Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks.

Science.gov (United States)

Oh, S June; Joung, Je-Gun; Chang, Jeong-Ho; Zhang, Byoung-Tak

2006-06-06

To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway structures using meta-level information rather than sequence

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks

Directory of Open Access Journals (Sweden)

Chang Jeong-Ho

2006-06-01

Full Text Available Abstract Background To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. Results To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. Conclusion By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway

Deletion of the Mitochondrial Chaperone TRAP-1 Uncovers Global Reprogramming of Metabolic Networks

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Sofia Lisanti

2014-08-01

Full Text Available Reprogramming of metabolic pathways contributes to human disease, especially cancer, but the regulators of this process are unknown. Here, we have generated a mouse knockout for the mitochondrial chaperone TRAP-1, a regulator of bioenergetics in tumors. TRAP-1−/− mice are viable and showed reduced incidence of age-associated pathologies, including obesity, inflammatory tissue degeneration, dysplasia, and spontaneous tumor formation. This was accompanied by global upregulation of oxidative phosphorylation and glycolysis transcriptomes, causing deregulated mitochondrial respiration, oxidative stress, impaired cell proliferation, and a switch to glycolytic metabolism in vivo. These data identify TRAP-1 as a central regulator of mitochondrial bioenergetics, and this pathway could contribute to metabolic rewiring in tumors.

Connexin 43-Mediated Astroglial Metabolic Networks Contribute to the Regulation of the Sleep-Wake Cycle.

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Clasadonte, Jerome; Scemes, Eliana; Wang, Zhongya; Boison, Detlev; Haydon, Philip G

2017-09-13

Astrocytes produce and supply metabolic substrates to neurons through gap junction-mediated astroglial networks. However, the role of astroglial metabolic networks in behavior is unclear. Here, we demonstrate that perturbation of astroglial networks impairs the sleep-wake cycle. Using a conditional Cre-Lox system in mice, we show that knockout of the gap junction subunit connexin 43 in astrocytes throughout the brain causes excessive sleepiness and fragmented wakefulness during the nocturnal active phase. This astrocyte-specific genetic manipulation silenced the wake-promoting orexin neurons located in the lateral hypothalamic area (LHA) by impairing glucose and lactate trafficking through astrocytic networks. This global wakefulness instability was mimicked with viral delivery of Cre recombinase to astrocytes in the LHA and rescued by in vivo injections of lactate. Our findings propose a novel regulatory mechanism critical for maintaining normal daily cycle of wakefulness and involving astrocyte-neuron metabolic interactions. Copyright © 2017 Elsevier Inc. All rights reserved.

Noise effect in metabolic networks

International Nuclear Information System (INIS)

Zheng-Yan, Li; Zheng-Wei, Xie; Tong, Chen; Qi, Ouyang

2009-01-01

Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states. (cross-disciplinary physics and related areas of science and technology)

Network configuration of global R&D networks

DEFF Research Database (Denmark)

Hansen, Zaza Nadja Lee; Srai, Jagjit Singh

2011-01-01

, network configuration of global R&D has tended to focus on strategic elements with limited attention given operational effectiveness, or to interfaces with downstream manufacturing operations. Within OM literature, the drivers of configuration of global networks within, engineering, production, supply...... to R&D networks emerged, e.g. product features were more prominent in R&D networks. Furthermore, the study has shown extensive interaction with other operations, including many downstream manufacturing operations. By extending the OM configuration concepts to the configuration of R&D networks......Companies are increasingly globalising their R&D activities, both within the firms and with external partners, with consequent implications for their interaction with manufacturing operations. Previous research in R&D networks has focused on coordination, governance and support elements. However...

Quantitative Tools for Dissection of Hydrogen-Producing Metabolic Networks-Final Report

Energy Technology Data Exchange (ETDEWEB)

Rabinowitz, Joshua D.; Dismukes, G.Charles.; Rabitz, Herschel A.; Amador-Noguez, Daniel

2012-10-19

During this project we have pioneered the development of integrated experimental-computational technologies for the quantitative dissection of metabolism in hydrogen and biofuel producing microorganisms (i.e. C. acetobutylicum and various cyanobacteria species). The application of these new methodologies resulted in many significant advances in the understanding of the metabolic networks and metabolism of these organisms, and has provided new strategies to enhance their hydrogen or biofuel producing capabilities. As an example, using mass spectrometry, isotope tracers, and quantitative flux-modeling we mapped the metabolic network structure in C. acetobutylicum. This resulted in a comprehensive and quantitative understanding of central carbon metabolism that could not have been obtained using genomic data alone. We discovered that biofuel production in this bacterium, which only occurs during stationary phase, requires a global remodeling of central metabolism (involving large changes in metabolite concentrations and fluxes) that has the effect of redirecting resources (carbon and reducing power) from biomass production into solvent production. This new holistic, quantitative understanding of metabolism is now being used as the basis for metabolic engineering strategies to improve solvent production in this bacterium. In another example, making use of newly developed technologies for monitoring hydrogen and NAD(P)H levels in vivo, we dissected the metabolic pathways for photobiological hydrogen production by cyanobacteria Cyanothece sp. This investigation led to the identification of multiple targets for improving hydrogen production. Importantly, the quantitative tools and approaches that we have developed are broadly applicable and we are now using them to investigate other important biofuel producers, such as cellulolytic bacteria.

Control of fluxes in metabolic networks

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Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

2016-01-01

Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. PMID:27197218

Prioritizing Candidate Disease Metabolites Based on Global Functional Relationships between Metabolites in the Context of Metabolic Pathways

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Yang, Haixiu; Xu, Yanjun; Han, Junwei; Li, Jing; Su, Fei; Zhang, Yunpeng; Zhang, Chunlong; Li, Dongguo; Li, Xia

2014-01-01

Identification of key metabolites for complex diseases is a challenging task in today's medicine and biology. A special disease is usually caused by the alteration of a series of functional related metabolites having a global influence on the metabolic network. Moreover, the metabolites in the same metabolic pathway are often associated with the same or similar disease. Based on these functional relationships between metabolites in the context of metabolic pathways, we here presented a pathway-based random walk method called PROFANCY for prioritization of candidate disease metabolites. Our strategy not only takes advantage of the global functional relationships between metabolites but also sufficiently exploits the functionally modular nature of metabolic networks. Our approach proved successful in prioritizing known metabolites for 71 diseases with an AUC value of 0.895. We also assessed the performance of PROFANCY on 16 disease classes and found that 4 classes achieved an AUC value over 0.95. To investigate the robustness of the PROFANCY, we repeated all the analyses in two metabolic networks and obtained similar results. Then we applied our approach to Alzheimer's disease (AD) and found that a top ranked candidate was potentially related to AD but had not been reported previously. Furthermore, our method was applicable to prioritize the metabolites from metabolomic profiles of prostate cancer. The PROFANCY could identify prostate cancer related-metabolites that are supported by literatures but not considered to be significantly differential by traditional differential analysis. We also developed a freely accessible web-based and R-based tool at http://bioinfo.hrbmu.edu.cn/PROFANCY. PMID:25153931

Does habitat variability really promote metabolic network modularity?

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Takemoto, Kazuhiro

2013-01-01

The hypothesis that variability in natural habitats promotes modular organization is widely accepted for cellular networks. However, results of some data analyses and theoretical studies have begun to cast doubt on the impact of habitat variability on modularity in metabolic networks. Therefore, we re-evaluated this hypothesis using statistical data analysis and current metabolic information. We were unable to conclude that an increase in modularity was the result of habitat variability. Although horizontal gene transfer was also considered because it may contribute for survival in a variety of environments, closely related to habitat variability, and is known to be positively correlated with network modularity, such a positive correlation was not concluded in the latest version of metabolic networks. Furthermore, we demonstrated that the previously observed increase in network modularity due to habitat variability and horizontal gene transfer was probably due to a lack of available data on metabolic reactions. Instead, we determined that modularity in metabolic networks is dependent on species growth conditions. These results may not entirely discount the impact of habitat variability and horizontal gene transfer. Rather, they highlight the need for a more suitable definition of habitat variability and a more careful examination of relationships of the network modularity with horizontal gene transfer, habitats, and environments.

Pathway discovery in metabolic networks by subgraph extraction.

Science.gov (United States)

Faust, Karoline; Dupont, Pierre; Callut, Jérôme; van Helden, Jacques

2010-05-01

Subgraph extraction is a powerful technique to predict pathways from biological networks and a set of query items (e.g. genes, proteins, compounds, etc.). It can be applied to a variety of different data types, such as gene expression, protein levels, operons or phylogenetic profiles. In this article, we investigate different approaches to extract relevant pathways from metabolic networks. Although these approaches have been adapted to metabolic networks, they are generic enough to be adjusted to other biological networks as well. We comparatively evaluated seven sub-network extraction approaches on 71 known metabolic pathways from Saccharomyces cerevisiae and a metabolic network obtained from MetaCyc. The best performing approach is a novel hybrid strategy, which combines a random walk-based reduction of the graph with a shortest paths-based algorithm, and which recovers the reference pathways with an accuracy of approximately 77%. Most of the presented algorithms are available as part of the network analysis tool set (NeAT). The kWalks method is released under the GPL3 license.

From genomes to in silico cells via metabolic networks

DEFF Research Database (Denmark)

Borodina, Irina; Nielsen, Jens

2005-01-01

Genome-scale metabolic models are the focal point of systems biology as they allow the collection of various data types in a form suitable for mathematical analysis. High-quality metabolic networks and metabolic networks with incorporated regulation have been successfully used for the analysis...... of phenotypes from phenotypic arrays and in gene-deletion studies. They have also been used for gene expression analysis guided by metabolic network structure, leading to the identification of commonly regulated genes. Thus, genome-scale metabolic modeling currently stands out as one of the most promising...

Slave nodes and the controllability of metabolic networks

International Nuclear Information System (INIS)

Kim, Dong-Hee; Motter, Adilson E

2009-01-01

Recent work on synthetic rescues has shown that the targeted deletion of specific metabolic genes can often be used to rescue otherwise non-viable mutants. This raises a fundamental biophysical question: to what extent can the whole-cell behavior of a large metabolic network be controlled by constraining the flux of one or more reactions in the network? This touches upon the issue of the number of degrees of freedom contained by one such network. Using the metabolic network of Escherichia coli as a model system, here we address this question theoretically by exploring not only reaction deletions, but also a continuum of all possible reaction expression levels. We show that the behavior of the metabolic network can be largely manipulated by the pinned expression of a single reaction. In particular, a relevant fraction of the metabolic reactions exhibits canalizing interactions, in that the specification of one reaction flux determines cellular growth as well as the fluxes of most other reactions in optimal steady states. The activity of individual reactions can thus be used as surrogates to monitor and possibly control cellular growth and other whole-cell behaviors. In addition to its implications for the study of control processes, our methodology provides a new approach to study how the integrated dynamics of the entire metabolic network emerges from the coordinated behavior of its component parts.

Identification of metabolic system parameters using global optimization methods

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Gatzke Edward P

2006-01-01

Full Text Available Abstract Background The problem of estimating the parameters of dynamic models of complex biological systems from time series data is becoming increasingly important. Methods and results Particular consideration is given to metabolic systems that are formulated as Generalized Mass Action (GMA models. The estimation problem is posed as a global optimization task, for which novel techniques can be applied to determine the best set of parameter values given the measured responses of the biological system. The challenge is that this task is nonconvex. Nonetheless, deterministic optimization techniques can be used to find a global solution that best reconciles the model parameters and measurements. Specifically, the paper employs branch-and-bound principles to identify the best set of model parameters from observed time course data and illustrates this method with an existing model of the fermentation pathway in Saccharomyces cerevisiae. This is a relatively simple yet representative system with five dependent states and a total of 19 unknown parameters of which the values are to be determined. Conclusion The efficacy of the branch-and-reduce algorithm is illustrated by the S. cerevisiae example. The method described in this paper is likely to be widely applicable in the dynamic modeling of metabolic networks.

Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator

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Usaite, Renata; Jewett, Michael C; Oliveira, Ana Paula; Yates, John R; Olsson, Lisbeth; Nielsen, Jens

2009-01-01

Highly conserved among eukaryotic cells, the AMP-activated kinase (AMPK) is a central regulator of carbon metabolism. To map the complete network of interactions around AMPK in yeast (Snf1) and to evaluate the role of its regulatory subunit Snf4, we measured global mRNA, protein and metabolite levels in wild type, Δsnf1, Δsnf4, and Δsnf1Δsnf4 knockout strains. Using four newly developed computational tools, including novel DOGMA sub-network analysis, we showed the benefits of three-level ome-data integration to uncover the global Snf1 kinase role in yeast. We for the first time identified Snf1's global regulation on gene and protein expression levels, and showed that yeast Snf1 has a far more extensive function in controlling energy metabolism than reported earlier. Additionally, we identified complementary roles of Snf1 and Snf4. Similar to the function of AMPK in humans, our findings showed that Snf1 is a low-energy checkpoint and that yeast can be used more extensively as a model system for studying the molecular mechanisms underlying the global regulation of AMPK in mammals, failure of which leads to metabolic diseases. PMID:19888214

Global tree network for computing structures enabling global processing operations

Science.gov (United States)

Blumrich; Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

2010-01-19

A system and method for enabling high-speed, low-latency global tree network communications among processing nodes interconnected according to a tree network structure. The global tree network enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the tree via links to facilitate performance of low-latency global processing operations at nodes of the virtual tree and sub-tree structures. The global operations performed include one or more of: broadcast operations downstream from a root node to leaf nodes of a virtual tree, reduction operations upstream from leaf nodes to the root node in the virtual tree, and point-to-point message passing from any node to the root node. The global tree network is configurable to provide global barrier and interrupt functionality in asynchronous or synchronized manner, and, is physically and logically partitionable.

Sirtuins as regulators of the yeast metabolic network

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Markus eRalser

2012-03-01

Full Text Available There is growing evidence that the metabolic network is an integral regulator of cellularphysiology. Dynamic changes in metabolite concentrations, metabolic flux, or networktopology act as reporters of biological or environmental signals, and are required for the cellto trigger an appropriate biological reaction. Changes in the metabolic network are recognizedby specific sensory macromolecules and translated into a transcriptional or translationalresponse. The protein family of sirtuins, discovered more than 30 years ago as regulators ofsilent chromatin, seems to fulfill the role of a metabolic sensor during aging and conditions ofcaloric restriction. NAD+/NADH interconverting metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase and alcohol dehydrogenase, as well as enzymes involved inNAD(H, synthesis provide or deprive NAD+ in close proximity to Sir2. This influence sirtuinactivity, and facilitates a dynamic response of the metabolic network to changes inmetabolism with effects on physiology and aging. The molecular network downstream Sir2,however, is complex. In just two orders, Sir2’s metabolism-related interactions span half ofthe yeast proteome, and are connected with virtually every physiological process. Thus,although it is fundamental to analyze single molecular mechanisms, it is at the same timecrucial to consider this genome-scale complexity when correlating single molecular eventswith phenotypes such as aging, cell growth, or stress resistance.

Global Operations Networks in Motion

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Jørgensen, Claus; Wæhrens, Brian Vejrum

2009-01-01

This paper addresses the phenomenon of global operations networks and how they change over time. The paper is based on the cases of three Danish companies and their global operations networks. It finds a number of common patterns highlighting some organisational effects and managerial challenges...... the companies face regarding rapid changes in their networks configurations and capabilities. The paper details the variables determining these changes and suggests how the on-going interplay between the focal organisation, its network partners, and their various contextual conditions can be approached....

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

Science.gov (United States)

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-01-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

State Support: A Prerequisite for Global Health Network Effectiveness Comment on "Four Challenges that Global Health Networks Face".

Science.gov (United States)

Marten, Robert; Smith, Richard D

2017-07-24

Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks' success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks' effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research. © 2018 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Multi-equilibrium property of metabolic networks: SSI module

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Chen Luonan

2011-06-01

Full Text Available Abstract Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

Predicting metabolic pathways by sub-network extraction.

Science.gov (United States)

Faust, Karoline; van Helden, Jacques

2012-01-01

Various methods result in groups of functionally related genes obtained from genomes (operons, regulons, syntheny groups, and phylogenetic profiles), transcriptomes (co-expression groups) and proteomes (modules of interacting proteins). When such groups contain two or more enzyme-coding genes, graph analysis methods can be applied to extract a metabolic pathway that interconnects them. We describe here the way to use the Pathway extraction tool available on the NeAT Web server ( http://rsat.ulb.ac.be/neat/ ) to piece together the metabolic pathway from a group of associated, enzyme-coding genes. The tool identifies the reactions that can be catalyzed by the products of the query genes (seed reactions), and applies sub-graph extraction algorithms to extract from a metabolic network a sub-network that connects the seed reactions. This sub-network represents the predicted metabolic pathway. We describe here the pathway prediction process in a step-by-step way, give hints about the main parametric choices, and illustrate how this tool can be used to extract metabolic pathways from bacterial genomes, on the basis of two study cases: the isoleucine-valine operon in Escherichia coli and a predicted operon in Cupriavidus (Ralstonia) metallidurans.

