach, at first the network infrastructure is constructed by several communication groups, which ...

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Although aircraft encounters with strong westerly winds during World War II provided the stimulus for postwar research on the jet stream, Wasaburo Ooishi observed these winds in the 1920s. Ooishi's work is reviewed in the context of earlier work in upperair observation and postwar work on the jet stream. An effort is made to reconstruct Ooishi's path to the directorship of Japan's first upper-air observatory by reliance on historical studies and memoirs from the Central Meteorological Observatory. Archival records from Japan's ...

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Complex networks, modeled as large graphs, received much attention during these last years. However, topological information on these networks is only available through intricate measurement procedures. Until recently, most studies assumed that these procedures eventually lead to samples large enough to be representative of the whole, at least concerning some key properties. This has a crucial impact on network modeling and simulation, which rely on these properties. Recent contributions proved that this assumption may be misleading, but no solution has been ...

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Two natural and widely used representations for the community structure of networks are clusterings, which partition the vertex set into disjoint subsets, and layouts, which assign the vertices to positions in a metric space. This paper unifies prominent characterizations of layout quality and clustering quality, by showing that energy models of pairwise attraction and repulsion subsume Newman and Girvan's modularity measure. Layouts with optimal energy are relaxations of, and are thus consistent with, clusterings with optimal modularity, which is of practical relevance because both representations are complementary and often ...

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We propose a new global optimization method (Simulated Tempering) for simulating effectively a system with a rough free-energy landscape (i.e., many coexisting states) at finite nonzero temperature. This method is related to simulated annealing, but here the temperature becomes a dynamic variable, and the system is always kept at equilibrium. We analyse the method on the Random Field Ising Model, and we find a dramatic improvement over conventional Metropolis and cluster methods. We analyse and discuss the conditions under which the ...

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In this paper we present an algorithm for drawing an undirected graph G which takes advantage of the structure of the modular decomposition tree of G. Specifically, our algorithm works by traversing the modular decomposition tree of the input graph G on n vertices and m edges, in a bottom-up fashion until it reaches the root of the tree, while at the same time intermediate drawings are computed. In order to achieve aesthetically pleasing results, we use grid and circular placement techniques, ...

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The mathematical models of populations of biological oscillators are a powerful tool for designing sensor networks with high energy efficiency, fault tolerance and scalability. Recently, Hong and Scaglione have proposed a novel design paradigm, based on pulse coupled oscillators, where the decision of each sensor is encoded as the time position of the emitted pulses. In this work, we propose an alternative approach, based on linear (not necessarily pulse) oscillators with nonlinear coupling, that provides a novel framework to design sensor ...

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In this paper we study the synchronization properties of random geometric graphs. We show that the onset of synchronization takes place roughly at the same value of the order parameter that a random graph with the same size and average connectivity. However, the dependence of the order parameter with the coupling strength indicates that the fully synchronized state is more easily attained in random graphs. We next focus on the complete synchronized state and show that this state is less stable for random geometric graphs than for ...

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An event-driven method for parallel simulation of a class dynamic Monte Carlo models is presented. The method can be applied to several models studied in the computational physics such as Ising spin simulations by the method of Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller, continuous time Ising spin simulation by Glauber, and the dynamic binary alloy simulation. Unlike previously known parallel multi-spin algorithms, the proposed algorithms do not change the simulated model. For example, the asynchrony and randomness of update time arrivals ...

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Without Abstract ...

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Prior research on artificial agents/agencies involves entities using specifically tailored operational strategies (e.g., for information retrieval, purchase negotiation). In some situations, however, an agent must interact with others whose strategies are initially unknown and whose interests may counter its own. In such circumstances, pre-defining effective counter-strategies could become difficult or impractical. One solution, which may be viable in certain contexts, is to create agents that self-evolve increasingly effective strategies from rudimentary beginnings, during actual deployment. Using the Iterated Prisoner's Dilemma (IPD) ...

