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Articles 1 - 26 of 26
Full-Text Articles in Physics
Human Disease Classification In The Postgenomic Era: A Complex Systems Approach To Human Pathobiology, Joseph Loscalzo, Isaac Kohane, Albert-László Barabási
Human Disease Classification In The Postgenomic Era: A Complex Systems Approach To Human Pathobiology, Joseph Loscalzo, Isaac Kohane, Albert-László Barabási
Albert-László Barabási
Contemporary classification of human disease derives from observational correlation between pathological analysis and clinical syndromes. Characterizing disease in this way established a nosology that has served clinicians well to the current time, and depends on observational skills and simple laboratory tools to define the syndromic phenotype. Yet, this time-honored diagnostic strategy has significant shortcomings that reflect both a lack of sensitivity in identifying preclinical disease, and a lack of specificity in defining disease unequivocally. In this paper, we focus on the latter limitation, viewing it as a reflection both of the different clinical presentations of many diseases (variable phenotypic expression), …
Emerging Behavior In Electronic Bidding, I. Yang, H. Jeong, B. Kahng, A.-L. Barabási
Emerging Behavior In Electronic Bidding, I. Yang, H. Jeong, B. Kahng, A.-L. Barabási
Albert-László Barabási
We characterize the statistical properties of a large number of agents on two major online auction sites. The measurements indicate that the total number of bids placed in a single category and the number of distinct auctions frequented by a given agent follow power-law distributions, implying that a few agents are responsible for a significant fraction of the total bidding activity on the online market. We find that these agents exert an unproportional influence on the final price of the auctioned items. This domination of online auctions by an unusually active minority may be a generic feature of all online …
Spectra Of "Real-World" Graphs: Beyond The Semicircle Law, Illés J. Farkas, Imre Derényi, Albert-László Barabási, Tamás Vicsek
Spectra Of "Real-World" Graphs: Beyond The Semicircle Law, Illés J. Farkas, Imre Derényi, Albert-László Barabási, Tamás Vicsek
Albert-László Barabási
Many natural and social systems develop complex networks that are usually modeled as random graphs. The eigenvalue spectrum of these graphs provides information about their structural properties. While the semicircle law is known to describe the spectral densities of uncorrelated random graphs, much less is known about the spectra of real-world graphs, describing such complex systems as the Internet, metabolic pathways, networks of power stations, scientific collaborations, or movie actors, which are inherently correlated and usually very sparse. An important limitation in addressing the spectra of these systems is that the numerical determination of the spectra for systems with more …
Dynamics Of Complex Systems: Scaling Laws For The Period Of Boolean Networks, Réka Albert, Albert-László Barabási
Dynamics Of Complex Systems: Scaling Laws For The Period Of Boolean Networks, Réka Albert, Albert-László Barabási
Albert-László Barabási
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 roadmap for understanding the dynamics of large interacting systems in general.
Separating The Internal And External Dynamics Of Complex Systems, M. Argollo De Menezes, A.-L. Barabási
Separating The Internal And External Dynamics Of Complex Systems, M. Argollo De Menezes, A.-L. Barabási
Albert-László Barabási
The observable behavior of a complex system reflects the mechanisms governing the internal interactions between the system’s components and the effect of external perturbations. Here we show that by capturing the simultaneous activity of several of the system’s components we can separate the internal dynamics from the external fluctuations. The method allows us to systematically determine the origin of fluctuations in various real systems, finding that while the Internet and the computer chip have robust internal dynamics, highway and Web traffic are driven by external demand. As multichannel measurements are becoming the norm in most fields, the method could help …
Dynamics Of Information Access On The Web, Z. Dezsö, E. Almaas, A. Lukács, B. Rácz, I. Szakadát, A.-L. Barabási
Dynamics Of Information Access On The Web, Z. Dezsö, E. Almaas, A. Lukács, B. Rácz, I. Szakadát, A.-L. Barabási
Albert-László Barabási
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 time scale 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, which form the timeindependent skeleton of the portal, and news documents. The visitations of the two node classes are markedly different, the skeleton acquiring visits at a constant rate, while a news document’s …
Percolation In Directed Scale-Free Networks, N. Schwartz, R. Cohen, D. Ben-Avraham, A.-L. Barabási, S. Havlin
Percolation In Directed Scale-Free Networks, N. Schwartz, R. Cohen, D. Ben-Avraham, A.-L. Barabási, S. Havlin
Albert-László Barabási
Many complex networks in nature have directed links, a property that affects the network’s navigability and large-scale topology. Here we study the percolation properties of such directed scale-free networks with correlated in and out degree distributions. We derive a phase diagram that indicates the existence of three regimes, determined by the values of the degree exponents. In the first regime we regain the known directed percolation mean field exponents. In contrast, the second and third regimes are characterized by anomalous exponents, which we calculate analytically. In the third regime the network is resilient to random dilution, i.e., the percolation threshold …
Topology Of Evolving Networks: Local Events And Universality, Réka Albert, Albert-László Barabási
Topology Of Evolving Networks: Local Events And Universality, Réka Albert, Albert-László Barabási
Albert-László Barabási
Networks grow and evolve by local events, such as the addition of new nodes and links, or rewiring of links from one node to another. We show that depending on the frequency of these processes two topologically different networks can emerge, the connectivity distribution following either a generalized power law or an exponential. We propose a continuum theory that predicts these two regimes as well as the scaling function and the exponents, in good agreement with numerical results. Finally, we use the obtained predictions to fit the connectivity distribution of the network describing the professional links between movie actors.