Computer Networks and Globalization

Directory of Open Access Journals (Sweden)

J. Magliaro

2007-07-01

Full Text Available Communication and information computer networks connect the world in ways that make globalization more natural and inequity more subtle. As educators, we look at these phenomena holistically analyzing them from the realist’s view, thus exploring tensions, (in equity and (injustice, and from the idealist’s view, thus embracing connectivity, convergence and development of a collective consciousness. In an increasingly market- driven world we find examples of openness and human generosity that are based on networks, specifically the Internet. After addressing open movements in publishing, software industry and education, we describe the possibility of a dialectic equilibrium between globalization and indigenousness in view of ecologically designed future smart networks

State Support: A Prerequisite for Global Health Network Effectiveness; Comment on “Four Challenges that Global Health Networks Face”

Directory of Open Access Journals (Sweden)

Robert Marten

2018-03-01

Full Text Available Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks’ success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks’ effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research.

Horizontal and vertical growth of S. cerevisiae metabolic network.

KAUST Repository

Grassi, Luigi

2011-10-14

BACKGROUND: The growth and development of a biological organism is reflected by its metabolic network, the evolution of which relies on the essential gene duplication mechanism. There are two current views about the evolution of metabolic networks. The retrograde model hypothesizes that a pathway evolves by recruiting novel enzymes in a direction opposite to the metabolic flow. The patchwork model is instead based on the assumption that the evolution is based on the exploitation of broad-specificity enzymes capable of catalysing a variety of metabolic reactions. RESULTS: We analysed a well-studied unicellular eukaryotic organism, S. cerevisiae, and studied the effect of the removal of paralogous gene products on its metabolic network. Our results, obtained using different paralog and network definitions, show that, after an initial period when gene duplication was indeed instrumental in expanding the metabolic space, the latter reached an equilibrium and subsequent gene duplications were used as a source of more specialized enzymes rather than as a source of novel reactions. We also show that the switch between the two evolutionary strategies in S. cerevisiae can be dated to about 350 million years ago. CONCLUSIONS: Our data, obtained through a novel analysis methodology, strongly supports the hypothesis that the patchwork model better explains the more recent evolution of the S. cerevisiae metabolic network. Interestingly, the effects of a patchwork strategy acting before the Euascomycete-Hemiascomycete divergence are still detectable today.

Metabolite coupling in genome-scale metabolic networks

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Palsson Bernhard Ø

2006-03-01

Full Text Available Abstract Background Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜT, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S. Results Metabolite coupling in the studied networks was found to be dominated by a relatively small group of highly interacting pairs of metabolites. As would be expected, metabolites with high individual metabolite connectivity also tended to be those with the highest metabolite coupling, as the most connected metabolites couple more often. For metabolite pairs that are not highly coupled, we show that the number of reactions a pair of metabolites shares across a metabolic network closely approximates a line on a log-log scale. We also show that the preferential coupling of two metabolites with each other is spread across the spectrum of metabolites and is not unique to the most connected metabolites. We provide a measure for determining which metabolite pairs couple more often than would be expected based on their individual connectivity in the network and show that these metabolites often derive their principal biological functions from existing in pairs. Thus, analysis of metabolite coupling provides information beyond that which is found from studying the individual connectivity of individual

Global fluctuations of cerebral blood flow indicate a global brain network independent of systemic factors.

Science.gov (United States)

Zhao, Li; Alsop, David C; Detre, John A; Dai, Weiying

2017-01-01

Global synchronization across specialized brain networks is a common feature of network models and in-vivo electrical measurements. Although the imaging of specialized brain networks with blood oxygenation sensitive resting state functional magnetic resonance imaging (rsfMRI) has enabled detailed study of regional networks, the study of globally correlated fluctuations with rsfMRI is confounded by spurious contributions to the global signal from systemic physiologic factors and other noise sources. Here we use an alternative rsfMRI method, arterial spin labeled perfusion MRI, to characterize global correlations and their relationship to correlations and anti-correlations between regional networks. Global fluctuations that cannot be explained by systemic factors dominate the fluctuations in cerebral blood flow. Power spectra of these fluctuations are band limited to below 0.05 Hz, similar to prior measurements of regional network fluctuations in the brain. Removal of these global fluctuations prior to measurement of regional networks reduces all regional network fluctuation amplitudes to below the global fluctuation amplitude and changes the strength and sign of inter network correlations. Our findings support large amplitude, globally synchronized activity across networks that require a reassessment of regional network amplitude and correlation measures.

Preferential attachment in the evolution of metabolic networks

Directory of Open Access Journals (Sweden)

Elofsson Arne

2005-11-01

Full Text Available Abstract Background Many biological networks show some characteristics of scale-free networks. Scale-free networks can evolve through preferential attachment where new nodes are preferentially attached to well connected nodes. In networks which have evolved through preferential attachment older nodes should have a higher average connectivity than younger nodes. Here we have investigated preferential attachment in the context of metabolic networks. Results The connectivities of the enzymes in the metabolic network of Escherichia coli were determined and representatives for these enzymes were located in 11 eukaryotes, 17 archaea and 46 bacteria. E. coli enzymes which have representatives in eukaryotes have a higher average connectivity while enzymes which are represented only in the prokaryotes, and especially the enzymes only present in βγ-proteobacteria, have lower connectivities than expected by chance. Interestingly, the enzymes which have been proposed as candidates for horizontal gene transfer have a higher average connectivity than the other enzymes. Furthermore, It was found that new edges are added to the highly connected enzymes at a faster rate than to enzymes with low connectivities which is consistent with preferential attachment. Conclusion Here, we have found indications of preferential attachment in the metabolic network of E. coli. A possible biological explanation for preferential attachment growth of metabolic networks is that novel enzymes created through gene duplication maintain some of the compounds involved in the original reaction, throughout its future evolution. In addition, we found that enzymes which are candidates for horizontal gene transfer have a higher average connectivity than other enzymes. This indicates that while new enzymes are attached preferentially to highly connected enzymes, these highly connected enzymes have sometimes been introduced into the E. coli genome by horizontal gene transfer. We speculate

Managing Evolving Global Operations Networks

DEFF Research Database (Denmark)

Mykhaylenko, Alona; Wæhrens, Brian Vejrum; Johansen, John

2015-01-01

For many globally dispersed organisations, the home base (HB) is a historic locus of integrative and coordinating efforts that safeguard overall performance. However, the dynamism of global operations networks is increasingly pulling the centre of gravity away from the HB and dispersing it across...... the network, challenging the HB’s ability to sustain its centrality over time. To counteract this tendency, this paper addresses the gap in the literature regarding the development of the network management capability of the HB within the context of its network. Data was collected through a retrospective...... longitudinal case study of an intra-organisational operations network of one OEM and its three foreign subsidiaries. The findings suggest a row of strategic roles and corresponding managerial capabilities, which the HB needs to develop depending on the changing subsidiaries’ competencies and HB...

Labour in Global Production Networks

DEFF Research Database (Denmark)

Lund-Thomsen, Peter; Nadvi, Khalid; Chan, Anita

A critical challenge facing developing country producers is to meet international labour standards and codes of conduct in order to engage in global production networks. Evidence of gains for workers from compliance with such standards and codes remains limited and patchy. This paper focuses...... on the global football industry, a sector dominated by leading global brands who manage dispersed global production networks. It assesses the work conditions for football stitchers engaged in different forms of work organisation, factories, stitching centres, and home-based settings, in Pakistan, India......, and China. It draws on detailed qualitative primary field research with football stitching workers and producers in these three countries. The paper explains how, and why, work conditions of football stitchers differ across these locations through an analytical framework that interweaves both global...

Global action networks: agents for collective action

NARCIS (Netherlands)

Glasbergen, P.

2010-01-01

Global action networks (GANs) are civil society initiated multi-stakeholder arrangements that aim to fulfill a leadership role for systemic change in global governance for sustainable development. The paper develops a network approach to study some of these GANs as motivators of global collective

Global Electricity Trade Network: Structures and Implications

Science.gov (United States)

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S. F.; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions. PMID:27504825

Signatures of arithmetic simplicity in metabolic network architecture.

Directory of Open Access Journals (Sweden)

William J Riehl

2010-04-01

Full Text Available Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity.

The UNESCO Global Network of National Geoparks

Science.gov (United States)

Mc Keever1, P.; Zouros, N.; Patzak, M.; Missotten, R.

2009-12-01

The UNESCO Global Network of National Geoparks was founded in 2004, following the model successfully established by the European Geoparks Network in 2000. It now comprises 63 members in 19 nations across the world. A Global Geopark is an area with geological heritage of international value but where that heritage is being used for the sustainable economic benefit if the local inhabitants, primarily through education and tourism. Supported by IUGS and IUCN, the aim of the Global Geoparks Network is to facilitate exchange and sharing between members to assist in the protection and conservation of the geological heritage of our planet but to do so in way where local communities can take ownership of these special places and where they can get some sustainable economic benefit from them. While allowing for the sustainable economic development of geoparks, the network explicitly forbids the destruction or sale of the geological value of a geopark. This paper outlines the ethos of the Global Geoparks Network and describes the typical activities of geoparks and how the network functions. Using two examples it also illustrates how members of the Global Geoparks Network provide good examples as tools not only for holistic nature conservation but also for economic development.

Metabolic networks in epilepsy by MR spectroscopic imaging.

Science.gov (United States)

Pan, J W; Spencer, D D; Kuzniecky, R; Duckrow, R B; Hetherington, H; Spencer, S S

2012-12-01

The concept of an epileptic network has long been suggested from both animal and human studies of epilepsy. Based on the common observation that the MR spectroscopic imaging measure of NAA/Cr is sensitive to neuronal function and injury, we use this parameter to assess for the presence of a metabolic network in mesial temporal lobe epilepsy (MTLE) patients. A multivariate factor analysis is performed with controls and MTLE patients, using NAA/Cr measures from 12 loci: the bilateral hippocampi, thalami, basal ganglia, and insula. The factor analysis determines which and to what extent these loci are metabolically covarying. We extract two independent factors that explain the data's variability in control and MTLE patients. In controls, these factors characterize a 'thalamic' and 'dominant subcortical' function. The MTLE patients also exhibit a 'thalamic' factor, in addition to a second factor involving the ipsilateral insula and bilateral basal ganglia. These data suggest that MTLE patients demonstrate a metabolic network that involves the thalami, also seen in controls. The MTLE patients also display a second set of metabolically covarying regions that may be a manifestation of the epileptic network that characterizes limbic seizure propagation. © 2012 John Wiley & Sons A/S.

A Network of Networks Perspective on Global Trade.

Science.gov (United States)

Maluck, Julian; Donner, Reik V

2015-01-01

Mutually intertwined supply chains in contemporary economy result in a complex network of trade relationships with a highly non-trivial topology that varies with time. In order to understand the complex interrelationships among different countries and economic sectors, as well as their dynamics, a holistic view on the underlying structural properties of this network is necessary. This study employs multi-regional input-output data to decompose 186 national economies into 26 industry sectors and utilizes the approach of interdependent networks to analyze the substructure of the resulting international trade network for the years 1990-2011. The partition of the network into national economies is observed to be compatible with the notion of communities in the sense of complex network theory. By studying internal versus cross-subgraph contributions to established complex network metrics, new insights into the architecture of global trade are obtained, which allow to identify key elements of global economy. Specifically, financial services and business activities dominate domestic trade whereas electrical and machinery industries dominate foreign trade. In order to further specify each national sector's role individually, (cross-)clustering coefficients and cross-betweenness are obtained for different pairs of subgraphs. The corresponding analysis reveals that specific industrial sectors tend to favor distinct directionality patterns and that the cross-clustering coefficient for geographically close country pairs is remarkably high, indicating that spatial factors are still of paramount importance for the organization of trade patterns in modern economy. Regarding the evolution of the trade network's substructure, globalization is well-expressed by trends of several structural characteristics (e.g., link density and node strength) in the interacting network framework. Extreme events, such as the financial crisis 2008/2009, are manifested as anomalies superimposed to

A Bayesian approach to the evolution of metabolic networks on a phylogeny.

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Aziz Mithani

2010-08-01

Full Text Available The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions or complex (incorporating dependencies among reactions stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks.

A Network of Networks Perspective on Global Trade

Science.gov (United States)

Maluck, Julian; Donner, Reik V.

2015-01-01

Mutually intertwined supply chains in contemporary economy result in a complex network of trade relationships with a highly non-trivial topology that varies with time. In order to understand the complex interrelationships among different countries and economic sectors, as well as their dynamics, a holistic view on the underlying structural properties of this network is necessary. This study employs multi-regional input-output data to decompose 186 national economies into 26 industry sectors and utilizes the approach of interdependent networks to analyze the substructure of the resulting international trade network for the years 1990–2011. The partition of the network into national economies is observed to be compatible with the notion of communities in the sense of complex network theory. By studying internal versus cross-subgraph contributions to established complex network metrics, new insights into the architecture of global trade are obtained, which allow to identify key elements of global economy. Specifically, financial services and business activities dominate domestic trade whereas electrical and machinery industries dominate foreign trade. In order to further specify each national sector’s role individually, (cross-)clustering coefficients and cross-betweenness are obtained for different pairs of subgraphs. The corresponding analysis reveals that specific industrial sectors tend to favor distinct directionality patterns and that the cross-clustering coefficient for geographically close country pairs is remarkably high, indicating that spatial factors are still of paramount importance for the organization of trade patterns in modern economy. Regarding the evolution of the trade network’s substructure, globalization is well-expressed by trends of several structural characteristics (e.g., link density and node strength) in the interacting network framework. Extreme events, such as the financial crisis 2008/2009, are manifested as anomalies superimposed

Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator

DEFF Research Database (Denmark)

Usaite, Renata; Jewett, Michael Christopher; Soberano de Oliveira, Ana Paula

2009-01-01

Highly conserved among eukaryotic cells, the AMP-activated kinase (AMPK) is a central regulator of carbon metabolism. To map the complete network of interactions around AMPK in yeast (Snf1) and to evaluate the role of its regulatory subunit Snf4, we measured global mRNA, protein and metabolite...

Small-worldness and gender differences of large scale brain metabolic covariance networks in young adults: a FDG PET study of 400 subjects.

Science.gov (United States)

Hu, Yuxiao; Xu, Qiang; Shen, Junkang; Li, Kai; Zhu, Hong; Zhang, Zhiqiang; Lu, Guangming

2015-02-01

Many studies have demonstrated the small-worldness of the human brain, and have revealed a sexual dimorphism in brain network properties. However, little is known about the gender effects on the topological organization of the brain metabolic covariance networks. To investigate the small-worldness and the gender differences in the topological architectures of human brain metabolic networks. FDG-PET data of 400 healthy right-handed subjects (200 women and 200 age-matched men) were involved in the present study. Metabolic networks of each gender were constructed by calculating the covariance of regional cerebral glucose metabolism (rCMglc) across subjects on the basis of AAL parcellation. Gender differences of network and nodal properties were investigated by using the graph theoretical approaches. Moreover, the gender-related difference of rCMglc in each brain region was tested for investigating the relationships between the hub regions and the brain regions showing significant gender-related differences in rCMglc. We found prominent small-world properties in the domain of metabolic networks in each gender. No significant gender difference in the global characteristics was found. Gender differences of nodal characteristic were observed in a few brain regions. We also found bilateral and lateralized distributions of network hubs in the females and males. Furthermore, we first reported that some hubs of a gender located in the brain regions showing weaker rCMglc in this gender than the other gender. The present study demonstrated that small-worldness was existed in metabolic networks, and revealed gender differences of organizational patterns in metabolic network. These results maybe provided insights into the understanding of the metabolic substrates underlying individual differences in cognition and behaviors. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Ensuring dynamic strategic fit of firms that compete globally in alliances and networks: proposing the Global SNA - Strategic Network Analysis - framework

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T. Diana L. Van Aduard de Macedo-Soares

2011-02-01

Full Text Available In order to sustain their competitive advantage in the current increasingly globalized and turbulent context, more and more firms are competing globally in alliances and networks that oblige them to adopt new managerial paradigms and tools. However, their strategic analyses rarely take into account the strategic implications of these alliances and networks, considering their global relational characteristics, admittedly because of a lack of adequate tools to do so. This paper contributes to research that seeks to fill this gap by proposing the Global Strategic Network Analysis - SNA - framework. Its purpose is to help firms that compete globally in alliances and networks to carry out their strategic assessments and decision-making with a view to ensuring dynamic strategic fit from both a global and relational perspective.

Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes

DEFF Research Database (Denmark)

Zelezniak, Aleksej; Pers, Tune Hannes; Pinho Soares, Simao Pedro

2010-01-01

mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets...... with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites—metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment...... factor regulatory network connecting several parts of metabolism. The identified transcription factors include members of the CREB, NRF1 and PPAR family, among others, and represent regulatory targets for further experimental analysis. Overall, our results provide a holistic picture of key metabolic...