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In this Letter we discuss a method for generating synchrony-optimized coupling architectures of Kuramoto oscillators with a heterogeneous distribution of native frequencies. The method allows us to relate the properties of the coupling network to its synchronizability. These relations were previously only established from a linear stability analysis of the identical oscillator case. We further demonstrate that the heterogeneity in the oscillator population produces heterogeneity in the optimal coupling network as well. Two rules for enhancing the synchronizability of a given ...

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Since its introduction in the year 1998 by Watts and Strogatz, the clustering coefficient has become a frequently used tool for analyzing graphs. In 2002 the transitivity was proposed by Newman, Watts and Strogatz as an alternative to the clustering coefficient. As many networks considered in complex systems are huge, the efficient computation of such network parameters is crucial. Several algorithms with polynomial running time can be derived from results known in graph theory. The main contribution of this work is ...

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The betweenness centrality index is essential in the analysis of social networks, but costly to compute. Currently, the fastest known algorithms require Θ(n 3) time and Θ(n 2) space, where n is the number of actors in the network. Motivated by the fast-growing need to compute centrality indices on large, yet very sparse, networks, new algorithms for betweenness are introduced in this paper. They require O(n + m) space and run in O(nm) and O(nm + n 2 log n) time ...

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Network's resilience to the malfunction of its components has been of great concern. The goal of this work is to determine the network design guidelines, which maximizes the network efficiency while keeping the cost of the network (that is the average connectivity) constant. With a global optimization method, memory tabu search (MTS), we get the optimal network structure with the approximately best efficiency. We analyze the statistical characters of the network and find that a network with a small quantity of ...

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Abstract.  In this paper we examine a number of methods for probing and understanding the large-scale structure of networks that evolve over time. We focus in particular on citation networks, networks of references between documents such as papers, patents, or court cases. We describe three different methods of analysis, one based on an expectation-maximization algorithm, one based on modularity optimization, and one based on eigenvector centrality. Using the network of citations between opinions of the United States Supreme Court as an example, ...

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Mercator is a program that uses hop-limited probes-the same primitive used in traceroute-to infer an Internet map. It uses informed random address probing to carefully exploring the IP address space when determining router adjacencies, uses source-route capable routers wherever possible to enhance the fidelity of the resulting map, and employs novel mechanisms for resolving aliases (interfaces belonging to the same router). This paper describes the design of these heuristics and our experiences with Mercator, and presents some preliminary analysis of the ...

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This purpose of this introductory paper is threefold. First, it introduces the Monte Carlo method with emphasis on probabilistic machine learning. Second, it reviews the main building blocks of modern Markov chain Monte Carlo simulation, thereby providing and introduction to the remaining papers of this special issue. Lastly, it discusses new interesting research horizons. ...

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One paradigm for sensitivity analyses in Bayesian statistics is to specify Γ, a reasonable class of priors, and to compute the corresponding class of posterior inferences. The class Γ is chosen to represent uncertainty about the prior. There is often additional uncertainty, however, about the family of sampling distributions. This article introduces a method for computing ranges of posterior expectations over reasonable classes of sampling distributions that lie "close to" a given parametric family. By treating the prior as a probability ...

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We consider Thomas Bayes's famous Scholium--his argument in defence of an a priori uniform distribution for an unknown probability, and argue that critics (R. A. Fisher) and friends (Karl Pearson, Harold Jeffreys) alike have misinterpreted the argument as an appeal to the principle of insufficient reason, and that Bayes's actual argument is free from the principal defect it has been charged with. True "Bayesian Inference" is found to differ considerably from and perhaps be logically preferable to modern perceptions of it. ...

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Modular decomposition is fundamental for many important problems in algorithmic graph theory including transitive orientation, the recognition of several classes of graphs, and certain combinatorial optimization problems. Accordingly, there has been a drive towards a practical, linear-time algorithm for the problem. This paper posits such an algorithm; we present a linear-time modular decomposition algorithm that proceeds in four straightforward steps. This is achieved by introducing the notion of factorizing permutations to an earlier recursive approach. The only data structure used is ...

