Showing papers by "Albert-László Barabási published in 2005"

The origin of bursts and heavy tails in human dynamics

Abstract: What determines the timing of human actions? A big question, but the science of human dynamics is here to tackle it. And its predictions are of practical value: for example, when ISPs decide what bandwidth an institution needs, they use a model of the likely timing and activity level of the individuals. Current models assume that an individual has a well defined probability of engaging in a specific action at a given moment, but evidence that the timing of human actions does not follow this pattern (of Poisson statistics) is emerging. Instead the delay between two consecutive events is best described by a heavy-tailed (power law) distribution. Albert-Laszlo Barabasi proposes an explanation for the prevalence of this behaviour. The ‘bursty’ nature of human dynamics, he finds, is a fundamental consequence of decision making. The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behaviour into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes1,2,3. In contrast, there is increasing evidence that the timing of many human activities, ranging from communication to entertainment and work patterns, follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity4,5,6,7,8. Here I show that the bursty nature of human behaviour is a consequence of a decision-based queuing process9,10: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, with most tasks being rapidly executed, whereas a few experience very long waiting times. In contrast, random or priority blind execution is well approximated by uniform inter-event statistics. These finding have important implications, ranging from resource management to service allocation, in both communications and retail.

Human dynamics: Darwin and Einstein correspondence patterns.

Abstract: These scientists prioritized their replies to letters in the same way that people rate their e-mails today.

Human Dynamics: The Correspondence Patterns of Darwin and Einstein

Abstract: While living in different historical era, Charles Darwin (1809-1882) and Albert Einstein (1879-1955) were both prolific correspondents: Darwin sent (received) at least 7,591 (6,530) letters during his lifetime while Einstein sent (received) over 14,500 (16,200). Before email scientists were part of an extensive university of letters, the main venue for exchanging new ideas and results. But were the communication patterns of the pre-email times any different from the current era of instant access? Here we show that while the means have changed, the communication dynamics has not: Darwin's and Einstein's pattern of correspondence and today's electronic exchanges follow the same scaling laws. Their communication belongs, however, to a different universality class from email communication, providing evidence for a new class of phenomena capturing human dynamics.

Topological units of environmental signal processing in the transcriptional regulatory network of Escherichia coli

Abstract: Recent evidence indicates that potential interactions within metabolic, protein-protein interaction, and transcriptional regulatory networks are used differentially according to the environmental conditions in which a cell exists. However, the topological units underlying such differential utilization are not understood. Here we use the transcriptional regulatory network of Escherichia coli to identify such units, called origons, representing regulatory subnetworks that originate at a distinct class of sensor transcription factors. Using microarray data, we find that specific environmental signals affect mRNA expression levels significantly only within the origons responsible for their detection and processing. We also show that small regulatory interaction patterns, called subgraphs and motifs, occupy distinct positions in and between origons, offering insights into their dynamical role in information processing. The identified features are likely to represent a general framework for environmental signal processing in prokaryotes.

Network Theory--the Emergence of the Creative Enterprise

Abstract: In both the arts and sciences, there are certain characteristics that set apart creative "dream teams". But can these characteristics be explained mathematically, asks Barabasi in his [Perspective][1]? A new study that mathematically examines the creative teams responsible for Broadway shows and landmark scientific papers reveals the key elements that underpin team creativity and success ([ GuimerAi et al .][2]). [1]: http://www.sciencemag.org/cgi/content/full/308/5722/639 [2]: http://www.sciencemag.org/cgi/content/short/308/5722/697

The Activity Reaction Core and Plasticity of Metabolic Networks

Abstract: Understanding the system-level adaptive changes taking place in an organism in response to variations in the environment is a key issue of contemporary biology. Current modeling approaches, such as constraint-based flux-balance analysis, have proved highly successful in analyzing the capabilities of cellular metabolism, including its capacity to predict deletion phenotypes, the ability to calculate the relative flux values of metabolic reactions, and the capability to identify properties of optimal growth states. Here, we use flux-balance analysis to thoroughly assess the activity of Escherichia coli, Helicobacter pylori, and Saccharomyces cerevisiae metabolism in 30,000 diverse simulated environments. We identify a set of metabolic reactions forming a connected metabolic core that carry non-zero fluxes under all growth conditions, and whose flux variations are highly correlated. Furthermore, we find that the enzymes catalyzing the core reactions display a considerably higher fraction of phenotypic essentiality and evolutionary conservation than those catalyzing noncore reactions. Cellular metabolism is characterized by a large number of species-specific conditionally active reactions organized around an evolutionary conserved, but always active, metabolic core. Finally, we find that most current antibiotics interfering with bacterial metabolism target the core enzymes, indicating that our findings may have important implications for antimicrobial drug-target discovery.