Logistical networking: a global storage network

International Nuclear Information System (INIS)

Beck, Micah; Moore, Terry

2005-01-01

The absence of an adequate distributed storage infrastructure for data buffering has become a significant impediment to the flow of work in the wide area, data intensive collaborations that are increasingly characteristic of leading edge research in several fields. One solution to this problem, pioneered under DOE's SciDAC program, is Logistical Networking, which provides a framework for a globally scalable, maximally interoperable storage network based on the Internet Backplane Protocol (IBP). This paper provides a brief overview of the Logistical Networking (LN) architecture, the middleware developed to exploit its value, and a few of the applications that some of research communities have made of it

Coordinations between gene modules control the operation of plant amino acid metabolic networks

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Galili Gad

2009-01-01

Full Text Available Abstract Background Being sessile organisms, plants should adjust their metabolism to dynamic changes in their environment. Such adjustments need particular coordination in branched metabolic networks in which a given metabolite can be converted into multiple other metabolites via different enzymatic chains. In the present report, we developed a novel "Gene Coordination" bioinformatics approach and use it to elucidate adjustable transcriptional interactions of two branched amino acid metabolic networks in plants in response to environmental stresses, using publicly available microarray results. Results Using our "Gene Coordination" approach, we have identified in Arabidopsis plants two oppositely regulated groups of "highly coordinated" genes within the branched Asp-family network of Arabidopsis plants, which metabolizes the amino acids Lys, Met, Thr, Ile and Gly, as well as a single group of "highly coordinated" genes within the branched aromatic amino acid metabolic network, which metabolizes the amino acids Trp, Phe and Tyr. These genes possess highly coordinated adjustable negative and positive expression responses to various stress cues, which apparently regulate adjustable metabolic shifts between competing branches of these networks. We also provide evidence implying that these highly coordinated genes are central to impose intra- and inter-network interactions between the Asp-family and aromatic amino acid metabolic networks as well as differential system interactions with other growth promoting and stress-associated genome-wide genes. Conclusion Our novel Gene Coordination elucidates that branched amino acid metabolic networks in plants are regulated by specific groups of highly coordinated genes that possess adjustable intra-network, inter-network and genome-wide transcriptional interactions. We also hypothesize that such transcriptional interactions enable regulatory metabolic adjustments needed for adaptation to the stresses.

Solidarity Action in Global Labor Networks

DEFF Research Database (Denmark)

Wad, Peter

2014-01-01

Globalization transforms workforces of transnational corporation from predominantly home countrydominated workforces into foreign-dominated, multinational workforces. Thus, the national grounding of trade unions as the key form of labor organizing is challenged by new multinational compositions...... and cross-border relocations of corporate employment affecting working conditions of employees and trade unions in local places. We assume that economic globalization is characterized by expanding global corporate network of vertically and horizontally integrated (equity-based) and disintegrated (nonequity......-based) value chains. We also assume that globalization can both impede and enable labor empowerment. Based on these premises the key question is, how can labor leverage effective power against management in global corporate networks? This question is split into two subquestions: a) How can labor theoretically...

Toward the automated generation of genome-scale metabolic networks in the SEED.

Science.gov (United States)

DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

2007-04-26

Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the

Toward the automated generation of genome-scale metabolic networks in the SEED

Directory of Open Access Journals (Sweden)

Gould John

2007-04-01

Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

Integration of metabolome data with metabolic networks reveals reporter reactions

DEFF Research Database (Denmark)

Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen

2006-01-01

Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...... network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from...... is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through...

MANAGING GLOBAL OPERATIONS NETWORKS IN MOTION

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Jørgensen, Claus; Sørensen, Brian Vejrum

2008-01-01

capabilities and intensified need for transfer, assimilation and augmentation of activities and know-how within the network. Based on these the paper highlights some organisational effects and managerial challenges the companies face regarding rapid changes in their networks configurations and capabilities.......Most industrial companies are, for reasons related to cost, market access or knowledge, working with some aspect of offshore operations. This may take form of captive operations or through outsourcing of activities overseas. With this trend, global operations networks are emerging resulting...... in corporate strategic repositioning, re-configurations of sites, and changes to the underlying capabilities. The paper is based on cases of 3 Danish companies and their global supply networks. These networks are not in a steady state, they evolve as a consequence of the ongoing co-evolution between the focal...

Exploring photosynthesis evolution by comparative analysis of metabolic networks between chloroplasts and photosynthetic bacteria

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Hou Jing

2006-04-01

Full Text Available Abstract Background Chloroplasts descended from cyanobacteria and have a drastically reduced genome following an endosymbiotic event. Many genes of the ancestral cyanobacterial genome have been transferred to the plant nuclear genome by horizontal gene transfer. However, a selective set of metabolism pathways is maintained in chloroplasts using both chloroplast genome encoded and nuclear genome encoded enzymes. As an organelle specialized for carrying out photosynthesis, does the chloroplast metabolic network have properties adapted for higher efficiency of photosynthesis? We compared metabolic network properties of chloroplasts and prokaryotic photosynthetic organisms, mostly cyanobacteria, based on metabolic maps derived from genome data to identify features of chloroplast network properties that are different from cyanobacteria and to analyze possible functional significance of those features. Results The properties of the entire metabolic network and the sub-network that consists of reactions directly connected to the Calvin Cycle have been analyzed using hypergraph representation. Results showed that the whole metabolic networks in chloroplast and cyanobacteria both possess small-world network properties. Although the number of compounds and reactions in chloroplasts is less than that in cyanobacteria, the chloroplast's metabolic network has longer average path length, a larger diameter, and is Calvin Cycle -centered, indicating an overall less-dense network structure with specific and local high density areas in chloroplasts. Moreover, chloroplast metabolic network exhibits a better modular organization than cyanobacterial ones. Enzymes involved in the same metabolic processes tend to cluster into the same module in chloroplasts. Conclusion In summary, the differences in metabolic network properties may reflect the evolutionary changes during endosymbiosis that led to the improvement of the photosynthesis efficiency in higher plants. Our

Metabolic Brain Network Analysis of Hypothyroidism Symptom Based on [18F]FDG-PET of Rats.

Science.gov (United States)

Wan, Hongkai; Tan, Ziyu; Zheng, Qiang; Yu, Jing

2018-03-12

Recent researches have demonstrated the value of using 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) positron emission tomography (PET) imaging to reveal the hypothyroidism-related damages in local brain regions. However, the influence of hypothyroidism on the entire brain network is barely studied. This study focuses on the application of graph theory on analyzing functional brain networks of the hypothyroidism symptom. For both the hypothyroidism and the control groups of Wistar rats, the functional brain networks were constructed by thresholding the glucose metabolism correlation matrices of 58 brain regions. The network topological properties (including the small-world properties and the nodal centralities) were calculated and compared between the two groups. We found that the rat brains, like human brains, have typical properties of the small-world network in both the hypothyroidism and the control groups. However, the hypothyroidism group demonstrated lower global efficiency and decreased local cliquishness of the brain network, indicating hypothyroidism-related impairment to the brain network. The hypothyroidism group also has decreased nodal centrality in the left posterior hippocampus, the right hypothalamus, pituitary, pons, and medulla. This observation accorded with the hypothyroidism-related functional disorder of hypothalamus-pituitary-thyroid (HPT) feedback regulation mechanism. Our research quantitatively confirms that hypothyroidism hampers brain cognitive function by causing impairment to the brain network of glucose metabolism. This study reveals the feasibility and validity of applying graph theory method to preclinical [ 18 F]FDG-PET images and facilitates future study on human subjects.

Second Law of Thermodynamics Applied to Metabolic Networks

Science.gov (United States)

Nigam, R.; Liang, S.

2003-01-01

We present a simple algorithm based on linear programming, that combines Kirchoff's flux and potential laws and applies them to metabolic networks to predict thermodynamically feasible reaction fluxes. These law's represent mass conservation and energy feasibility that are widely used in electrical circuit analysis. Formulating the Kirchoff's potential law around a reaction loop in terms of the null space of the stoichiometric matrix leads to a simple representation of the law of entropy that can be readily incorporated into the traditional flux balance analysis without resorting to non-linear optimization. Our technique is new as it can easily check the fluxes got by applying flux balance analysis for thermodynamic feasibility and modify them if they are infeasible so that they satisfy the law of entropy. We illustrate our method by applying it to the network dealing with the central metabolism of Escherichia coli. Due to its simplicity this algorithm will be useful in studying large scale complex metabolic networks in the cell of different organisms.

Genetic networks of liver metabolism revealed by integration of metabolic and transcriptional profiling.

Directory of Open Access Journals (Sweden)

Christine T Ferrara

2008-03-01

Full Text Available Although numerous quantitative trait loci (QTL influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identification of the individual gene(s and molecular pathways leading to those phenotypes is often elusive. One way to improve understanding of genetic architecture is to classify phenotypes in greater depth by including transcriptional and metabolic profiling. In the current study, we have generated and analyzed mRNA expression and metabolic profiles in liver samples obtained in an F2 intercross between the diabetes-resistant C57BL/6 leptin(ob/ob and the diabetes-susceptible BTBR leptin(ob/ob mouse strains. This cross, which segregates for genotype and physiological traits, was previously used to identify several diabetes-related QTL. Our current investigation includes microarray analysis of over 40,000 probe sets, plus quantitative mass spectrometry-based measurements of sixty-seven intermediary metabolites in three different classes (amino acids, organic acids, and acyl-carnitines. We show that liver metabolites map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal networks for control of specific metabolic processes in liver. As a proof of principle of the practical significance of this integrative approach, we illustrate the construction of a specific causal network that links gene expression and metabolic changes in the context of glutamate metabolism, and demonstrate its validity by showing that genes in the network respond to changes in glutamine and glutamate availability. Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes.

Strategic Knowledge Networks for Global Education

Science.gov (United States)

Peterson, J. Fiona

2009-01-01

The inherent opportunities for communication, collaboration and experiential learning in an online and global network create the impetus for the new network paradigm in higher education. A strategic knowledge network in education was designed and developed to build "Mode 2" knowledge capabilities; create new knowledge for innovative…

Blueprint for antimicrobial hit discovery targeting metabolic networks.

Science.gov (United States)

Shen, Y; Liu, J; Estiu, G; Isin, B; Ahn, Y-Y; Lee, D-S; Barabási, A-L; Kapatral, V; Wiest, O; Oltvai, Z N

2010-01-19

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy.

State Support: A Prerequisite for Global Health Network Effectiveness

Science.gov (United States)

Marten, Robert; Smith, Richard D.

2018-01-01

Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks’ success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks’ effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research. PMID:29524958

Anthropomorphic Networks as Representatives of Global Consciousness

Directory of Open Access Journals (Sweden)

Sergii Yahodzinskyi

2018-02-01

Full Text Available There has been analyzed a phenomenon of global consciousness, and its cultural and historical, civilizational dimensions have been substantiated. There has been demonstrated that the concept of planetary consciousness, global thinking, noosphere was described for the first time in the philosophy of cosmism. However, in modern conditions ideas of representatives of the naturalistic philosophical direction of cosmism have not lost their heuristic potential. They can be reconsidered in a new fashion within the context of emerging anthropomorphic (human dimension networks. There has been proved that global consciousness is a component of the social and cultural potential of global information networks defining vectors to prospects of humanity progress in the 21st century. Relying on methodology of the structural and functional analysis, the author arrives at a conclusion about global networks obtaining the status of representatives of global consciousness. This is the area of networks where all relevant information is concentrated – from statistical data to scientific and technical information. Access to these data is limited by human abilities and is realized in the form of discrete requests with using heuristic algorithms of information procession. A suggestion is introduced considering the fact that modern society being a self-organized system seeks to gain stable condition. Anthropomorphic networks are means of decreasing social entropy, which is growing as a result of any kind of human intervention into social processes. Thus, for the first time a human is challenged by their intellect, ability to create, discover and control.

The network of global corporate control.

Science.gov (United States)

Vitali, Stefania; Glattfelder, James B; Battiston, Stefano

2011-01-01

The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international ownership network, along with the computation of the control held by each global player. We find that transnational corporations form a giant bow-tie structure and that a large portion of control flows to a small tightly-knit core of financial institutions. This core can be seen as an economic "super-entity" that raises new important issues both for researchers and policy makers.

The CERN Global Network opens its doors to companies

CERN Multimedia

Francesco Poppi

2010-01-01

Six months after its launch, the CERN Global Network already has almost one thousand members. Today, it is opening its doors to companies from CERN's Member States. This will open up a variety of new professional and career opportunities to all the members and will enhance the networking capabilities of all parties involved.   Screenshot of the CERN Global Network website. A new item has recently appeared on the top menu of the Network's website: “Organisations”. This is the entry point for companies and, later, research institutes, wishing to join. “The CERN Global Network brings together hundreds of people who have worked at or with CERN and who have a wealth of skills and expertise. Thanks to the Network, the job opportunities made available by the companies will become visible to the wider community,” says Linda Orr-Easo, a member of the Knowledge and Technology Transfer Group and the CERN Global Network Manager. In addition to creating new career opp...

Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

Science.gov (United States)

Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

2013-03-28

Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus. Copyright © 2013 Elsevier Inc. All rights reserved.

E-njoy the first CERN Global Network e-vent!

CERN Multimedia

CERN Bulletin

2010-01-01

Empowered by the considerable interest it received after it was launched, the CERN Global Network takes off and organizes the first e-vent, which will be a special talk on science communication that will be held on 29 June at 4.30 p.m. in the Council Chamber. You can experience it live on the Global Network site and, if you are a Member, provide feedback. Stay linked!   On the CERN Global Network webpage, you will be able to choose the topic of the next e-vents. Seven weeks after its launch, about 600 people have already joined the CERN Global Network and six thematic groups have been created. The whole idea of joining the Network is to stay connected or reconnect with life at CERN where seminars, talks and discussions are undoubtedly a very important and much appreciated part of it. This is where the e-vents come into play. “The e-vents enable members of the Global Network to participate in selected events taking place at CERN, such as lectures or panel discussions. They will...

Development of the Global Measles Laboratory Network.

Science.gov (United States)

Featherstone, David; Brown, David; Sanders, Ray

2003-05-15

The routine reporting of suspected measles cases and laboratory testing of samples from these cases is the backbone of measles surveillance. The Global Measles Laboratory Network (GMLN) has developed standards for laboratory confirmation of measles and provides training resources for staff of network laboratories, reference materials and expertise for the development and quality control of testing procedures, and accurate information for the Measles Mortality Reduction and Regional Elimination Initiative. The GMLN was developed along the lines of the successful Global Polio Laboratory Network, and much of the polio laboratory infrastructure was utilized for measles. The GMLN has developed as countries focus on measles control activities following successful eradication of polio. Currently more than 100 laboratories are part of the global network and follow standardized testing and reporting procedures. A comprehensive laboratory accreditation process will be introduced in 2002 with six quality assurance and performance indicators.

Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

DEFF Research Database (Denmark)

Förster, Jochen; Famili, I.; Fu, P.

2003-01-01

The metabolic network in the yeast Saccharomyces cerevisiae was reconstructed using currently available genomic, biochemical, and physiological information. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, and transport steps between the compartments...

Global dissipativity of continuous-time recurrent neural networks with time delay

International Nuclear Information System (INIS)

Liao Xiaoxin; Wang Jun

2003-01-01

This paper addresses the global dissipativity of a general class of continuous-time recurrent neural networks. First, the concepts of global dissipation and global exponential dissipation are defined and elaborated. Next, the sets of global dissipativity and global exponentially dissipativity are characterized using the parameters of recurrent neural network models. In particular, it is shown that the Hopfield network and cellular neural networks with or without time delays are dissipative systems

Structure and evolution of the global seafood trade network

Science.gov (United States)

Gephart, Jessica A.; Pace, Michael L.

2015-12-01

The food production system is increasingly global and seafood is among the most highly traded commodities. Global trade can improve food security by providing access to a greater variety of foods, increasing wealth, buffering against local supply shocks, and benefit the environment by increasing overall use efficiency for some resources. However, global trade can also expose countries to external supply shocks and degrade the environment by increasing resource demand and loosening feedbacks between consumers and the impacts of food production. As a result, changes in global food trade can have important implications for both food security and the environmental impacts of production. Measurements of globalization and the environmental impacts of food production require data on both total trade and the origin and destination of traded goods (the network structure). While the global trade network of agricultural and livestock products has previously been studied, seafood products have been excluded. This study describes the structure and evolution of the global seafood trade network, including metrics quantifying the globalization of seafood, shifts in bilateral trade flows, changes in centrality and comparisons of seafood to agricultural and industrial trade networks. From 1994 to 2012 the number of countries trading in the network remained relatively constant, while the number of trade partnerships increased by over 65%. Over this same period, the total quantity of seafood traded increased by 58% and the value increased 85% in real terms. These changes signify the increasing globalization of seafood products. Additionally, the trade patterns in the network indicate: increased influence of Thailand and China, strengthened intraregional trade, and increased exports from South America and Asia. In addition to characterizing these network changes, this study identifies data needs in order to connect seafood trade with environmental impacts and food security outcomes.

GLOBAL CONVERGENCE FOR THE XOR BOOLEAN NETWORKS

OpenAIRE

Ho, Juei-Ling

2009-01-01

Shih and Ho have proved a global convergent theorem for boolean network: if a map from $\\{0,1\\}^{n}$ to itself defines a boolean network has the conditions: (1) each column of the discrete Jacobian matrix of each element of $\\{0,1\\}^{n}$ is either a unit vector or a zero vector; (2) all the boolean eigenvalues of the discrete Jacobian matrix of this map evaluated at each element of $\\{0,1\\}^{n}$ are zero, then it has a unique fixed point and this boolean network is global convergent to the fi...

Limited Influence of Oxygen on the Evolution of Chemical Diversity in Metabolic Networks

Directory of Open Access Journals (Sweden)

Kazuhiro Takemoto

2013-10-01

Full Text Available Oxygen is thought to promote species and biomolecule diversity. Previous studies have suggested that oxygen expands metabolic networks by acquiring metabolites with different chemical properties (higher hydrophobicity, for example. However, such conclusions are typically based on biased evaluation, and are therefore non-conclusive. Thus, we re-investigated the effect of oxygen on metabolic evolution using a phylogenetic comparative method and metadata analysis to reduce the bias as much as possible. Notably, we found no difference in metabolic network expansion between aerobes and anaerobes when evaluating phylogenetic relationships. Furthermore, we showed that previous studies have overestimated or underestimated the degrees of differences in the chemical properties (e.g., hydrophobicity between oxic and anoxic metabolites in metabolic networks of unicellular organisms; however, such overestimation was not observed when considering the metabolic networks of multicellular organisms. These findings indicate that the contribution of oxygen to increased chemical diversity in metabolic networks is lower than previously thought; rather, phylogenetic signals and cell-cell communication result in increased chemical diversity. However, this conclusion does not contradict the effect of oxygen on metabolic evolution; instead, it provides a deeper understanding of how oxygen contributes to metabolic evolution despite several limitations in data analysis methods.