Spectra Of "Real-World" Graphs: Beyond The Semicircle Law, Illés J. Farkas, Imre Derényi, Albert-László Barabási, Tamás Vicsek
Spectra Of "Real-World" Graphs: Beyond The Semicircle Law, Illés J. Farkas, Imre Derényi, Albert-László Barabási, Tamás Vicsek
Albert-László Barabási
Many natural and social systems develop complex networks that are usually modeled as random graphs. The eigenvalue spectrum of these graphs provides information about their structural properties. While the semicircle law is known to describe the spectral densities of uncorrelated random graphs, much less is known about the spectra of real-world graphs, describing such complex systems as the Internet, metabolic pathways, networks of power stations, scientific collaborations, or movie actors, which are inherently correlated and usually very sparse. An important limitation in addressing the spectra of these systems is that the numerical determination of the spectra for systems with more …
Halting Viruses In Scale-Free Networks, Zoltán Dezső, Albert-László Barabási
Halting Viruses In Scale-Free Networks, Zoltán Dezső, Albert-László Barabási
Albert-László Barabási
The vanishing epidemic threshold for viruses spreading on scale-free networks indicate that traditional methods, aiming to decrease a virus' spreading rate cannot succeed in eradicating an epidemic. We demonstrate that policies that discriminate between the nodes, curing mostly the highly connected nodes, can restore a finite epidemic threshold and potentially eradicate a virus. We find that the more biased a policy is towards the hubs, the more chance it has to bring the epidemic threshold above the virus’ spreading rate. Furthermore, such biased policies are more cost effective, requiring less cures to eradicate the virus.
Reverse Engineering Of Linking Preferences From Network Restructuring, Gergely Palla, Illés Farkas, Imre Derényi, Albert-László Barabási, Tamás Vicsek
Reverse Engineering Of Linking Preferences From Network Restructuring, Gergely Palla, Illés Farkas, Imre Derényi, Albert-László Barabási, Tamás Vicsek
Albert-László Barabási
We provide a method to deduce the preferences governing the restructuring dynamics of a network from the observed rewiring of the edges. Our approach is applicable for systems in which the preferences can be formulated in terms of a single-vertex energy function with f(k) being the contribution of a node of degree k to the total energy, and the dynamics obeys the detailed balance. The method is first tested by Monte Carlo simulations of restructuring graphs with known energies; then it is used to study variations of real network systems ranging from the coauthorship network of scientific publications to the …
Analysis Of A Large-Scale Weighted Network Of One-To-One Human Communication, Jukka-Pekka Onnela, Jari Saramäki, Jörkki Hyvönen, Gábor Szabó, M. Argollo De Menezes, Kimmo Kaski, Albert-László Barabási, János Kertész
Analysis Of A Large-Scale Weighted Network Of One-To-One Human Communication, Jukka-Pekka Onnela, Jari Saramäki, Jörkki Hyvönen, Gábor Szabó, M. Argollo De Menezes, Kimmo Kaski, Albert-László Barabási, János Kertész
Albert-László Barabási
We construct a connected network of 3.9 million nodes from mobile phone call records, which can be regarded as a proxy for the underlying human communication network at the societal level. We assign two weights on each edge to reflect the strength of social interaction, which are the aggregate call duration and the cumulative number of calls placed between the individuals over a period of 18 weeks. We present a detailed analysis of this weighted network by examining its degree, strength, and weight distributions, as well as its topological assortativity and weighted assortativity, clustering and weighted clustering, together with correlations …
Topology Of Evolving Networks: Local Events And Universality, Réka Albert, Albert-László Barabási
Topology Of Evolving Networks: Local Events And Universality, Réka Albert, Albert-László Barabási
Albert-László Barabási
Networks grow and evolve by local events, such as the addition of new nodes and links, or rewiring of links from one node to another. We show that depending on the frequency of these processes two topologically different networks can emerge, the connectivity distribution following either a generalized power law or an exponential. We propose a continuum theory that predicts these two regimes as well as the scaling function and the exponents, in good agreement with numerical results. Finally, we use the obtained predictions to fit the connectivity distribution of the network describing the professional links between movie actors.
