30 research outputs found
A statistical mechanics description of environmental variability in metabolic networks
Many of the chemical reactions that take place within a living cell are irreversible. Due to evolutionary pressures, the number of allowable reactions within these systems are highly constrained and thus the resulting metabolic networks display considerable asymmetry. In this paper, we explore possible evolutionary factors pertaining to the reduced symmetry observed in these networks, and demonstrate the important role environmental variability plays in shaping their structural organization. Interpreting the returnability index as an equilibrium constant for a reaction network in equilibrium with a hypothetical reference system, enables us to quantify the extent to which a metabolic network is in disequilibrium. Further, by introducing a new directed centrality measure via an extension of the subgraph centrality metric to directed networks, we are able to characterise individual metabolites by their participation within metabolic pathways. To demonstrate these ideas, we study 116 metabolic networks of bacteria. In particular, we find that the equilibrium constant for the metabolic networks decreases significantly in-line with variability in bacterial habitats, supporting the view that environmental variability promotes disequilibrium within these biochemical reaction system
Phase transitions in contagion processes mediated by recurrent mobility patterns
Human mobility and activity patterns mediate contagion on many levels,
including the spatial spread of infectious diseases, diffusion of rumors, and
emergence of consensus. These patterns however are often dominated by specific
locations and recurrent flows and poorly modeled by the random diffusive
dynamics generally used to study them. Here we develop a theoretical framework
to analyze contagion within a network of locations where individuals recall
their geographic origins. We find a phase transition between a regime in which
the contagion affects a large fraction of the system and one in which only a
small fraction is affected. This transition cannot be uncovered by continuous
deterministic models due to the stochastic features of the contagion process
and defines an invasion threshold that depends on mobility parameters,
providing guidance for controlling contagion spread by constraining mobility
processes. We recover the threshold behavior by analyzing diffusion processes
mediated by real human commuting data.Comment: 20 pages of Main Text including 4 figures, 7 pages of Supplementary
Information; Nature Physics (2011
Traffic optimization in transport networks based on local routing
Congestion in transport networks is a topic of theoretical interest and
practical importance. In this paper we study the flow of vehicles in urban
street networks. In particular, we use a cellular automata model to simulate
the motion of vehicles along streets, coupled with a congestion-aware routing
at street crossings. Such routing makes use of the knowledge of agents about
traffic in nearby roads and allows the vehicles to dynamically update the
routes towards their destinations. By implementing the model in real urban
street patterns of various cities, we show that it is possible to achieve a
global traffic optimization based on local agent decisions.Comment: 4 pages, 5 figure
A Metric of Influential Spreading during Contagion Dynamics through the Air Transportation Network
The spread of infectious diseases at the global scale is mediated by long-range human travel. Our ability to predict the impact of an outbreak on human health requires understanding the spatiotemporal signature of early-time spreading from a specific location. Here, we show that network topology, geography, traffic structure and individual mobility patterns are all essential for accurate predictions of disease spreading. Specifically, we study contagion dynamics through the air transportation network by means of a stochastic agent-tracking model that accounts for the spatial distribution of airports, detailed air traffic and the correlated nature of mobility patterns and waiting-time distributions of individual agents. From the simulation results and the empirical air-travel data, we formulate a metric of influential spreading––the geographic spreading centrality––which accounts for spatial organization and the hierarchical structure of the network traffic, and provides an accurate measure of the early-time spreading power of individual nodes
Chimera-like states in modular neural networks