Structure versus time in the evolutionary diversification of avian carotenoid metabolic networks.

Science.gov (United States)

Morrison, Erin S; Badyaev, Alexander V

2018-05-01

Historical associations of genes and proteins are thought to delineate pathways available to subsequent evolution; however, the effects of past functional involvements on contemporary evolution are rarely quantified. Here, we examined the extent to which the structure of a carotenoid enzymatic network persists in avian evolution. Specifically, we tested whether the evolution of carotenoid networks was most concordant with phylogenetically structured expansion from core reactions of common ancestors or with subsampling of biochemical pathway modules from an ancestral network. We compared structural and historical associations in 467 carotenoid networks of extant and ancestral species and uncovered the overwhelming effect of pre-existing metabolic network structure on carotenoid diversification over the last 50 million years of avian evolution. Over evolutionary time, birds repeatedly subsampled and recombined conserved biochemical modules, which likely maintained the overall structure of the carotenoid metabolic network during avian evolution. These findings explain the recurrent convergence of evolutionary distant species in carotenoid metabolism and weak phylogenetic signal in avian carotenoid evolution. Remarkable retention of an ancient metabolic structure throughout extensive and prolonged ecological diversification in avian carotenoid metabolism illustrates a fundamental requirement of organismal evolution - historical continuity of a deterministic network that links past and present functional associations of its components. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Are we connected? : Ports in Global Networks

NARCIS (Netherlands)

R.A. Zuidwijk (Rob)

2015-01-01

markdownabstractAbstract Global supply chains are built on organizational, information, and logistics networks. Ports are connected via these networks and also need to connect these networks. Synchromodality is an innovative concept for container transportation, and the port plays an important

A general model for metabolic scaling in self-similar asymmetric networks.

Directory of Open Access Journals (Sweden)

Alexander Byers Brummer

2017-03-01

Full Text Available How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE model argues that these two principles (space-filling and energy minimization are (i general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber's Law can still be attained within many asymmetric networks.

Three Eras in Global Tobacco Control: How Global Governance Processes Influenced Online Tobacco Control Networking.

Science.gov (United States)

Wipfli, Heather; Chu, Kar-Hai; Lancaster, Molly; Valente, Thomas

2016-01-01

Online networks can serve as a platform to diffuse policy innovations and enhance global health governance. This study focuses on how shifts in global health governance may influence related online networks. We compare social network metrics (average degree centrality [AVGD], density [D] and clustering coefficient [CC]) of Globalink, an online network of tobacco control advocates, across three eras in global tobacco control governance; pre-Framework Convention on Tobacco Control (FCTC) policy transfer (1992-1998), global regime formation through the FCTC negotiations (1999-2005), and philanthropic funding through the Bloomberg Initiative (2006-2012). Prior to 1999, Globalink was driven by a handful of high-income countries (AVGD=1.908 D=0.030, CC=0.215). The FCTC negotiations (1999-2005) corresponded with a rapid uptick in the number of countries represented within Globalink and new members were most often brought into the network through relationships with regional neighbors (AVGD=2.824, D=0.021, CC=0.253). Between 2006 and 2012, the centrality of the US in the network increases significantly (AVGD=3.414, D=0.023, CC=0.310). The findings suggest that global institutionalization through WHO, as with the FCTC, can lead to the rapid growth of decentralized online networks. Alternatively, private initiatives, such as the Bloomberg Initiative, can lead to clustering in which a single source of information gains increasing influence over an online network.

Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

OpenAIRE

Mart?n-Jim?nez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; Gonz?lez, Janneth

2017-01-01

Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework t...

Resistance Genes in Global Crop Breeding Networks.

Science.gov (United States)

Garrett, K A; Andersen, K F; Asche, F; Bowden, R L; Forbes, G A; Kulakow, P A; Zhou, B

2017-10-01

Resistance genes are a major tool for managing crop diseases. The networks of crop breeders who exchange resistance genes and deploy them in varieties help to determine the global landscape of resistance and epidemics, an important system for maintaining food security. These networks function as a complex adaptive system, with associated strengths and vulnerabilities, and implications for policies to support resistance gene deployment strategies. Extensions of epidemic network analysis can be used to evaluate the multilayer agricultural networks that support and influence crop breeding networks. Here, we evaluate the general structure of crop breeding networks for cassava, potato, rice, and wheat. All four are clustered due to phytosanitary and intellectual property regulations, and linked through CGIAR hubs. Cassava networks primarily include public breeding groups, whereas others are more mixed. These systems must adapt to global change in climate and land use, the emergence of new diseases, and disruptive breeding technologies. Research priorities to support policy include how best to maintain both diversity and redundancy in the roles played by individual crop breeding groups (public versus private and global versus local), and how best to manage connectivity to optimize resistance gene deployment while avoiding risks to the useful life of resistance genes. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

FluxVisualizer, a Software to Visualize Fluxes through Metabolic Networks

Directory of Open Access Journals (Sweden)

Tim Daniel Rose

2018-04-01

Full Text Available FluxVisualizer (Version 1.0, 2017, freely available at https://fluxvisualizer.ibgc.cnrs.fr is a software to visualize fluxes values on a scalable vector graphic (SVG representation of a metabolic network by colouring or increasing the width of reaction arrows of the SVG file. FluxVisualizer does not aim to draw metabolic networks but to use a customer’s SVG file allowing him to exploit his representation standards with a minimum of constraints. FluxVisualizer is especially suitable for small to medium size metabolic networks, where a visual representation of the fluxes makes sense. The flux distribution can either be an elementary flux mode (EFM, a flux balance analysis (FBA result or any other flux distribution. It allows the automatic visualization of a series of pathways of the same network as is needed for a set of EFMs. The software is coded in python3 and provides a graphical user interface (GUI and an application programming interface (API. All functionalities of the program can be used from the API and the GUI and allows advanced users to add their own functionalities. The software is able to work with various formats of flux distributions (Metatool, CellNetAnalyzer, COPASI and FAME export files as well as with Excel files. This simple software can save a lot of time when evaluating fluxes simulations on a metabolic network.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

Directory of Open Access Journals (Sweden)

Kumari Sonal Choudhary

2016-06-01

Full Text Available Epithelial to mesenchymal transition (EMT is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR, are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E and mesenchymal (EGFR_M networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

Science.gov (United States)

Choudhary, Kumari Sonal; Rohatgi, Neha; Halldorsson, Skarphedinn; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

2016-06-01

Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

From Local to Global Dilemmas in Social Networks

OpenAIRE

Pinheiro, Fl?vio L.; Pacheco, Jorge M.; Santos, Francisco C.

2012-01-01

Social networks affect in such a fundamental way the dynamics of the population they support that the global, population-wide behavior that one observes often bears no relation to the individual processes it stems from. Up to now, linking the global networked dynamics to such individual mechanisms has remained elusive. Here we study the evolution of cooperation in networked populations and let individuals interact via a 2-person Prisoner's Dilemma ? a characteristic defection dominant social ...

The global structure of knowledge network

NARCIS (Netherlands)

Angelopoulos, Spyros; Lomi, Alessandro

2017-01-01

In this paper, we treat patent citations as knowledge networks connecting pieces of formalized knowledge and people, and focus on how ideas are connected, rather than how they are protected. We focus on the global structural properties of formalized knowledge network, and more specifically on the

Global network centrality of university rankings

Science.gov (United States)

Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

2017-10-01

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

Metabolic Network Discovery by Top-Down and Bottom-Up Approaches and Paths for Reconciliation

Energy Technology Data Exchange (ETDEWEB)

Çakır, Tunahan, E-mail: tcakir@gyte.edu.tr [Computational Systems Biology Group, Department of Bioengineering, Gebze Technical University (formerly known as Gebze Institute of Technology), Gebze (Turkey); Khatibipour, Mohammad Jafar [Computational Systems Biology Group, Department of Bioengineering, Gebze Technical University (formerly known as Gebze Institute of Technology), Gebze (Turkey); Department of Chemical Engineering, Gebze Technical University (formerly known as Gebze Institute of Technology), Gebze (Turkey)

2014-12-03

The primary focus in the network-centric analysis of cellular metabolism by systems biology approaches is to identify the active metabolic network for the condition of interest. Two major approaches are available for the discovery of the condition-specific metabolic networks. One approach starts from genome-scale metabolic networks, which cover all possible reactions known to occur in the related organism in a condition-independent manner, and applies methods such as the optimization-based Flux-Balance Analysis to elucidate the active network. The other approach starts from the condition-specific metabolome data, and processes the data with statistical or optimization-based methods to extract information content of the data such that the active network is inferred. These approaches, termed bottom-up and top-down, respectively, are currently employed independently. However, considering that both approaches have the same goal, they can both benefit from each other paving the way for the novel integrative analysis methods of metabolome data- and flux-analysis approaches in the post-genomic era. This study reviews the strengths of constraint-based analysis and network inference methods reported in the metabolic systems biology field; then elaborates on the potential paths to reconcile the two approaches to shed better light on how the metabolism functions.

Metabolic Network Discovery by Top-Down and Bottom-Up Approaches and Paths for Reconciliation

International Nuclear Information System (INIS)

Çakır, Tunahan; Khatibipour, Mohammad Jafar

2014-01-01

The primary focus in the network-centric analysis of cellular metabolism by systems biology approaches is to identify the active metabolic network for the condition of interest. Two major approaches are available for the discovery of the condition-specific metabolic networks. One approach starts from genome-scale metabolic networks, which cover all possible reactions known to occur in the related organism in a condition-independent manner, and applies methods such as the optimization-based Flux-Balance Analysis to elucidate the active network. The other approach starts from the condition-specific metabolome data, and processes the data with statistical or optimization-based methods to extract information content of the data such that the active network is inferred. These approaches, termed bottom-up and top-down, respectively, are currently employed independently. However, considering that both approaches have the same goal, they can both benefit from each other paving the way for the novel integrative analysis methods of metabolome data- and flux-analysis approaches in the post-genomic era. This study reviews the strengths of constraint-based analysis and network inference methods reported in the metabolic systems biology field; then elaborates on the potential paths to reconcile the two approaches to shed better light on how the metabolism functions.

Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p

DEFF Research Database (Denmark)

Moxley, Joel F.; Jewett, Michael Christopher; Antoniewicz, Maciek R.

2009-01-01

. However, the potential of systems biology approaches is limited by difficulties in integrating metabolic measurements across the functional levels of the cell despite their being most closely linked to cellular phenotype. To address this limitation, we developed a model-based approach to correlate m......RNA and metabolic flux data that combines information from both interaction network models and flux determination models. We started by quantifying 5,764 mRNAs, 54 metabolites, and 83 experimental C-13-based reaction fluxes in continuous cultures of yeast under stress in the absence or presence of global regulator...... of metabolic flux (i.e., use of different reaction pathways) by transcriptional regulation and metabolite interaction density (i.e., level of pairwise metabolite-protein interactions) as a key biosynthetic control determinant. Furthermore, this model predicted flux rewiring in studies of follow...

Global synchronization of a class of delayed complex networks

International Nuclear Information System (INIS)

Li Ping; Yi Zhang; Zhang Lei

2006-01-01

Global synchronization of a class of complex networks with time-varying delays is investigated in this paper. Some sufficient conditions are derived. These conditions show that the synchronization of delayed complex networks can be determined by their topologies. In addition, these conditions are simply represented in terms of the networks coupling matrix and are easy to be checked. A typical example of complex networks with chaotic nodes is employed to illustrate the obtained global synchronization results

Metabolic network model guided engineering ethylmalonyl-CoA pathway to improve ascomycin production in Streptomyces hygroscopicus var. ascomyceticus.

Science.gov (United States)

Wang, Junhua; Wang, Cheng; Song, Kejing; Wen, Jianping

2017-10-03

Ascomycin is a 23-membered polyketide macrolide with high immunosuppressant and antifungal activity. As the lower production in bio-fermentation, global metabolic analysis is required to further explore its biosynthetic network and determine the key limiting steps for rationally engineering. To achieve this goal, an engineering approach guided by a metabolic network model was implemented to better understand ascomycin biosynthesis and improve its production. The metabolic conservation of Streptomyces species was first investigated by comparing the metabolic enzymes of Streptomyces coelicolor A3(2) with those of 31 Streptomyces strains, the results showed that more than 72% of the examined proteins had high sequence similarity with counterparts in every surveyed strain. And it was found that metabolic reactions are more highly conserved than the enzymes themselves because of its lower diversity of metabolic functions than that of genes. The main source of the observed metabolic differences was from the diversity of secondary metabolism. According to the high conservation of primary metabolic reactions in Streptomyces species, the metabolic network model of Streptomyces hygroscopicus var. ascomyceticus was constructed based on the latest reported metabolic model of S. coelicolor A3(2) and validated experimentally. By coupling with flux balance analysis and using minimization of metabolic adjustment algorithm, potential targets for ascomycin overproduction were predicted. Since several of the preferred targets were highly associated with ethylmalonyl-CoA biosynthesis, two target genes hcd (encoding 3-hydroxybutyryl-CoA dehydrogenase) and ccr (encoding crotonyl-CoA carboxylase/reductase) were selected for overexpression in S. hygroscopicus var. ascomyceticus FS35. Both the mutants HA-Hcd and HA-Ccr showed higher ascomycin titer, which was consistent with the model predictions. Furthermore, the combined effects of the two genes were evaluated and the strain HA

Bringing metabolic networks to life: integration of kinetic, metabolic, and proteomic data

Directory of Open Access Journals (Sweden)

Klipp Edda

2006-12-01

Full Text Available Abstract Background Translating a known metabolic network into a dynamic model requires reasonable guesses of all enzyme parameters. In Bayesian parameter estimation, model parameters are described by a posterior probability distribution, which scores the potential parameter sets, showing how well each of them agrees with the data and with the prior assumptions made. Results We compute posterior distributions of kinetic parameters within a Bayesian framework, based on integration of kinetic, thermodynamic, metabolic, and proteomic data. The structure of the metabolic system (i.e., stoichiometries and enzyme regulation needs to be known, and the reactions are modelled by convenience kinetics with thermodynamically independent parameters. The parameter posterior is computed in two separate steps: a first posterior summarises the available data on enzyme kinetic parameters; an improved second posterior is obtained by integrating metabolic fluxes, concentrations, and enzyme concentrations for one or more steady states. The data can be heterogenous, incomplete, and uncertain, and the posterior is approximated by a multivariate log-normal distribution. We apply the method to a model of the threonine synthesis pathway: the integration of metabolic data has little effect on the marginal posterior distributions of individual model parameters. Nevertheless, it leads to strong correlations between the parameters in the joint posterior distribution, which greatly improve the model predictions by the following Monte-Carlo simulations. Conclusion We present a standardised method to translate metabolic networks into dynamic models. To determine the model parameters, evidence from various experimental data is combined and weighted using Bayesian parameter estimation. The resulting posterior parameter distribution describes a statistical ensemble of parameter sets; the parameter variances and correlations can account for missing knowledge, measurement

Global Synoptic Climatology Network (GSCN)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Dataset DSI-9290 is the result of a joint effort to create a Global Synoptic Climatology Network among the Meteorological Service of Canada (Downsview, Ontario and...

Data-driven integration of genome-scale regulatory and metabolic network models

Science.gov (United States)

Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

2015-01-01

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

The global transmission network of HIV-1.

Science.gov (United States)

Wertheim, Joel O; Leigh Brown, Andrew J; Hepler, N Lance; Mehta, Sanjay R; Richman, Douglas D; Smith, Davey M; Kosakovsky Pond, Sergei L

2014-01-15

Human immunodeficiency virus type 1 (HIV-1) is pandemic, but its contemporary global transmission network has not been characterized. A better understanding of the properties and dynamics of this network is essential for surveillance, prevention, and eventual eradication of HIV. Here, we apply a simple and computationally efficient network-based approach to all publicly available HIV polymerase sequences in the global database, revealing a contemporary picture of the spread of HIV-1 within and between countries. This approach automatically recovered well-characterized transmission clusters and extended other clusters thought to be contained within a single country across international borders. In addition, previously undescribed transmission clusters were discovered. Together, these clusters represent all known modes of HIV transmission. The extent of international linkage revealed by our comprehensive approach demonstrates the need to consider the global diversity of HIV, even when describing local epidemics. Finally, the speed of this method allows for near-real-time surveillance of the pandemic's progression.

Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model

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Ingkasuwan Papapit

2012-08-01

Full Text Available Abstract Background Starch serves as a temporal storage of carbohydrates in plant leaves during day/night cycles. To study transcriptional regulatory modules of this dynamic metabolic process, we conducted gene regulation network analysis based on small-sample inference of graphical Gaussian model (GGM. Results Time-series significant analysis was applied for Arabidopsis leaf transcriptome data to obtain a set of genes that are highly regulated under a diurnal cycle. A total of 1,480 diurnally regulated genes included 21 starch metabolic enzymes, 6 clock-associated genes, and 106 transcription factors (TF. A starch-clock-TF gene regulation network comprising 117 nodes and 266 edges was constructed by GGM from these 133 significant genes that are potentially related to the diurnal control of starch metabolism. From this network, we found that β-amylase 3 (b-amy3: At4g17090, which participates in starch degradation in chloroplast, is the most frequently connected gene (a hub gene. The robustness of gene-to-gene regulatory network was further analyzed by TF binding site prediction and by evaluating global co-expression of TFs and target starch metabolic enzymes. As a result, two TFs, indeterminate domain 5 (AtIDD5: At2g02070 and constans-like (COL: At2g21320, were identified as positive regulators of starch synthase 4 (SS4: At4g18240. The inference model of AtIDD5-dependent positive regulation of SS4 gene expression was experimentally supported by decreased SS4 mRNA accumulation in Atidd5 mutant plants during the light period of both short and long day conditions. COL was also shown to positively control SS4 mRNA accumulation. Furthermore, the knockout of AtIDD5 and COL led to deformation of chloroplast and its contained starch granules. This deformity also affected the number of starch granules per chloroplast, which increased significantly in both knockout mutant lines. Conclusions In this study, we utilized a systematic approach of microarray

Do all roads lead to Rome? A comparison of brain networks derived from inter-subject volumetric and metabolic covariance and moment-to-moment hemodynamic correlations in old individuals.

Science.gov (United States)

Di, Xin; Gohel, Suril; Thielcke, Andre; Wehrl, Hans F; Biswal, Bharat B

2017-11-01

Relationships between spatially remote brain regions in human have typically been estimated by moment-to-moment correlations of blood-oxygen-level dependent signals in resting-state using functional MRI (fMRI). Recently, studies using subject-to-subject covariance of anatomical volumes, cortical thickness, and metabolic activity are becoming increasingly popular. However, question remains on whether these measures reflect the same inter-region connectivity and brain network organizations. In the current study, we systematically analyzed inter-subject volumetric covariance from anatomical MRI images, metabolic covariance from fluorodeoxyglucose positron emission tomography images from 193 healthy subjects, and resting-state moment-to-moment correlations from fMRI images of a subset of 44 subjects. The correlation matrices calculated from the three methods were found to be minimally correlated, with higher correlation in the range of 0.31, as well as limited proportion of overlapping connections. The volumetric network showed the highest global efficiency and lowest mean clustering coefficient, leaning toward random-like network, while the metabolic and resting-state networks conveyed properties more resembling small-world networks. Community structures of the volumetric and metabolic networks did not reflect known functional organizations, which could be observed in resting-state network. The current results suggested that inter-subject volumetric and metabolic covariance do not necessarily reflect the inter-regional relationships and network organizations as resting-state correlations, thus calling for cautions on interpreting results of inter-subject covariance networks.

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

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Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

Network analysis of metabolic enzyme evolution in Escherichia coli

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Kraulis Per

2004-02-01

Full Text Available Abstract Background The two most common models for the evolution of metabolism are the patchwork evolution model, where enzymes are thought to diverge from broad to narrow substrate specificity, and the retrograde evolution model, according to which enzymes evolve in response to substrate depletion. Analysis of the distribution of homologous enzyme pairs in the metabolic network can shed light on the respective importance of the two models. We here investigate the evolution of the metabolism in E. coli viewed as a single network using EcoCyc. Results Sequence comparison between all enzyme pairs was performed and the minimal path length (MPL between all enzyme pairs was determined. We find a strong over-representation of homologous enzymes at MPL 1. We show that the functionally similar and functionally undetermined enzyme pairs are responsible for most of the over-representation of homologous enzyme pairs at MPL 1. Conclusions The retrograde evolution model predicts that homologous enzymes pairs are at short metabolic distances from each other. In general agreement with previous studies we find that homologous enzymes occur close to each other in the network more often than expected by chance, which lends some support to the retrograde evolution model. However, we show that the homologous enzyme pairs which may have evolved through retrograde evolution, namely the pairs that are functionally dissimilar, show a weaker over-representation at MPL 1 than the functionally similar enzyme pairs. Our study indicates that, while the retrograde evolution model may have played a small part, the patchwork evolution model is the predominant process of metabolic enzyme evolution.

Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling

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Mahadevan Radhakrishnan

2010-05-01

Full Text Available Abstract Background Geobacter sulfurreducens is a member of the Geobacter species, which are capable of oxidation of organic waste coupled to the reduction of heavy metals and electrode with applications in bioremediation and bioenergy generation. While the metabolism of this organism has been studied through the development of a stoichiometry based genome-scale metabolic model, the associated regulatory network has not yet been well studied. In this manuscript, we report on the implementation of a thermodynamics based metabolic flux model for Geobacter sulfurreducens. We use this updated model to identify reactions that are subject to regulatory control in the metabolic network of G. sulfurreducens using thermodynamic variability analysis. Findings As a first step, we have validated the regulatory sites and bottleneck reactions predicted by the thermodynamic flux analysis in E. coli by evaluating the expression ranges of the corresponding genes. We then identified ten reactions in the metabolic network of G. sulfurreducens that are predicted to be candidates for regulation. We then compared the free energy ranges for these reactions with the corresponding gene expression fold changes under conditions of different environmental and genetic perturbations and show that the model predictions of regulation are consistent with data. In addition, we also identify reactions that operate close to equilibrium and show that the experimentally determined exchange coefficient (a measure of reversibility is significant for these reactions. Conclusions Application of the thermodynamic constraints resulted in identification of potential bottleneck reactions not only from the central metabolism but also from the nucleotide and amino acid subsystems, thereby showing the highly coupled nature of the thermodynamic constraints. In addition, thermodynamic variability analysis serves as a valuable tool in estimating the ranges of ΔrG' of every reaction in the model

Towards a global quantum network

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Simon, Christoph

2017-11-01

The creation of a global quantum network is now a realistic proposition thanks to developments in satellite and fibre links and quantum memory. Applications will range from secure communication and fundamental physics experiments to a future quantum internet.

Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders.

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Meng, Qingying; Ying, Zhe; Noble, Emily; Zhao, Yuqi; Agrawal, Rahul; Mikhail, Andrew; Zhuang, Yumei; Tyagi, Ethika; Zhang, Qing; Lee, Jae-Hyung; Morselli, Marco; Orozco, Luz; Guo, Weilong; Kilts, Tina M; Zhu, Jun; Zhang, Bin; Pellegrini, Matteo; Xiao, Xinshu; Young, Marian F; Gomez-Pinilla, Fernando; Yang, Xia

2016-05-01

Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient-host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Multinational Firms and the Management of Global Networks

DEFF Research Database (Denmark)

De Marchi, Valentina; Maria, Eleonora Di; Ponte, Stefano

2014-01-01

This paper aims at enriching the literature on international business (IB) studies to include insights from Global Value Chain (GVC) analysis to better explain how MNCs can orchestrate a global network organization. A first important contribution of the GVC literature is that it shifts the focus...... from single firms to their value chains, providing instruments to study how activities are split and organized among different firms at the industry level, and how MNCs can implement different governing mechanisms within a network-based setting. The GVC literature also highlights that retailers (as...... can manage their network relationships in a global scenario. Finally, through their focus on upgrading, GVC studies suggest that knowledge flows and innovation dynamics taking place within value chains are as important as those taking place within the MNC’s organizational border. We conclude...

Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

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Sriram Chandrasekaran

2017-12-01

Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

Development and analysis of an in vivo-compatible metabolic network of Mycobacterium tuberculosis

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Reifman Jaques

2010-11-01

Full Text Available Abstract Background During infection, Mycobacterium tuberculosis confronts a generally hostile and nutrient-poor in vivo host environment. Existing models and analyses of M. tuberculosis metabolic networks are able to reproduce experimentally measured cellular growth rates and identify genes required for growth in a range of different in vitro media. However, these models, under in vitro conditions, do not provide an adequate description of the metabolic processes required by the pathogen to infect and persist in a host. Results To better account for the metabolic activity of M. tuberculosis in the host environment, we developed a set of procedures to systematically modify an existing in vitro metabolic network by enhancing the agreement between calculated and in vivo-measured gene essentiality data. After our modifications, the new in vivo network contained 663 genes, 838 metabolites, and 1,049 reactions and had a significantly increased sensitivity (0.81 in predicted gene essentiality than the in vitro network (0.31. We verified the modifications generated from the purely computational analysis through a review of the literature and found, for example, that, as the analysis suggested, lipids are used as the main source for carbon metabolism and oxygen must be available for the pathogen under in vivo conditions. Moreover, we used the developed in vivo network to predict the effects of double-gene deletions on M. tuberculosis growth in the host environment, explore metabolic adaptations to life in an acidic environment, highlight the importance of different enzymes in the tricarboxylic acid-cycle under different limiting nutrient conditions, investigate the effects of inhibiting multiple reactions, and look at the importance of both aerobic and anaerobic cellular respiration during infection. Conclusions The network modifications we implemented suggest a distinctive set of metabolic conditions and requirements faced by M. tuberculosis during

IMPLICATIONS OF SOCIAL RESPONSIBILITY DISCLOSURE ON GLOBAL PRODUCTION NETWORK

OpenAIRE

Le Bo; Dan Shen; Jin Jun Bo

2014-01-01

This paper aims to discuss effectiveness of social responsibility disclosure in promoting global production network. Through a critical review on the theoretical development from supply chain to global production network, the global supply chain management of Apple Inc., as a case, is investigated, with focus on corporate and NGOs’ social disclosure on the environmental and labor rights' issues of its suppliers in China. The paper concludes that effectiveness of corporate social disclosure on...

Computational solution to automatically map metabolite libraries in the context of genome scale metabolic networks

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Benjamin eMerlet

2016-02-01

Full Text Available This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc and flat file formats (SBML and Matlab files. We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics and Glasgow Polyomics on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks.In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks.In order to achieve this goal we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

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Richard A Notebaart

2008-01-01

Full Text Available To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools.

Data-driven integration of genome-scale regulatory and metabolic network models

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Saheed eImam

2015-05-01

Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

Expanded flux variability analysis on metabolic network of Escherichia coli

Institute of Scientific and Technical Information of China (English)

CHEN Tong; XIE ZhengWei; OUYANG Qi

2009-01-01

Flux balance analysis,based on the mass conservation law in a cellular organism,has been extensively employed to study the interplay between structures and functions of cellular metabolic networks.Consequently,the phenotypes of the metabolism can be well elucidated.In this paper,we introduce the Expanded Flux Variability Analysis (EFVA) to characterize the intrinsic nature of metabolic reactions,such as flexibility,modularity and essentiality,by exploring the trend of the range,the maximum and the minimum flux of reactions.We took the metabolic network of Escherichia coli as an example and analyzed the variability of reaction fluxes under different growth rate constraints.The average variability of all reactions decreases dramatically when the growth rate increases.Consider the noise effect on the metabolic system,we thus argue that the microorganism may practically grow under a suboptimal state.Besides,under the EFVA framework,the reactions are easily to be grouped into catabolic and anabolic groups.And the anabolic groups can be further assigned to specific biomass constitute.We also discovered the growth rate dependent essentiality of reactions.

Validation of a metabolic network for Saccharomyces cerevisiae using mixed substrate studies.

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Vanrolleghem, P A; de Jong-Gubbels, P; van Gulik, W M; Pronk, J T; van Dijken, J P; Heijnen, S

1996-01-01

Setting up a metabolic network model for respiratory growth of Saccharomyces cerevisiae requires the estimation of only two (energetic) stoichiometric parameters: (1) the operational PO ratio and (2) a growth-related maintenance factor k. It is shown, both theoretically and practically, how chemostat cultivations with different mixtures of two substrates allow unique values to be given to these unknowns of the proposed metabolic model. For the yeast and model considered, an effective PO ratio of 1.09 mol of ATP/mol of O (95% confidence interval 1.07-1.11) and a k factor of 0.415 mol of ATP/C-mol of biomass (0.385-0.445) were obtained from biomass substrate yield data on glucose/ethanol mixtures. Symbolic manipulation software proved very valuable in this study as it supported the proof of theoretical identifiability and significantly reduced the necessary computations for parameter estimation. In the transition from 100% glucose to 100% ethanol in the feed, four metabolic regimes occur. Switching between these regimes is determined by cessation of an irreversible reaction and initiation of an alternative reaction. Metabolic network predictions of these metabolic switches compared well with activity measurements of key enzymes. As a second validation of the network, the biomass yield of S. cerevisiae on acetate was also compared to the network prediction. An excellent agreement was found for a network in which acetate transport was modeled with a proton symport, while passive diffusion of acetate gave significantly higher yield predictions.

Running a network on a shoestring: the Global Invasive Species Information Network

Science.gov (United States)

Jarnevich, Catherine S.; Simpson, Annie; Graham, James J; Newman, Gregory J.; Bargeron, Chuck T.

2015-01-01

The Global Invasive Species Information Network (GISIN) was conceptualized in 2004 to aggregate and disseminate invasive species data in a standardized way. A decade later the GISIN community has implemented a data portal and three of six GISIN data aggregation models in the GISIN data exchange Protocol, including invasive species status information, resource URLs, and occurrence data. The portal is based on a protocol developed by representatives from 15 countries and 27 organizations of the global invasive species information management community. The GISIN has 19 data providers sharing 34,343 species status records, 1,693,073 occurrences, and 15,601 resource URLs. While the GISIN's goal is to be global, much of its data and funding are provided by the United States. Several initiatives use the GISIN as their information backbone, such as the Great Lakes Early Detection Network (GLEDN) and the North American Invasive Species Network (NAISN). Here we share several success stories and organizational challenges that remain.

Dead end metabolites--defining the known unknowns of the E. coli metabolic network.

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Amanda Mackie

Full Text Available The EcoCyc database is an online scientific database which provides an integrated view of the metabolic and regulatory network of the bacterium Escherichia coli K-12 and facilitates computational exploration of this important model organism. We have analysed the occurrence of dead end metabolites within the database--these are metabolites which lack the requisite reactions (either metabolic or transport that would account for their production or consumption within the metabolic network. 127 dead end metabolites were identified from the 995 compounds that are contained within the EcoCyc metabolic network. Their presence reflects either a deficit in our representation of the network or in our knowledge of E. coli metabolism. Extensive literature searches resulted in the addition of 38 transport reactions and 3 metabolic reactions to the database and led to an improved representation of the pathway for Vitamin B12 salvage. 39 dead end metabolites were identified as components of reactions that are not physiologically relevant to E. coli K-12--these reactions are properties of purified enzymes in vitro that would not be expected to occur in vivo. Our analysis led to improvements in the software that underpins the database and to the program that finds dead end metabolites within EcoCyc. The remaining dead end metabolites in the EcoCyc database likely represent deficiencies in our knowledge of E. coli metabolism.

Four Challenges That Global Health Networks Face

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Jeremy Shiffman

2017-04-01

Full Text Available Global health networks, webs of individuals and organizations with a shared concern for a particular condition, have proliferated over the past quarter century. They differ in their effectiveness, a factor that may help explain why resource allocations vary across health conditions and do not correspond closely with disease burden. Drawing on findings from recently concluded studies of eight global health networks—addressing alcohol harm, early childhood development (ECD, maternal mortality, neonatal mortality, pneumonia, surgically-treatable conditions, tobacco use, and tuberculosis—I identify four challenges that networks face in generating attention and resources for the conditions that concern them. The first is problem definition: generating consensus on what the problem is and how it should be addressed. The second is positioning: portraying the issue in ways that inspire external audiences to act. The third is coalition-building: forging alliances with these external actors, particularly ones outside the health sector. The fourth is governance: establishing institutions to facilitate collective action. Research indicates that global health networks that effectively tackle these challenges are more likely to garner support to address the conditions that concern them. In addition to the effectiveness of networks, I also consider their legitimacy, identifying reasons both to affirm and to question their right to exert power.

Network-level architecture and the evolutionary potential of underground metabolism.

Science.gov (United States)

Notebaart, Richard A; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs

2014-08-12

A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

Enumeration of smallest intervention strategies in genome-scale metabolic networks.

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Axel von Kamp

2014-01-01

Full Text Available One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions in genome-scale metabolic network models. For this we combine two approaches, namely (i the mapping of MCSs to EMs in a dual network, and (ii a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth than reported previously. The strength of the presented approach is that smallest intervention strategies can be

Integration of Plant Metabolomics Data with Metabolic Networks: Progresses and Challenges.

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Töpfer, Nadine; Seaver, Samuel M D; Aharoni, Asaph

2018-01-01

In the last decade, plant genome-scale modeling has developed rapidly and modeling efforts have advanced from representing metabolic behavior of plant heterotrophic cell suspensions to studying the complex interplay of cell types, tissues, and organs. A crucial driving force for such developments is the availability and integration of "omics" data (e.g., transcriptomics, proteomics, and metabolomics) which enable the reconstruction, extraction, and application of context-specific metabolic networks. In this chapter, we demonstrate a workflow to integrate gas chromatography coupled to mass spectrometry (GC-MS)-based metabolomics data of tomato fruit pericarp (flesh) tissue, at five developmental stages, with a genome-scale reconstruction of tomato metabolism. This method allows for the extraction of context-specific networks reflecting changing activities of metabolic pathways throughout fruit development and maturation.

Language Choice & Global Learning Networks

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Dennis Sayers

1995-05-01

Full Text Available How can other languages be used in conjunction with English to further intercultural and multilingual learning when teachers and students participate in computer-based global learning networks? Two portraits are presented of multilingual activities in the Orillas and I*EARN learning networks, and are discussed as examples of the principal modalities of communication employed in networking projects between distant classes. Next, an important historical precedent --the social controversy which accompanied the introduction of telephone technology at the end of the last century-- is examined in terms of its implications for language choice in contemporary classroom telecomputing projects. Finally, recommendations are offered to guide decision making concerning the role of language choice in promoting collaborative critical inquiry.