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We study the transition from incoherence to coherence in large networks of coupled phase oscillators. We present various approximations that describe the behavior of an appropriately defined order parameter past the transition and generalize recent results for the critical coupling strength. We find that, under appropriate conditions, the coupling strength at which the transition occurs is determined by the largest eigenvalue of the adjacency matrix. We show how, with an additional assumption, a mean-field approximation recently proposed is recovered from our ...

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We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary; on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the ...

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Ensembl's human non-coding and protein coding genes are used to automatically find DNA pattern motifs. The Backus-Naur form (BNF) grammar for regular expressions (RE) is used by genetic programming to ensure the generated strings are legal. The evolved motif suggests the presence of Thymine followed by one or more Adenines etc. early in transcripts indicate a non-protein coding gene. Keywords: pseudogene, short and microRNAs, non-coding transcripts, systems biology, machine learning, Bioinformatics, motif, regular expression, strongly typed genetic programming, context-free grammar. ...

Abstract

Complex networks have acquired a great popularity in recent years, since the graph representation of many natural, social, and technological systems is often very helpful to characterize and model their phenomenology. Additionally, the mathematical tools of statistical physics have proven to be particularly suitable for studying and understanding complex networks. Nevertheless, an important obstacle to this theoretical approach is still represented by the difficulties to draw parallelisms between network science and more traditional aspects of statistical physics. In this paper, we ...

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Random critical branching trees (CBTs) are generated by the multiplicative branching process, where the branching number is determined stochastically, independent of the degree of their ancestor. Here we show analytically that despite this stochastic independence, there exists the degree-degree correlation (DDC) in the CBT and it is disassortative. Moreover, the skeletons of fractal networks, the maximum spanning trees formed by the edge betweenness centrality, behave similarly to the CBT in the DDC. This analytic solution and observation support the argument that ...

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Fractal scaling—a power-law behavior of the number of boxes needed to tile a given network with respect to the lateral size of the box—is studied. We introduce a box-covering algorithm that is a modified version of the original algorithm introduced by Song et al. [Nature (London) 433 , 392 (2005)]; this algorithm enables easy implementation. Fractal networks are viewed as comprising a skeleton and shortcuts. The skeleton, embedded underneath the original network, is a special type of spanning ...

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We investigate the properties of the spanning trees of various real-world and model networks. The spanning tree representing the communication kernel of the original network is determined by maximizing the total weight of the edges, whose weights are given by the edge betweenness centralities. We find that a scale-free tree and shortcuts organize a complex network. Especially, in ubiquitous scale-free networks, it is found that the scale-free spanning tree shows very robust betweenness centrality distributions and the remaining shortcuts characterize the ...

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We report the simultaneous characterization of time- and force-dependent mechanical properties of adherent cells in the physiologically relevant regime of large forces. We used magnetic tweezers to apply forces to magnetic beads bound to the cytoskeleton, and recorded the resulting deformation (creep response). The creep response followed a weak power law at all force levels. Stress stiffening and fluidization occurred simultaneously and were quantified by the force-dependence of the creep compliance and the power law exponent. The amount of stiffening and fluidization in response to force was controlled solely ...

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I describe a method to estimate a social network topology and diffusion parameters from the time sequence data of an infectious disease outbreak. The method is applicable to a stochastic diffusion process in a meta-population and SIR (Susceptible, Infectious, and Recovered) model over a social network. The method is based on the maximal likelihood estimation from the data on the number of the infectious persons. I demonstrate the performance of the method of profiling with the WHO (World Health Organization) report on SARS (Severe Acute Respiratory Syndrome) pandemic ...

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In the human genomes, recombination frequency between homologous chromosomes during meiosis is highly correlated with their physical length while it differs significantly when their coding density is considered. Furthermore, it has been observed that the recombination events are distributed unevenly along the chromosomes. We have found that many of such recombination properties can be predicted by computer simulations of population evolution based on the Monte Carlo methods. For example, these simulations have shown that the probability of acceptance of the recombination events by selection is higher at the ...