Chimera states, namely the coexistence of coherent and incoherent behavior, were previously analyzed in complex networks. However, they have not been extensively studied in modular networks. Here, we consider a neural network inspired by the connectome of the C. elegans soil worm, organized into six interconnected communities, where neurons obey chaotic bursting dynamics. Neurons are assumed to be connected with electrical synapses within their communities and with chemical synapses across them. As our numerical simulations reveal, the coaction of these two types of coupling can shape the dynamics in such a way that chimera-like states can happen. They consist of a fraction of synchronized neurons which belong to the larger communities, and a fraction of desynchronized neurons which are part of smaller communities. In addition to the Kuramoto order parameter ?, we also employ other measures of coherence, such as the chimera-like ? and metastability ? indices, which quantify the degree of synchronization among communities and along time, respectively. We perform the same analysis for networks that share common features with the C. elegans neural network. Similar results suggest that under certain assumptions, chimera-like states are prominent phenomena in modular networks, and might provide insight for the behavior of more complex modular networks
Development Trends of White Matter Connectivity in the First Years of Life
The human brain is organized into a collection of interacting networks with specialized functions to support various cognitive functions. Recent research has reached a consensus that the brain manifests small-world topology, which implicates both global and local efficiency at minimal wiring costs, and also modular organization, which indicates functional segregation and specialization. However, the important questions of how and when the small-world topology and modular organization come into existence remain largely unanswered. Taking a graph theoretic approach, we attempt to shed light on this matter by an in vivo study, using diffusion tensor imaging based fiber tractography, on 39 healthy pediatric subjects with longitudinal data collected at average ages of 2 weeks, 1 year, and 2 years. Our results indicate that the small-world architecture exists at birth with efficiency that increases in later stages of development. In addition, we found that the networks are broad scale in nature, signifying the existence of pivotal connection hubs and resilience of the brain network to random and targeted attacks. We also observed, with development, that the brain network seems to evolve progressively from a local, predominantly proximity based, connectivity pattern to a more distributed, predominantly functional based, connectivity pattern. These observations suggest that the brain in the early years of life has relatively efficient systems that may solve similar information processing problems, but in divergent ways
The stellar occultation by (319) Leona on 2023 September 13 in preparation for the occultation of Betelgeuse
peer reviewedOn 2023 December 12, the star α Orionis will be occulted by asteroid (319) Leona. This represents an extraordinary and unique opportunity to analyse the brightness distribution of Betelgeuse's photosphere with extreme angular resolution by studying light curves from different points on Earth and at different wavelengths. Here we present observations of another occultation by asteroid Leona, on 2023 September 13, whose goal was to determine Leona's projected shape and size in preparation for the December 12th event and its interpretation. The occultation campaign was highly successful with 25 positive detections from 17 different sites and a near miss. The effective diameter in projected area derived from the positive detections was 66 ± 2 km using an elliptical fit to the instantaneous limb. The body is highly elongated, with dimensions of 79.6 ± 2.2 km × 54.8 ± 1.3 km in its long and short axis, respectively, at occultation time. This result, in combination with dense time series photometry of Leona that we recently obtained, together with archival sparse photometry, allowed us to predict the angular size of the asteroid for the Betelgeuse event and to simulate the expected brightness change. Also, an accurate position coming from the occultation is provided, to improve the orbit of Leona
Flux-dependent graphs for metabolic networks
Cells adapt their metabolic fluxes in response to changes in the environment.
We present a framework for the systematic construction of flux-based graphs
derived from organism-wide metabolic networks. Our graphs encode the
directionality of metabolic fluxes via edges that represent the flow of
metabolites from source to target reactions. The methodology can be applied in
the absence of a specific biological context by modelling fluxes
probabilistically, or can be tailored to different environmental conditions by
incorporating flux distributions computed through constraint-based approaches
such as Flux Balance Analysis. We illustrate our approach on the central carbon
metabolism of Escherichia coli and on a metabolic model of human hepatocytes.
The flux-dependent graphs under various environmental conditions and genetic
perturbations exhibit systemic changes in their topological and community
structure, which capture the re-routing of metabolic fluxes and the varying
importance of specific reactions and pathways. By integrating constraint-based
models and tools from network science, our framework allows the study of
context-specific metabolic responses at a system level beyond standard pathway
descriptions