Global operations networks in motion: Managing configurations and capabilities

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Wæhrens, Brian Vejrum; Jørgensen, Claus

2010-01-01

In the past, the ‘Made in the World’ label, although capturing what may lie ahead, seemed awkward and futuristic. Today, it has become a reality. An ample array of global products are built up of numerous components and modules manufactured by global networks of differentiated partners rather than...... within the boundaries of one national entity. The purpose of this paper is to contribute to bridging the empirical gap in the area of global operations networks and provide insights into how they change over time. The paper is based on the cases of three Danish companies and their global operations...

Metabolic network modeling of microbial interactions in natural and engineered environmental systems

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Octavio ePerez-Garcia

2016-05-01

Full Text Available We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA, experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e. i lumped networks, ii compartment per guild networks, iii bi-level optimization simulations and iv dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial

Evolution of the global virtual water trade network.

Science.gov (United States)

Dalin, Carole; Konar, Megan; Hanasaki, Naota; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2012-04-17

Global freshwater resources are under increasing pressure from economic development, population growth, and climate change. The international trade of water-intensive products (e.g., agricultural commodities) or virtual water trade has been suggested as a way to save water globally. We focus on the virtual water trade network associated with international food trade built with annual trade data and annual modeled virtual water content. The evolution of this network from 1986 to 2007 is analyzed and linked to trade policies, socioeconomic circumstances, and agricultural efficiency. We find that the number of trade connections and the volume of water associated with global food trade more than doubled in 22 years. Despite this growth, constant organizational features were observed in the network. However, both regional and national virtual water trade patterns significantly changed. Indeed, Asia increased its virtual water imports by more than 170%, switching from North America to South America as its main partner, whereas North America oriented to a growing intraregional trade. A dramatic rise in China's virtual water imports is associated with its increased soy imports after a domestic policy shift in 2000. Significantly, this shift has led the global soy market to save water on a global scale, but it also relies on expanding soy production in Brazil, which contributes to deforestation in the Amazon. We find that the international food trade has led to enhanced savings in global water resources over time, indicating its growing efficiency in terms of global water use.

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

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Brian R Granger

2016-04-01

Full Text Available The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space, a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

Science.gov (United States)

Granger, Brian R; Chang, Yi-Chien; Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

2016-04-01

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

Characterization of the Usage of the Serine Metabolic Network in Human Cancer

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Mahya Mehrmohamadi

2014-11-01

Full Text Available The serine, glycine, one-carbon (SGOC metabolic network is implicated in cancer pathogenesis, but its general functions are unknown. We carried out a computational reconstruction of the SGOC network and then characterized its expression across thousands of cancer tissues. Pathways including methylation and redox metabolism exhibited heterogeneous expression indicating a strong context dependency of their usage in tumors. From an analysis of coexpression, simultaneous up- or downregulation of nucleotide synthesis, NADPH, and glutathione synthesis was found to be a common occurrence in all cancers. Finally, we developed a method to trace the metabolic fate of serine using stable isotopes, high-resolution mass spectrometry, and a mathematical model. Although the expression of single genes didn’t appear indicative of flux, the collective expression of several genes in a given pathway allowed for successful flux prediction. Altogether, these findings identify expansive and heterogeneous functions for the SGOC metabolic network in human cancer.

Computing autocatalytic sets to unravel inconsistencies in metabolic network reconstructions

DEFF Research Database (Denmark)

Schmidt, R.; Waschina, S.; Boettger-Schmidt, D.

2015-01-01

, the method we report represents a powerful tool to identify inconsistencies in large-scale metabolic networks. AVAILABILITY AND IMPLEMENTATION: The method is available as source code on http://users.minet.uni-jena.de/ approximately m3kach/ASBIG/ASBIG.zip. CONTACT: christoph.kaleta@uni-jena.de SUPPLEMENTARY...... by inherent inconsistencies and gaps. RESULTS: Here we present a novel method to validate metabolic network reconstructions based on the concept of autocatalytic sets. Autocatalytic sets correspond to collections of metabolites that, besides enzymes and a growth medium, are required to produce all biomass...... components in a metabolic model. These autocatalytic sets are well-conserved across all domains of life, and their identification in specific genome-scale reconstructions allows us to draw conclusions about potential inconsistencies in these models. The method is capable of detecting inconsistencies, which...

A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

NARCIS (Netherlands)

Herrgård, Markus J.; Swainston, Neil; Dobson, Paul; Dunn, Warwick B.; Arga, K. Yalçin; Arvas, Mikko; Blüthgen, Nils; Borger, Simon; Costenoble, Roeland; Heinemann, Matthias; Hucka, Michael; Novère, Nicolas Le; Li, Peter; Liebermeister, Wolfram; Mo, Monica L.; Oliveira, Ana Paula; Petranovic, Dina; Pettifer, Stephen; Simeonidis, Evangelos; Smallbone, Kieran; Spasić, Irena; Weichart, Dieter; Brent, Roger; Broomhead, David S.; Westerhoff, Hans V.; Kırdar, Betül; Penttilä, Merja; Klipp, Edda; Palsson, Bernhard Ø.; Sauer, Uwe; Oliver, Stephen G.; Mendes, Pedro; Nielsen, Jens; Kell, Douglas B.

2008-01-01

Genomic data allow the large-scale manual or semi-automated assembly of metabolic network reconstructions, which provide highly curated organism-specific knowledge bases. Although several genome-scale network reconstructions describe Saccharomyces cerevisiae metabolism, they differ in scope and

Dynamic brain glucose metabolism identifies anti-correlated cortical-cerebellar networks at rest.

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Tomasi, Dardo G; Shokri-Kojori, Ehsan; Wiers, Corinde E; Kim, Sunny W; Demiral, Şukru B; Cabrera, Elizabeth A; Lindgren, Elsa; Miller, Gregg; Wang, Gene-Jack; Volkow, Nora D

2017-12-01

It remains unclear whether resting state functional magnetic resonance imaging (rfMRI) networks are associated with underlying synchrony in energy demand, as measured by dynamic 2-deoxy-2-[ 18 F]fluoroglucose (FDG) positron emission tomography (PET). We measured absolute glucose metabolism, temporal metabolic connectivity (t-MC) and rfMRI patterns in 53 healthy participants at rest. Twenty-two rfMRI networks emerged from group independent component analysis (gICA). In contrast, only two anti-correlated t-MC emerged from FDG-PET time series using gICA or seed-voxel correlations; one included frontal, parietal and temporal cortices, the other included the cerebellum and medial temporal regions. Whereas cerebellum, thalamus, globus pallidus and calcarine cortex arose as the strongest t-MC hubs, the precuneus and visual cortex arose as the strongest rfMRI hubs. The strength of the t-MC linearly increased with the metabolic rate of glucose suggesting that t-MC measures are strongly associated with the energy demand of the brain tissue, and could reflect regional differences in glucose metabolism, counterbalanced metabolic network demand, and/or differential time-varying delivery of FDG. The mismatch between metabolic and functional connectivity patterns computed as a function of time could reflect differences in the temporal characteristics of glucose metabolism as measured with PET-FDG and brain activation as measured with rfMRI.

Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions

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Orth Jeffrey D

2012-05-01

Full Text Available Abstract Background The iJO1366 reconstruction of the metabolic network of Escherichia coli is one of the most complete and accurate metabolic reconstructions available for any organism. Still, because our knowledge of even well-studied model organisms such as this one is incomplete, this network reconstruction contains gaps and possible errors. There are a total of 208 blocked metabolites in iJO1366, representing gaps in the network. Results A new model improvement workflow was developed to compare model based phenotypic predictions to experimental data to fill gaps and correct errors. A Keio Collection based dataset of E. coli gene essentiality was obtained from literature data and compared to model predictions. The SMILEY algorithm was then used to predict the most likely missing reactions in the reconstructed network, adding reactions from a KEGG based universal set of metabolic reactions. The feasibility of these putative reactions was determined by comparing updated versions of the model to the experimental dataset, and genes were predicted for the most feasible reactions. Conclusions Numerous improvements to the iJO1366 metabolic reconstruction were suggested by these analyses. Experiments were performed to verify several computational predictions, including a new mechanism for growth on myo-inositol. The other predictions made in this study should be experimentally verifiable by similar means. Validating all of the predictions made here represents a substantial but important undertaking.

Random sampling of elementary flux modes in large-scale metabolic networks.

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Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

2012-09-15

The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

Global asymptotic stability of delayed Cohen-Grossberg neural networks

International Nuclear Information System (INIS)

Wu Wei; Cui Baotong; Huang Min

2007-01-01

In this letter, the global asymptotic stability of a class of Cohen-Grossberg neural networks with time-varying delays is discussed. A new set of sufficient conditions for the neural networks are proposed to guarantee the global asymptotic convergence. Our criteria represent an extension of the existing results in literatures. An example is also presented to compare our results with the previous results

A state of the art of metabolic networks of unicellular microalgae and cyanobacteria for biofuel production.

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Baroukh, Caroline; Muñoz-Tamayo, Rafael; Steyer, Jean-Philippe; Bernard, Olivier

2015-07-01

The most promising and yet challenging application of microalgae and cyanobacteria is the production of renewable energy: biodiesel from microalgae triacylglycerols and bioethanol from cyanobacteria carbohydrates. A thorough understanding of microalgal and cyanobacterial metabolism is necessary to master and optimize biofuel production yields. To this end, systems biology and metabolic modeling have proven to be very efficient tools if supported by an accurate knowledge of the metabolic network. However, unlike heterotrophic microorganisms that utilize the same substrate for energy and as carbon source, microalgae and cyanobacteria require light for energy and inorganic carbon (CO2 or bicarbonate) as carbon source. This double specificity, together with the complex mechanisms of light capture, makes the representation of metabolic network nonstandard. Here, we review the existing metabolic networks of photoautotrophic microalgae and cyanobacteria. We highlight how these networks have been useful for gaining insight on photoautotrophic metabolism. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics.

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Maldonado, Elaina M; Leoncikas, Vytautas; Fisher, Ciarán P; Moore, J Bernadette; Plant, Nick J; Kierzek, Andrzej M

2017-11-01

The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

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Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

2016-01-01

This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

Global value chains: Building blocks and network dynamics

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Tsekeris, Theodore

2017-12-01

The paper employs measures and tools from complex network analysis to enhance the understanding and interpretation of structural characteristics pertaining to the Global Value Chains (GVCs) during the period 1995-2011. The analysis involves the country, sector and country-sector value chain networks to identify main drivers of structural change. The results indicate significant intertemporal changes, mirroring the increased globalization in terms of network size, strength and connectivity. They also demonstrate higher clustering and increased concentration of the most influential countries and country-sectors relative to all others in the GVC network, with the geographical dimension to prevail over the sectoral dimension in the formation of value chains. The regionalization and less hierarchical organization drive country-sector production sharing, while the sectoral value chain network has become more integrated and more competitive over time. The findings suggest that the impact of country-sector policies and/or shocks may vary with the own-group and network-wide influence of each country, take place in multiple geographical scales, as GVCs have a block structure, and involve time dynamics.

Hegemonic transitions and global shifts in social metabolism: Implications for resource-rich countries. Introduction to the special section

NARCIS (Netherlands)

Muradian Sarache, R.P.; Walter, M.; Martinez-Alier, J.

2012-01-01

This introductory paper to the special section of Global Environmental Change entitled "Global transformations, social metabolism and the dynamics of socio-environmental conflicts" argues that the emergence of new global economic centers is inducing a major expansion in the global social metabolism

The complex network of global cargo ship movements.

Science.gov (United States)

Kaluza, Pablo; Kölzsch, Andrea; Gastner, Michael T; Blasius, Bernd

2010-07-06

Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.

Global robust stability of delayed recurrent neural networks

International Nuclear Information System (INIS)

Cao Jinde; Huang Deshuang; Qu Yuzhong

2005-01-01

This paper is concerned with the global robust stability of a class of delayed interval recurrent neural networks which contain time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. A new sufficient condition is presented for the existence, uniqueness, and global robust stability of equilibria for interval neural networks with time delays by constructing Lyapunov functional and using matrix-norm inequality. An error is corrected in an earlier publication, and an example is given to show the effectiveness of the obtained results

Abnormal metabolic brain networks in Parkinson's disease from blackboard to bedside.

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Tang, Chris C; Eidelberg, David

2010-01-01

Metabolic imaging in the rest state has provided valuable information concerning the abnormalities of regional brain function that underlie idiopathic Parkinson's disease (PD). Moreover, network modeling procedures, such as spatial covariance analysis, have further allowed for the quantification of these changes at the systems level. In recent years, we have utilized this strategy to identify and validate three discrete metabolic networks in PD associated with the motor and cognitive manifestations of the disease. In this chapter, we will review and compare the specific functional topographies underlying parkinsonian akinesia/rigidity, tremor, and cognitive disturbance. While network activity progressed over time, the rate of change for each pattern was distinctive and paralleled the development of the corresponding clinical symptoms in early-stage patients. This approach is already showing great promise in identifying individuals with prodromal manifestations of PD and in assessing the rate of progression before clinical onset. Network modulation was found to correlate with the clinical effects of dopaminergic treatment and surgical interventions, such as subthalamic nucleus (STN) deep brain stimulation (DBS) and gene therapy. Abnormal metabolic networks have also been identified for atypical parkinsonian syndromes, such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Using multiple disease-related networks for PD, MSA, and PSP, we have developed a novel, fully automated algorithm for accurate classification at the single-patient level, even at early disease stages. Copyright © 2010 Elsevier B.V. All rights reserved.

Links that speak: the global language network and its association with global fame.

Science.gov (United States)

Ronen, Shahar; Gonçalves, Bruno; Hu, Kevin Z; Vespignani, Alessandro; Pinker, Steven; Hidalgo, César A

2014-12-30

Languages vary enormously in global importance because of historical, demographic, political, and technological forces. However, beyond simple measures of population and economic power, there has been no rigorous quantitative way to define the global influence of languages. Here we use the structure of the networks connecting multilingual speakers and translated texts, as expressed in book translations, multiple language editions of Wikipedia, and Twitter, to provide a concept of language importance that goes beyond simple economic or demographic measures. We find that the structure of these three global language networks (GLNs) is centered on English as a global hub and around a handful of intermediate hub languages, which include Spanish, German, French, Russian, Portuguese, and Chinese. We validate the measure of a language's centrality in the three GLNs by showing that it exhibits a strong correlation with two independent measures of the number of famous people born in the countries associated with that language. These results suggest that the position of a language in the GLN contributes to the visibility of its speakers and the global popularity of the cultural content they produce.

Discovery of Boolean metabolic networks: integer linear programming based approach.

Science.gov (United States)

Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing

2018-04-11

Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".

Identification of global oil trade patterns: An empirical research based on complex network theory

International Nuclear Information System (INIS)

Ji, Qiang; Zhang, Hai-Ying; Fan, Ying

2014-01-01

Highlights: • A global oil trade core network is analyzed using complex network theory. • The global oil export core network displays a scale-free behaviour. • The current global oil trade network can be divided into three trading blocs. • The global oil trade network presents a ‘robust and yet fragile’ characteristic. - Abstract: The Global oil trade pattern becomes increasingly complex, which has become one of the most important factors affecting every country’s energy strategy and economic development. In this paper, a global oil trade core network is constructed to analyze the overall features, regional characteristics and stability of the oil trade using complex network theory. The results indicate that the global oil export core network displays a scale-free behaviour, in which the trade position of nodes presents obvious heterogeneity and the ‘hub nodes’ play a ‘bridge’ role in the formation process of the trade network. The current global oil trade network can be divided into three trading blocs, including the ‘South America-West Africa-North America’ trading bloc, the ‘Middle East–Asian–Pacific region’ trading bloc, and ‘the former Soviet Union–North Africa–Europe’ trading bloc. Geopolitics and diplomatic relations are the two main reasons for this regional oil trade structure. Moreover, the global oil trade network presents a ‘robust but yet fragile’ characteristic, and the impacts of trade interruption always tend to spread throughout the whole network even if the occurrence of export disruptions is localised

Alignment of global supply networks based on strategic groups of supply chains

Directory of Open Access Journals (Sweden)

Nikos G. Moraitakis

2017-09-01

Full Text Available Background: From a supply chain perspective, often big differences exist between global raw material suppliers’ approaches to supply their respective local markets. The progressing complexity of large centrally managed global supply networks and their often-unknown upstream ramifications increase the likelihood of undetected bottlenecks and inefficiencies. It is therefore necessary to develop an approach to strategically master the upstream complexity of such networks from a holistic supply chain perspective in order to align regional competitive priorities and supply chain structures. The objective of this research is hence to develop an approach for the supply-chain-based alignment of complex global supply networks. Method: We review existing literature from the fields of supply chain and network management, strategic sourcing, and strategic management. Based on the literature review and theoretical and practical considerations we deduce a conceptual approach to consider upstream supply chain structures in supply network alignment initiatives. Results: On the basis of these considerations and current empirical literature we transfer strategic group theory to the supply network management context. The proposed approach introduces strategic groups of supply chains as a segmentation criterion for complex global supply networks which enables the network-wide alignment of competitive priorities. Conclusion: Supply-chain-based segmentation of global supply network structures can effectively reduce the complexity, firms face when aiming to strategically align their supply chains on a holistic level. The results of this research are applicable for certain types of global supply networks and can be used for network alignment and strategy development. The approach can furthermore generate insights useable for negotiation support with suppliers.