Minimum spanning trees of weighted scale-free networks

Abstract: A complete characterization of real networks requires us to understand the consequences of the uneven interaction strengths between a system's components. Here we use minimum spanning trees (MSTs) to explore the effect of correlations between link weights and network topology on scale-free networks. Solely by changing the nature of the correlations between weights and network topology, the structure of the MSTs can change from scale-free to exponential. Additionally, for some choices of weight correlations, the efficiency of the MSTs increases with increasing network size, a result with potential implications for the design and scalability of communication networks.

Inhomogeneous evolution of subgraphs and cycles in complex networks.

Abstract: Subgraphs and cycles are often used to characterize the local properties of complex networks Here we show that the subgraph structure of real networks is highly time dependent: as the network grows, the density of some subgraphs remains unchanged, while the density of others increase at a rate that is determined by the network's degree distribution and clustering properties This inhomogeneous evolution process, supported by direct measurements on several real networks, leads to systematic shifts in the overall subgraph spectrum and to an inevitable overrepresentation of some subgraphs and cycles

Fifteen Minutes of Fame: The Dynamics of Information Access on the Web

Abstract: While current studies on complex networks focus on systems that change relatively slowly in time, the structure of the most visited regions of the Web is altered at the timescale from hours to days. Here we investigate the dynamics of visitation of a major news portal, representing the prototype for such a rapidly evolving network. The nodes of the network can be classified into stable nodes, that form the time independent skeleton of the portal, and news documents. The visitation of the two node classes are markedly different, the skeleton acquiring visits at a constant rate, while a news document's visitation peaking after a few hours. We find that the visitation pattern of a news document decays as a power law, in contrast with the exponential prediction provided by simple models of site visitation. This is rooted in the inhomogeneous nature of the browsing pattern characterizing individual users: the time interval between consecutive visits by the same user to the site follows a power law distribution, in contrast with the exponential expected for Poisson processes. We show that the exponent characterizing the individual user's browsing patterns determines the power-law decay in a document's visitation. Finally, our results document the fleeting quality of news and events: while fifteen minutes of fame is still an exaggeration in the online media, we find that access to most news items significantly decays after 36 hours of posting.

Emergence of large-scale vorticity during diffusion in a random potential under an alternating bias.

Abstract: Conventional wisdom indicates that the presence of an alternating driving force will not change the long-term behavior of a Brownian particle moving in a random potential. Although this is true in one dimension, here we offer direct evidence that the inevitable local symmetry breaking present in a two-dimensional random potential leads to the emergence of a local ratchet effect that generates large-scale vorticity patterns consisting of steady-state net diffusive currents. For small fields the spatial correlation function of the current follows a logarithmic distance dependence, while for large external fields both the vorticity and the correlations gradually disappear. We uncover the scaling laws characterizing this unique pattern formation process, and discuss their potential relevance to real systems.

Topological units of environmental signal processing in the transcriptional-regulatory network of Escherichia coli

Abstract: Recent evidence indicates that potential interactions within metabolic, protein-protein interaction, and transcriptional regulatory networks are used differentially according to the environmental conditions in which a cell exists. However, the topological units underlying such differential utilization are not understood. Here we use the transcriptional regulatory network of Escherichia coli to identify such units, called origons, representing regulatory subnetworks that originate at a distinct class of sensor transcription factors. Using microarray data, we find that specific environmental signals affect mRNA expression levels significantly only within the origons responsible for their detection and processing. We also show that small regulatory interaction patterns, called subgraphs and motifs, occupy distinct positions in and between origons, offering insights into their dynamical role in information processing. The identified features are likely to represent a general framework for environmental signal processing in prokaryotes.

The architecture of complexity: the structure and the dynamics of networks, from the web to the cell

Abstract: Networks with complex topology describe systems as diverse as the cell, the World Wide Web or the society. The emergence of most networks is driven by self-organizing processes that are governed by simple but generic laws. The analysis of the cellular network of various organisms shows that cells and complex man-made networks, such as the Internet or the world wide web, and many social and collaboration networks share the same large-scale topology. I will show that the scale-free topology of these complex webs have important consequences on their robustness against failures and attacks, with implications on drug design, the Internet's ability to survive attacks and failures, and the ability of ideas and innovations to spread on the network.