Hierarchical Organization In Complex Networks, Erzsébet Ravasz, Albert-László Barabási
Hierarchical Organization In Complex Networks, Erzsébet Ravasz, Albert-László Barabási
Albert-László Barabási
Many real networks in nature and society share two generic properties: they are scale-free and they display a high degree of clustering. We show that these two features are the consequence of a hierarchical organization, implying that small groups of nodes organize in a hierarchical manner into increasingly large groups, while maintaining a scale-free topology. In hierarchical networks, the degree of clustering characterizing the different groups follows a strict scaling law, which can be used to identify the presence of a hierarchical organization in real networks. We find that several real networks, such as the Worldwideweb, actor network, the Internet …
Impact Of Non-Poissonian Activity Patterns On Spreading Processes, Alexei Vazquez, Balázs Rácz, András Lukács, Albert-László Barabási
Impact Of Non-Poissonian Activity Patterns On Spreading Processes, Alexei Vazquez, Balázs Rácz, András Lukács, Albert-László Barabási
Albert-László Barabási
Halting a computer or biological virus outbreak requires a detailed understanding of the timing of the interactions between susceptible and infected individuals. While current spreading models assume that users interact uniformly in time, following a Poisson process, a series of recent measurements indicates that the intercontact time distribution is heavy tailed, corresponding to a temporally inhomogeneous bursty contact process. Here we show that the non-Poisson nature of the contact dynamics results in prevalence decay times significantly larger than predicted by the standard Poisson process based models. Our predictions are in agreement with the detailed time resolved prevalence data of computer …
Inhomogeneous Evolution Of Subgraphs And Cycles In Complex Networks, Alexei Vázquez, J. G. Oliveira, Albert-László Barabási
Inhomogeneous Evolution Of Subgraphs And Cycles In Complex Networks, Alexei Vázquez, J. G. Oliveira, Albert-László Barabási
Albert-László Barabási
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.
Modeling Bursts And Heavy Tails In Human Dynamics, Alexei Vázquez, João Gama Oliveira, Zoltán Dezsö, Kwang-Il Goh, Imre Kondor, Albert-László Barabási
Modeling Bursts And Heavy Tails In Human Dynamics, Alexei Vázquez, João Gama Oliveira, Zoltán Dezsö, Kwang-Il Goh, Imre Kondor, Albert-László Barabási
Albert-László Barabási
No abstract provided.
The Architecture Of Complexity, Albert-László Barabási
The Architecture Of Complexity, Albert-László Barabási
Albert-László Barabási
No abstract provided.
Human Disease Classification In The Postgenomic Era: A Complex Systems Approach To Human Pathobiology, Joseph Loscalzo, Isaac Kohane, Albert-László Barabási
Human Disease Classification In The Postgenomic Era: A Complex Systems Approach To Human Pathobiology, Joseph Loscalzo, Isaac Kohane, Albert-László Barabási
Albert-László Barabási
Contemporary classification of human disease derives from observational correlation between pathological analysis and clinical syndromes. Characterizing disease in this way established a nosology that has served clinicians well to the current time, and depends on observational skills and simple laboratory tools to define the syndromic phenotype. Yet, this time-honored diagnostic strategy has significant shortcomings that reflect both a lack of sensitivity in identifying preclinical disease, and a lack of specificity in defining disease unequivocally. In this paper, we focus on the latter limitation, viewing it as a reflection both of the different clinical presentations of many diseases (variable phenotypic expression), …
The Impact Of Cellular Networks On Disease Comorbidity, Juyong Park, Deok-Sun Lee, Nicholas A. Christakis, Albert-László Barabási
The Impact Of Cellular Networks On Disease Comorbidity, Juyong Park, Deok-Sun Lee, Nicholas A. Christakis, Albert-László Barabási
Albert-László Barabási
The impact of disease-causing defects is often not limited to the products of a mutated gene but, thanks to interactions between the molecular components, may also affect other cellular functions, resulting in potential comorbidity effects. By combining information on cellular interactions, disease–gene associations, and population-level disease patterns extracted from Medicare data, we find statistically significant correlations between the underlying structure of cellular networks and disease comorbidity patterns in the human population. Our results indicate that such a combination of population-level data and cellular network information could help build novel hypotheses about disease mechanisms.