Association of structural global brain network properties with intelligence in normal aging.

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Florian U Fischer

Full Text Available Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60-85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience.

Association of Structural Global Brain Network Properties with Intelligence in Normal Aging

Science.gov (United States)

Fischer, Florian U.; Wolf, Dominik; Scheurich, Armin; Fellgiebel, Andreas

2014-01-01

Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60–85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R) and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient) were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience. PMID:24465994

Identifying all moiety conservation laws in genome-scale metabolic networks.

Science.gov (United States)

De Martino, Andrea; De Martino, Daniele; Mulet, Roberto; Pagnani, Andrea

2014-01-01

The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

Identifying all moiety conservation laws in genome-scale metabolic networks.

Directory of Open Access Journals (Sweden)

Andrea De Martino

Full Text Available The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

Improving the description of metabolic networks: the TCA cycle as example

NARCIS (Netherlands)

Stobbe, Miranda D.; Houten, Sander M.; van Kampen, Antoine H. C.; Wanders, Ronald J. A.; Moerland, Perry D.

2012-01-01

To collect the ever-increasing yet scattered knowledge on metabolism, multiple pathway databases like the Kyoto Encyclopedia of Genes and Genomes have been created. A complete and accurate description of the metabolic network for human and other organisms is essential to foster new biological

Networks in Cell Biology

Science.gov (United States)

Buchanan, Mark; Caldarelli, Guido; De Los Rios, Paolo; Rao, Francesco; Vendruscolo, Michele

2010-05-01

Introduction; 1. Network views of the cell Paolo De Los Rios and Michele Vendruscolo; 2. Transcriptional regulatory networks Sarath Chandra Janga and M. Madan Babu; 3. Transcription factors and gene regulatory networks Matteo Brilli, Elissa Calistri and Pietro Lió; 4. Experimental methods for protein interaction identification Peter Uetz, Björn Titz, Seesandra V. Rajagopala and Gerard Cagney; 5. Modeling protein interaction networks Francesco Rao; 6. Dynamics and evolution of metabolic networks Daniel Segré; 7. Hierarchical modularity in biological networks: the case of metabolic networks Erzsébet Ravasz Regan; 8. Signalling networks Gian Paolo Rossini; Appendix 1. Complex networks: from local to global properties D. Garlaschelli and G. Caldarelli; Appendix 2. Modelling the local structure of networks D. Garlaschelli and G. Caldarelli; Appendix 3. Higher-order topological properties S. Ahnert, T. Fink and G. Caldarelli; Appendix 4. Elementary mathematical concepts A. Gabrielli and G. Caldarelli; References.

Solidarity Action in Global Labor Networks. Four Cases of Workplace Organizing at Foreign Affiliates in the Global South

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Peter Wad

2014-03-01

Full Text Available Globalization transforms workforces of transnational corporation from predominantly home countrydominated workforces into foreign-dominated, multinational workforces. Thus, the national grounding of trade unions as the key form of labor organizing is challenged by new multinational compositions and cross-border relocations of corporate employment affecting working conditions of employees and trade unions in local places. We assume that economic globalization is characterized by expanding global corporate network of vertically and horizontally integrated (equity-based and disintegrated (nonequity-based value chains. We also assume that globalization can both impede and enable labor empowerment. Based on these premises the key question is, how can labor leverage effective power against management in global corporate networks? This question is split into two subquestions: a How can labor theoretically reorganize from national unions and industrial relations institutions into global labor networks that allow prolabor improvement in global workplaces? b How and why has labor in a globalized economy secured the core International Labor Organization (ILO international labor right to organize companies and conduct collective bargaining? The Global Labor Network perspective is adopted as an analytical framework. Empirically, a comparative case methodology is applied comprising four more or less successful industrial disputes where labor achieved the right to organize and undertake collective bargaining. The disputes took place in affiliated factories of foreign transnational corporations located in Malaysia, the Philippines, Sri Lanka, and Turkey. The conclusion is that the combination of global labor capabilities and global labor strategizing must generate strategic labor power that adequately matches the weaknesses of the counterpart’s global corporate network in order to achieve prolabor outcomes. The most efficient solidarity action was leveraged

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and Pareto filters.

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Carlos Pozo

Full Text Available Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and Pareto filters.

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Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Sorribas, Albert; Jiménez, Laureano

2012-01-01

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the

Global Prioritization of Disease Candidate Metabolites Based on a Multi-omics Composite Network

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Yao, Qianlan; Xu, Yanjun; Yang, Haixiu; Shang, Desi; Zhang, Chunlong; Zhang, Yunpeng; Sun, Zeguo; Shi, Xinrui; Feng, Li; Han, Junwei; Su, Fei; Li, Chunquan; Li, Xia

2015-01-01

The identification of disease-related metabolites is important for a better understanding of metabolite pathological processes in order to improve human medicine. Metabolites, which are the terminal products of cellular regulatory process, can be affected by multi-omic processes. In this work, we propose a powerful method, MetPriCNet, to predict and prioritize disease candidate metabolites based on integrated multi-omics information. MetPriCNet prioritized candidate metabolites based on their global distance similarity with seed nodes in a composite network, which integrated multi-omics information from the genome, phenome, metabolome and interactome. After performing cross-validation on 87 phenotypes with a total of 602 metabolites, MetPriCNet achieved a high AUC value of up to 0.918. We also assessed the performance of MetPriCNet on 18 disease classes and found that 4 disease classes achieved an AUC value over 0.95. Notably, MetPriCNet can also predict disease metabolites without known disease metabolite knowledge. Some new high-risk metabolites of breast cancer were predicted, although there is a lack of known disease metabolite information. A predicted disease metabolic landscape was constructed and analyzed based on the results of MetPriCNet for 87 phenotypes to help us understand the genetic and metabolic mechanism of disease from a global view. PMID:26598063

Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

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Bharat Manna

2017-10-01

Full Text Available Substantial rise in the global energy demand is one of the biggest challenges in this century. Environmental pollution due to rapid depletion of the fossil fuel resources and its alarming impact on the climate change and Global Warming have motivated researchers to look for non-petroleum-based sustainable, eco-friendly, renewable, low-cost energy alternatives, such as biofuel. Lignocellulosic biomass is one of the most promising bio-resources with huge potential to contribute to this worldwide energy demand. However, the complex organization of the Cellulose, Hemicellulose and Lignin in the Lignocellulosic biomass requires extensive pre-treatment and enzymatic hydrolysis followed by fermentation, raising overall production cost of biofuel. This encourages researchers to design cost-effective approaches for the production of second generation biofuels. The products from enzymatic hydrolysis of cellulose are mostly glucose monomer or cellobiose unit that are subjected to fermentation. Spirochaeta genus is a well-known group of obligate or facultative anaerobes, living primarily on carbohydrate metabolism. Spirochaeta cellobiosiphila sp. is a facultative anaerobe under this genus, which uses a variety of monosaccharides and disaccharides as energy sources. However, most rapid growth occurs on cellobiose and fermentation yields significant amount of ethanol, acetate, CO2, H2 and small amounts of formate. It is predicted to be promising microbial machinery for industrial fermentation processes for biofuel production. The metabolic pathways that govern cellobiose metabolism in Spirochaeta cellobiosiphila are yet to be explored. The function annotation of the genome sequence of Spirochaeta cellobiosiphila is in progress. In this work we aim to map all the metabolic activities for reconstruction of genome-scale metabolic model of Spirochaeta cellobiosiphila.

Optimality principles in the regulation of metabolic networks.

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Berkhout, Jan; Bruggeman, Frank J; Teusink, Bas

2012-08-29

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular "task" of the network-its function-should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02.

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Guo, Jing; Zhang, Hong; Wang, Cheng; Chang, Ji-Wei; Chen, Ling-Ling

2016-05-01

We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Global efficiency of structural networks mediates cognitive control in Mild Cognitive Impairment

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Rok Berlot

2016-12-01

Full Text Available Background: Cognitive control has been linked to both the microstructure of individual tracts and the structure of whole-brain networks, but their relative contributions in health and disease remain unclear. Objective: To determine the contribution of both localised white matter tract damage and disruption of global network architecture to cognitive control, in older age and Mild Cognitive Impairment (MCI.Methods: 25 patients with MCI and 20 age, sex and intelligence-matched healthy volunteers were investigated with 3 Tesla structural magnetic resonance imaging (MRI. Cognitive control and episodic memory were evaluated with established tests. Structural network graphs were constructed from diffusion MRI-based whole-brain tractography. Their global measures were calculated using graph theory. Regression models utilized both global network metrics and microstructure of specific connections, known to be critical for each domain, to predict cognitive scores. Results: Global efficiency and the mean clustering coefficient of networks were reduced in MCI. Cognitive control was associated with global network topology. Episodic memory, in contrast, correlated with individual temporal tracts only. Relationships between cognitive control and network topology were attenuated by addition of single tract measures to regression models, consistent with a partial mediation effect. The mediation effect was stronger in MCI than healthy volunteers, explaining 23-36% of the effect of cingulum microstructure on cognitive control performance. Network clustering was a significant mediator in the relationship between tract microstructure and cognitive control in both groups. Conclusions: The status of critical connections and large-scale network topology are both important for maintenance of cognitive control in MCI. Mediation via large-scale networks is more important in patients with MCI than healthy volunteers. This effect is domain-specific, and true for cognitive

Reconstruction and Analysis of Human Kidney-Specific Metabolic Network Based on Omics Data

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Ai-Di Zhang

2013-01-01

Full Text Available With the advent of the high-throughput data production, recent studies of tissue-specific metabolic networks have largely advanced our understanding of the metabolic basis of various physiological and pathological processes. However, for kidney, which plays an essential role in the body, the available kidney-specific model remains incomplete. This paper reports the reconstruction and characterization of the human kidney metabolic network based on transcriptome and proteome data. In silico simulations revealed that house-keeping genes were more essential than kidney-specific genes in maintaining kidney metabolism. Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model. Furthermore, we found that the discrepancies in metabolic processes of different tissues are directly corresponding to tissue's functions. Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism. Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases.

The Global Epidemic of the Metabolic Syndrome.

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Saklayen, Mohammad G

2018-02-26

Metabolic syndrome, variously known also as syndrome X, insulin resistance, etc., is defined by WHO as a pathologic condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Though there is some variation in the definition by other health care organization, the differences are minor. With the successful conquest of communicable infectious diseases in most of the world, this new non-communicable disease (NCD) has become the major health hazard of modern world. Though it started in the Western world, with the spread of the Western lifestyle across the globe, it has become now a truly global problem. The prevalence of the metabolic syndrome is often more in the urban population of some developing countries than in its Western counterparts. The two basic forces spreading this malady are the increase in consumption of high calorie-low fiber fast food and the decrease in physical activity due to mechanized transportations and sedentary form of leisure time activities. The syndrome feeds into the spread of the diseases like type 2 diabetes, coronary diseases, stroke, and other disabilities. The total cost of the malady including the cost of health care and loss of potential economic activity is in trillions. The present trend is not sustainable unless a magic cure is found (unlikely) or concerted global/governmental/societal efforts are made to change the lifestyle that is promoting it. There are certainly some elements in the causation of the metabolic syndrome that cannot be changed but many are amenable for corrections and curtailments. For example, better urban planning to encourage active lifestyle, subsidizing consumption of whole grains and possible taxing high calorie snacks, restricting media advertisement of unhealthy food, etc. Revitalizing old fashion healthier lifestyle, promoting old-fashioned foods using healthy herbs rather than oil and sugar, and educating people about choosing healthy/wholesome food over junks

Global exponential stability for nonautonomous cellular neural networks with delays

International Nuclear Information System (INIS)

Zhang Qiang; Wei Xiaopeng; Xu Jin

2006-01-01

In this Letter, by utilizing Lyapunov functional method and Halanay inequalities, we analyze global exponential stability of nonautonomous cellular neural networks with delay. Several new sufficient conditions ensuring global exponential stability of the network are obtained. The results given here extend and improve the earlier publications. An example is given to demonstrate the effectiveness of the obtained results

Interconnectivity of human cellular metabolism and disease prevalence

International Nuclear Information System (INIS)

Lee, Deok-Sun

2010-01-01

Fluctuations of metabolic reaction fluxes may cause abnormal concentrations of toxic or essential metabolites, possibly leading to metabolic diseases. The mutual binding of enzymatic proteins and ones involving common metabolites enforces distinct coupled reactions, by which local perturbations may spread through the cellular network. Such network effects at the molecular interaction level in human cellular metabolism can reappear in the patterns of disease occurrence. Here we construct the enzyme-reaction network and the metabolite-reaction network, capturing the flux coupling of metabolic reactions caused by the interacting enzymes and the shared metabolites, respectively. Diseases potentially caused by the failure of individual metabolic reactions can be identified by using the known disease–gene association, which allows us to derive the probability of an inactivated reaction causing diseases from the disease records at the population level. We find that the greater the number of proteins that catalyze a reaction, the higher the mean prevalence of its associated diseases. Moreover, the number of connected reactions and the mean size of the avalanches in the networks constructed are also shown to be positively correlated with the disease prevalence. These findings illuminate the impact of the cellular network topology on disease development, suggesting that the global organization of the molecular interaction network should be understood to assist in disease diagnosis, treatment, and drug discovery

Interconnectivity of human cellular metabolism and disease prevalence

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Lee, Deok-Sun

2010-12-01

Fluctuations of metabolic reaction fluxes may cause abnormal concentrations of toxic or essential metabolites, possibly leading to metabolic diseases. The mutual binding of enzymatic proteins and ones involving common metabolites enforces distinct coupled reactions, by which local perturbations may spread through the cellular network. Such network effects at the molecular interaction level in human cellular metabolism can reappear in the patterns of disease occurrence. Here we construct the enzyme-reaction network and the metabolite-reaction network, capturing the flux coupling of metabolic reactions caused by the interacting enzymes and the shared metabolites, respectively. Diseases potentially caused by the failure of individual metabolic reactions can be identified by using the known disease-gene association, which allows us to derive the probability of an inactivated reaction causing diseases from the disease records at the population level. We find that the greater the number of proteins that catalyze a reaction, the higher the mean prevalence of its associated diseases. Moreover, the number of connected reactions and the mean size of the avalanches in the networks constructed are also shown to be positively correlated with the disease prevalence. These findings illuminate the impact of the cellular network topology on disease development, suggesting that the global organization of the molecular interaction network should be understood to assist in disease diagnosis, treatment, and drug discovery.

Polycentrism in Global Health Governance Scholarship; Comment on “Four Challenges That Global Health Networks Face”

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Jale Tosun

2018-01-01

Full Text Available Drawing on an in-depth analysis of eight global health networks, a recent essay in this journal argued that global health networks face four challenges to their effectiveness: problem definition, positioning, coalition-building, and governance. While sharing the argument of the essay concerned, in this commentary, we argue that these analytical concepts can be used to explicate a concept that has implicitly been used in global health governance scholarship for quite a few years. While already prominent in the discussion of climate change governance, for instance, global health governance scholarship could make progress by looking at global health governance as being polycentric. Concisely, polycentric forms of governance mix scales, mechanisms, and actors. Drawing on the essay, we propose a polycentric approach to the study of global health governance that incorporates coalitionbuilding tactics, internal governance and global political priority as explanatory factors.

Optimality Principles in the Regulation of Metabolic Networks

Directory of Open Access Journals (Sweden)

Jan Berkhout

2012-08-01

Full Text Available One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Links that speak: The global language network and its association with global fame

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Ronen, Shahar; Gonçalves, Bruno; Hu, Kevin Z.; Vespignani, Alessandro; Pinker, Steven; Hidalgo, César A.

2014-01-01

Languages vary enormously in global importance because of historical, demographic, political, and technological forces. However, beyond simple measures of population and economic power, there has been no rigorous quantitative way to define the global influence of languages. Here we use the structure of the networks connecting multilingual speakers and translated texts, as expressed in book translations, multiple language editions of Wikipedia, and Twitter, to provide a concept of language importance that goes beyond simple economic or demographic measures. We find that the structure of these three global language networks (GLNs) is centered on English as a global hub and around a handful of intermediate hub languages, which include Spanish, German, French, Russian, Portuguese, and Chinese. We validate the measure of a language’s centrality in the three GLNs by showing that it exhibits a strong correlation with two independent measures of the number of famous people born in the countries associated with that language. These results suggest that the position of a language in the GLN contributes to the visibility of its speakers and the global popularity of the cultural content they produce. PMID:25512502

Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

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Takemoto, Kazuhiro; Aie, Kazuki

2017-05-25

Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

Modeling the Metabolism of Arabidopsis thaliana: Application of Network Decomposition and Network Reduction in the Context of Petri Nets

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Ina Koch

2017-06-01

Full Text Available Motivation:Arabidopsis thaliana is a well-established model system for the analysis of the basic physiological and metabolic pathways of plants. Nevertheless, the system is not yet fully understood, although many mechanisms are described, and information for many processes exists. However, the combination and interpretation of the large amount of biological data remain a big challenge, not only because data sets for metabolic paths are still incomplete. Moreover, they are often inconsistent, because they are coming from different experiments of various scales, regarding, for example, accuracy and/or significance. Here, theoretical modeling is powerful to formulate hypotheses for pathways and the dynamics of the metabolism, even if the biological data are incomplete. To develop reliable mathematical models they have to be proven for consistency. This is still a challenging task because many verification techniques fail already for middle-sized models. Consequently, new methods, like decomposition methods or reduction approaches, are developed to circumvent this problem.Methods: We present a new semi-quantitative mathematical model of the metabolism of Arabidopsis thaliana. We used the Petri net formalism to express the complex reaction system in a mathematically unique manner. To verify the model for correctness and consistency we applied concepts of network decomposition and network reduction such as transition invariants, common transition pairs, and invariant transition pairs.Results: We formulated the core metabolism of Arabidopsis thaliana based on recent knowledge from literature, including the Calvin cycle, glycolysis and citric acid cycle, glyoxylate cycle, urea cycle, sucrose synthesis, and the starch metabolism. By applying network decomposition and reduction techniques at steady-state conditions, we suggest a straightforward mathematical modeling process. We demonstrate that potential steady-state pathways exist, which provide the

A global evolutionary and metabolic analysis of human obesity gene risk variants.