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Cell differentiation in multicellular organisms is a complex process whose mechanism can be understood by a reductionist approach, in which the individual processes that control the generation of different cell types are identified. Alternatively, a large scale approach in search of different organizational features of the growth stages promises to reveal its modular global structure with the goal of discovering previously unknown relations between cell types. Here we sort and analyze a large set of scattered data to construct the network of human cell differentiation (NHCD) based on ...

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Randomly packing spheres of equal size into a container consistently results in a static configuration with a density of ~64%. The ubiquity of random close packing (RCP) rather than the optimal crystalline array at 74% begs the question of the physical law behind this empirically deduced state. Indeed, there is no signature of any macroscopic quantity with a discontinuity associated with the observed packing limit. Here we show that RCP can be interpreted as a manifestation of a thermodynamic singularity, which defines it as the "freezing point" in ...

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It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a “module� in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN) by searching for such cohesive groups of proteins. Here, we present an alternative approach independent of any prior definition of what ...

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Robust multiarray analysis (RMA) is the most widely used preprocessing algorithm for Affymetrix and Nimblegen gene expression microarrays. RMA performs background correction, normalization, and summarization in a modular way. The last 2 steps require multiple arrays to be analyzed simultaneously. The ability to borrow information across samples provides RMA various advantages. For example, the summarization step fits a parametric model that accounts for probe effects, assumed to be fixed across arrays, and improves outlier detection. Residuals, obtained from the fitted model, ...

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With the completion of human genome mapping, the focus of scientists seeking to explain the biological complexity of living systems is shifting from analyzing the individual components (such as a particular gene or biochemical reaction) to understanding the set of interactions amongst the large number of components that results in the different functions of the organism. To this end, the area of systems biology attempts to achieve a "systems-level" description of biology by focusing on the network of interactions instead of the characteristics of its isolated parts. In ...

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We analyze gene co-expression network under the random matrix theory framework. The nearest neighbor spacing distribution of the adjacency matrix of this network follows Gaussian orthogonal statistics of random matrix theory (RMT). Spectral rigidity test follows random matrix prediction for a certain range, and deviates after wards. Eigenvector analysis of the network using inverse participation ratio (IPR) suggests that the statistics of bulk of the eigenvalues of network is consistent with those of the real symmetric random matrix, whereas few eigenvalues are localized. Based on these IPR calculations, we ...

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Recent experiments on cortical neural networks have revealed the existence of well-defined avalanches of electrical activity. Such avalanches have been claimed to be generically scale-invariant -- i.e. power-law distributed -- with many exciting implications in Neuroscience. Recently, a self-organized model has been proposed by Levina, Herrmann and Geisel to justify such an empirical finding. Given that (i) neural dynamics is dissipative and (ii) there is a loading mechanism "charging" progressively the background synaptic strength, this model/dynamics is very similar in spirit to forest-fire and earthquake models, archetypical examples of ...

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10.1126/science.1185570 ...

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Transport networks are ubiquitous in both social and biological systems. Robust network performance involves a complex trade-off involving cost, transport efficiency, and fault tolerance. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield reasonable solutions to such combinatorial optimization problems. Furthermore, they develop without centralized control and may represent a readily scalable solution for growing networks in general. We show that the slime mold Physarum polycephalum forms networks with comparable efficiency, fault tolerance, ...

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A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping ...

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We show that renormalization group (RG) theory applied to complex networks is useful to classify network topologies into universality classes in the space of configurations. The RG flow readily identifies a small-world–fractal transition by finding (i) a trivial stable fixed point of a complete graph, (ii) a nontrivial point of a pure fractal topology that is stable or unstable according to the amount of long-range links in the network, and (iii) another stable point of a fractal with shortcuts that exist exactly at the ...