Predicting Synthetic Rescues In Metabolic Networks, Adilson E. Motter, Natali Gulbahce, Eivind Almaas, Albert-László Barabási
Predicting Synthetic Rescues In Metabolic Networks, Adilson E. Motter, Natali Gulbahce, Eivind Almaas, Albert-László Barabási
Albert-László Barabási
An important goal of medical research is to develop methods to recover the loss of cellular function due to mutations and other defects. Many approaches based on gene therapy aim to repair the defective gene or to insert genes with compensatory function. Here, we propose an alternative, network-based strategy that aims to restore biological function by forcing the cell to either bypass the functions affected by the defective gene, or to compensate for the lost function. Focusing on the metabolism of single-cell organisms, we computationally study mutants that lack an essential enzyme, and thus are unable to grow or have …
Stable Evolutionary Signal In A Yeast Protein Interaction Network, Stefan Wuchty, Albert-László Barabási, Michael T. Ferdig
Stable Evolutionary Signal In A Yeast Protein Interaction Network, Stefan Wuchty, Albert-László Barabási, Michael T. Ferdig
Albert-László Barabási
Background: The recently emerged protein interaction network paradigm can provide novel and important insights into the innerworkings of a cell. Yet, the heavy burden of both false positive and false negative protein-protein interaction data casts doubt on the broader usefulness of these interaction sets. Approaches focusing on one-protein-at-a-time have been powerfully employed to demonstrate the high degree of conservation of proteins participating in numerous interactions; here, we expand his 'node' focused paradigm to investigate the relative persistence of 'link' based evolutionary signals in a protein interaction network of S. cerevisiae and point out the value of this relatively untapped source …
The Activity Reaction Core And Plasticity Of Metabolic Networks, Eivind Almaas, Zoltán N. Oltvai, Albert-László Barabási
The Activity Reaction Core And Plasticity Of Metabolic Networks, Eivind Almaas, Zoltán N. Oltvai, Albert-László Barabási
Albert-László Barabási
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 fluxbalance 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 …
Aggregation Of Topological Motifs In The Escherichia Coli Transcriptional Regulatory Networks, Radu Dobrin, Qasim K. Beg, Albert-László Barabási, Zoltán N. Oltvai
Aggregation Of Topological Motifs In The Escherichia Coli Transcriptional Regulatory Networks, Radu Dobrin, Qasim K. Beg, Albert-László Barabási, Zoltán N. Oltvai
Albert-László Barabási
Background: Transcriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes and operons regulated by them.To better understand the system-level function of such networks simplification of their architecture was previously achieved by identifying the motifs present in the network, which are small, overrepresented, topologically distinct regulatory interaction patterns (subgraphs). However, the interaction of such motifs with each other, and their form of integration into the full network has not been previously examined. Results: By studying the transcriptional regulatory network of the bacterium, Escherichia coli, we demonstrate that …
Impact Of Limited Solvent Capacity On Metabolic Rate, Enzyme Activities, And Metabolite Concentrations Of S. Cerevisiae Glycolysis, Alexei Vazquez, Marcio A. De Menezes, Albert-László Barabási, Zoltan N. Oltvai
Impact Of Limited Solvent Capacity On Metabolic Rate, Enzyme Activities, And Metabolite Concentrations Of S. Cerevisiae Glycolysis, Alexei Vazquez, Marcio A. De Menezes, Albert-László Barabási, Zoltan N. Oltvai
Albert-László Barabási
The cell’s cytoplasm is crowded by its various molecular components, resulting in a limited solvent capacity for the allocation of new proteins, thus constraining various cellular processes such as metabolism. Here we study the impact of the limited solvent capacity constraint on the metabolic rate, enzyme activities, and metabolite concentrations using a computational model of Saccharomyces cerevisiae glycolysis as a case study. We show that given the limited solvent capacity constraint, the optimal enzyme activities and the metabolite concentrations necessary to achieve a maximum rate of glycolysis are in agreement with their experimentally measured values. Furthermore, the predicted maximum glycolytic …
A Dynamic Network Approach For The Study Of Human Phenotypes -- Removed From View At The Discretion Of Northeastern University Libraries (2/3/11), César A. Hidalgo, Nicholas Blumm, Albert-László Barabási, Nicholas A. Christakis
A Dynamic Network Approach For The Study Of Human Phenotypes -- Removed From View At The Discretion Of Northeastern University Libraries (2/3/11), César A. Hidalgo, Nicholas Blumm, Albert-László Barabási, Nicholas A. Christakis
Albert-László Barabási
The use of networks to integrate different genetic, proteomic, and metabolic datasets has been proposed as a viable path toward elucidating the origins of specific diseases. Here we introduce a new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN). We present evidence that the structure of the PDN is relevant to the understanding of illness progression by showing that (1) patients develop diseases close in the network to those they already have; (2) the progression of disease along the links of the network is different for patients …