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Castillo, Joseph J; Hazlett, Zachary S; Orlando, Robert A; Garver, William S

2017-09-05

It is generally accepted that the selection of gene variants during human evolution optimized energy metabolism that now interacts with our obesogenic environment to increase the prevalence of obesity. The purpose of this study was to perform a global evolutionary and metabolic analysis of human obesity gene risk variants (110 human obesity genes with 127 nearest gene risk variants) identified using genome-wide association studies (GWAS) to enhance our knowledge of early and late genotypes. As a result of determining the mean frequency of these obesity gene risk variants in 13 available populations from around the world our results provide evidence for the early selection of ancestral risk variants (defined as selection before migration from Africa) and late selection of derived risk variants (defined as selection after migration from Africa). Our results also provide novel information for association of these obesity genes or encoded proteins with diverse metabolic pathways and other human diseases. The overall results indicate a significant differential evolutionary pattern for the selection of obesity gene ancestral and derived risk variants proposed to optimize energy metabolism in varying global environments and complex association with metabolic pathways and other human diseases. These results are consistent with obesity genes that encode proteins possessing a fundamental role in maintaining energy metabolism and survival during the course of human evolution. Copyright © 2017. Published by Elsevier B.V.

Chronic obstructive pulmonary disease candidate gene prioritization based on metabolic networks and functional information.

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Xinyan Wang

Full Text Available Chronic obstructive pulmonary disease (COPD is a multi-factor disease, in which metabolic disturbances played important roles. In this paper, functional information was integrated into a COPD-related metabolic network to assess similarity between genes. Then a gene prioritization method was applied to the COPD-related metabolic network to prioritize COPD candidate genes. The gene prioritization method was superior to ToppGene and ToppNet in both literature validation and functional enrichment analysis. Top-ranked genes prioritized from the metabolic perspective with functional information could promote the better understanding about the molecular mechanism of this disease. Top 100 genes might be potential markers for diagnostic and effective therapies.

Adaptive approach to global synchronization of directed networks with fast switching topologies

International Nuclear Information System (INIS)

Qin Buzhi; Lu Xinbiao

2010-01-01

Global synchronization of directed networks with switching topologies is investigated. It is found that if there exists at least one directed spanning tree in the network with the fixed time-average topology and the time-average topology is achieved sufficiently fast, the network will reach global synchronization for appreciate coupling strength. Furthermore, this appreciate coupling strength may be obtained by local adaptive approach. A sufficient condition about the global synchronization is given. Numerical simulations verify the effectiveness of the adaptive strategy.

Local and global responses in complex gene regulation networks

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Tsuchiya, Masa; Selvarajoo, Kumar; Piras, Vincent; Tomita, Masaru; Giuliani, Alessandro

2009-04-01

An exacerbated sensitivity to apparently minor stimuli and a general resilience of the entire system stay together side-by-side in biological systems. This apparent paradox can be explained by the consideration of biological systems as very strongly interconnected network systems. Some nodes of these networks, thanks to their peculiar location in the network architecture, are responsible for the sensitivity aspects, while the large degree of interconnection is at the basis of the resilience properties of the system. One relevant feature of the high degree of connectivity of gene regulation networks is the emergence of collective ordered phenomena influencing the entire genome and not only a specific portion of transcripts. The great majority of existing gene regulation models give the impression of purely local ‘hard-wired’ mechanisms disregarding the emergence of global ordered behavior encompassing thousands of genes while the general, genome wide, aspects are less known. Here we address, on a data analysis perspective, the discrimination between local and global scale regulations, this goal was achieved by means of the examination of two biological systems: innate immune response in macrophages and oscillating growth dynamics in yeast. Our aim was to reconcile the ‘hard-wired’ local view of gene regulation with a global continuous and scalable one borrowed from statistical physics. This reconciliation is based on the network paradigm in which the local ‘hard-wired’ activities correspond to the activation of specific crucial nodes in the regulation network, while the scalable continuous responses can be equated to the collective oscillations of the network after a perturbation.

Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

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Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

2018-04-01

Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

Context-specific metabolic networks are consistent with experiments.

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Scott A Becker

2008-05-01

Full Text Available Reconstructions of cellular metabolism are publicly available for a variety of different microorganisms and some mammalian genomes. To date, these reconstructions are "genome-scale" and strive to include all reactions implied by the genome annotation, as well as those with direct experimental evidence. Clearly, many of the reactions in a genome-scale reconstruction will not be active under particular conditions or in a particular cell type. Methods to tailor these comprehensive genome-scale reconstructions into context-specific networks will aid predictive in silico modeling for a particular situation. We present a method called Gene Inactivity Moderated by Metabolism and Expression (GIMME to achieve this goal. The GIMME algorithm uses quantitative gene expression data and one or more presupposed metabolic objectives to produce the context-specific reconstruction that is most consistent with the available data. Furthermore, the algorithm provides a quantitative inconsistency score indicating how consistent a set of gene expression data is with a particular metabolic objective. We show that this algorithm produces results consistent with biological experiments and intuition for adaptive evolution of bacteria, rational design of metabolic engineering strains, and human skeletal muscle cells. This work represents progress towards producing constraint-based models of metabolism that are specific to the conditions where the expression profiling data is available.

Metabolic network prediction through pairwise rational kernels.

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Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

2014-09-26

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy

Integration of expression data in genome-scale metabolic network reconstructions

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Anna S. Blazier

2012-08-01

Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

The Role of Functional Interdependencies in Global Operations Networks

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Wæhrens, Brian Vejrum

2011-01-01

The existing studies do not adequately address the complex interplay between co-evolving production, innovation and service networks. The widening geographical and cognitive gap between these networks means that managing their interfaces in global operations context is becoming strategically...

A Status Report on the Global Research in Microbial Metabolic Engineering

Energy Technology Data Exchange (ETDEWEB)

Joe, Min Ho; Lim, Sang Yong; Kim, Dong Ho

2008-09-15

Biotechnology industry is now a global 'Mega-Trend' and metabolic engineering technology has important role is this area. Therefore, many countries has made efforts in this field to produce top value added bio-products efficiently using microorganisms. It has been applied to increase the production of chemicals that are already produced by the host organism, to produce desired chemical substances from less expensive feedstock, and to generate products that are new to the host organism. Recent experimental advances, the so-called '-omics' technologies, mainly functional genomics, proteomics and metabolomics, have enabled wholesale generation of new genomic, transcriptomic, proteomic, and metabolomic data. This report provides the insights of the integrated view of metabolism generated by metabolic engineering for biotechnological applications of microbial metabolic engineering.

A Status Report on the Global Research in Microbial Metabolic Engineering

International Nuclear Information System (INIS)

Joe, Min Ho; Lim, Sang Yong; Kim, Dong Ho

2008-09-01

Biotechnology industry is now a global 'Mega-Trend' and metabolic engineering technology has important role is this area. Therefore, many countries has made efforts in this field to produce top value added bio-products efficiently using microorganisms. It has been applied to increase the production of chemicals that are already produced by the host organism, to produce desired chemical substances from less expensive feedstock, and to generate products that are new to the host organism. Recent experimental advances, the so-called '-omics' technologies, mainly functional genomics, proteomics and metabolomics, have enabled wholesale generation of new genomic, transcriptomic, proteomic, and metabolomic data. This report provides the insights of the integrated view of metabolism generated by metabolic engineering for biotechnological applications of microbial metabolic engineering

A Status Report on the Global Research in Microbial Metabolic Engineering

Energy Technology Data Exchange (ETDEWEB)

Joe, Min Ho; Lim, Sang Yong; Kim, Dong Ho

2008-09-15

Biotechnology industry is now a global 'Mega-Trend' and metabolic engineering technology has important role is this area. Therefore, many countries has made efforts in this field to produce top value added bio-products efficiently using microorganisms. It has been applied to increase the production of chemicals that are already produced by the host organism, to produce desired chemical substances from less expensive feedstock, and to generate products that are new to the host organism. Recent experimental advances, the so-called '-omics' technologies, mainly functional genomics, proteomics and metabolomics, have enabled wholesale generation of new genomic, transcriptomic, proteomic, and metabolomic data. This report provides the insights of the integrated view of metabolism generated by metabolic engineering for biotechnological applications of microbial metabolic engineering.

Gender differences of brain glucose metabolic networks revealed by FDG-PET: evidence from a large cohort of 400 young adults.

Science.gov (United States)

Hu, Yuxiao; Xu, Qiang; Li, Kai; Zhu, Hong; Qi, Rongfeng; Zhang, Zhiqiang; Lu, Guangming

2013-01-01

Gender differences of the human brain are an important issue in neuroscience research. In recent years, an increasing amount of evidence has been gathered from noninvasive neuroimaging studies supporting a sexual dimorphism of the human brain. However, there is a lack of imaging studies on gender differences of brain metabolic networks based on a large population sample. FDG PET data of 400 right-handed, healthy subjects, including 200 females (age: 25:45 years, mean age ± SD: 40.9 ± 3.9 years) and 200 age-matched males were obtained and analyzed in the present study. We first investigated the regional differences of brain glucose metabolism between genders using a voxel-based two-sample t-test analysis. Subsequently, we investigated the gender differences of the metabolic networks. Sixteen metabolic covariance networks using seed-based correlation were analyzed. Seven regions showing significant regional metabolic differences between genders, and nine regions conventionally used in the resting-state network studies were selected as regions-of-interest. Permutation tests were used for comparing within- and between-network connectivity between genders. Compared with the males, females showed higher metabolism in the posterior part and lower metabolism in the anterior part of the brain. Moreover, there were widely distributed patterns of the metabolic networks in the human brain. In addition, significant gender differences within and between brain glucose metabolic networks were revealed in the present study. This study provides solid data that reveal gender differences in regional brain glucose metabolism and brain glucose metabolic networks. These observations might contribute to the better understanding of the gender differences in human brain functions, and suggest that gender should be included as a covariate when designing experiments and explaining results of brain glucose metabolic networks in the control and experimental individuals or patients.

Global Interconnectedness - Local Authorities and Transnational Networking

Directory of Open Access Journals (Sweden)

Hans Krause Hansen

2006-09-01

Full Text Available This article argues that, in their continuous and proclaimed efforts at "modernizing" themselves, public sector organizations, also at the sub-national level, increasingly envision the new media as an object of policy making and intervention. At the same time, this focus on the new media facilitates transborder networking, taking the shape of globalizing webs that connect the actors internationally through pro- cesses af mediation and with implications for relations af authority and modes of governance. As such, these webs both constitute and facilitate a form of everyday political globalization which is on the rise. Empirically, our account is based on studies of two local authorities, the cities of Vina del Mar in Chile and Bremen in Germany, as two of the transnational networks that connect them.

Polycentrism in Global Health Governance Scholarship Comment on "Four Challenges That Global Health Networks Face".

Science.gov (United States)

Tosun, Jale

2017-05-23

Drawing on an in-depth analysis of eight global health networks, a recent essay in this journal argued that global health networks face four challenges to their effectiveness: problem definition, positioning, coalition-building, and governance. While sharing the argument of the essay concerned, in this commentary, we argue that these analytical concepts can be used to explicate a concept that has implicitly been used in global health governance scholarship for quite a few years. While already prominent in the discussion of climate change governance, for instance, global health governance scholarship could make progress by looking at global health governance as being polycentric. Concisely, polycentric forms of governance mix scales, mechanisms, and actors. Drawing on the essay, we propose a polycentric approach to the study of global health governance that incorporates coalitionbuilding tactics, internal governance and global political priority as explanatory factors. © 2018 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Detection of driver metabolites in the human liver metabolic network using structural controllability analysis

Science.gov (United States)

2014-01-01

Background Abnormal states in human liver metabolism are major causes of human liver diseases ranging from hepatitis to hepatic tumor. The accumulation in relevant data makes it feasible to derive a large-scale human liver metabolic network (HLMN) and to discover important biological principles or drug-targets based on network analysis. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis (which is a newly prevailed concept in networks) to biological networks. The exploration on the connections between structural controllability theory and the HLMN could be used to uncover valuable information on the human liver metabolism from a fresh perspective. Results We applied structural controllability analysis to the HLMN and detected driver metabolites. The driver metabolites tend to have strong ability to influence the states of other metabolites and weak susceptibility to be influenced by the states of others. In addition, the metabolites were classified into three classes: critical, high-frequency and low-frequency driver metabolites. Among the identified 36 critical driver metabolites, 27 metabolites were found to be essential; the high-frequency driver metabolites tend to participate in different metabolic pathways, which are important in regulating the whole metabolic systems. Moreover, we explored some other possible connections between the structural controllability theory and the HLMN, and find that transport reactions and the environment play important roles in the human liver metabolism. Conclusion There are interesting connections between the structural controllability theory and the human liver metabolism: driver metabolites have essential biological functions; the crucial role of extracellular metabolites and transport reactions in controlling the HLMN highlights the importance of the environment in the health of human liver metabolism. PMID:24885538

Ecological network analysis on global virtual water trade.

Science.gov (United States)

Yang, Zhifeng; Mao, Xufeng; Zhao, Xu; Chen, Bin

2012-02-07

Global water interdependencies are likely to increase with growing virtual water trade. To address the issues of the indirect effects of water trade through the global economic circulation, we use ecological network analysis (ENA) to shed insight into the complicated system interactions. A global model of virtual water flow among agriculture and livestock production trade in 1995-1999 is also built as the basis for network analysis. Control analysis is used to identify the quantitative control or dependency relations. The utility analysis provides more indicators for describing the mutual relationship between two regions/countries by imitating the interactions in the ecosystem and distinguishes the beneficiary and the contributor of virtual water trade system. Results show control and utility relations can well depict the mutual relation in trade system, and direct observable relations differ from integral ones with indirect interactions considered. This paper offers a new way to depict the interrelations between trade components and can serve as a meaningful start as we continue to use ENA in providing more valuable implications for freshwater study on a global scale.

Global and local targeted immunization in networks with community structure

International Nuclear Information System (INIS)

Yan, Shu; Tang, Shaoting; Pei, Sen; Zheng, Zhiming; Fang, Wenyi

2015-01-01

Immunization plays an important role in the field of epidemic spreading in complex networks. In previous studies, targeted immunization has been proved to be an effective strategy. However, when extended to networks with community structure, it is unknown whether the superior strategy is to vaccinate the nodes who have the most connections in the entire network (global strategy), or those in the original community where epidemic starts to spread (local strategy). In this work, by using both analytic approaches and simulations, we observe that the answer depends on the closeness between communities. If communities are tied closely, the global strategy is superior to the local strategy. Otherwise, the local targeted immunization is advantageous. The existence of a transitional value of closeness implies that we should adopt different strategies. Furthermore, we extend our investigation from two-community networks to multi-community networks. We consider the mode of community connection and the location of community where epidemic starts to spread. Both simulation results and theoretical predictions show that local strategy is a better option for immunization in most cases. But if the epidemic begins from a core community, global strategy is superior in some cases. (paper)

Quantitative analysis of proteome and lipidome dynamics reveals functional regulation of global lipid metabolism

DEFF Research Database (Denmark)

Casanovas, Albert; Sprenger, Richard R; Tarasov, Kirill

2015-01-01

Elucidating how and to what extent lipid metabolism is remodeled under changing conditions is essential for understanding cellular physiology. Here, we analyzed proteome and lipidome dynamics to investigate how regulation of lipid metabolism at the global scale supports remodeling of cellular...

Impact of the topology of global macroeconomic network on the spreading of economic crises.

Science.gov (United States)

Lee, Kyu-Min; Yang, Jae-Suk; Kim, Gunn; Lee, Jaesung; Goh, Kwang-Il; Kim, In-mook

2011-03-31

Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country's role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more "globalized" random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises.

Environmental versatility promotes modularity in large scale metabolic networks

OpenAIRE

Samal A.; Wagner Andreas; Martin O.C.

2011-01-01

Abstract Background The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chem...

Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

Science.gov (United States)

Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

2014-01-01

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

Structure and dynamics of the global financial network

International Nuclear Information System (INIS)

Silva, Thiago Christiano; Rubens Stancato de Souza, Sergio; Tabak, Benjamin Miranda

2016-01-01

In this paper, we study the evolution of the network topology for the global financial market. We evaluate the level of diversification and participation of developed and emerging economies in cross-border exposures and find that the gross exposure network is dense, the vulnerability matrix is sparse, and the network’s fragility changes over time. Prior to the financial crisis in 2008, the network was relatively fragile, whereas it became more resilient afterwards, showing a reduction in financial institutions’ risk appetite. Our results suggest that financial regulators should track down the network evolution in their systemic risk assessment.

Acquisition management of the Global Transportation Network

Science.gov (United States)

2001-08-02

This report discusses the acquisition management of the Global transportation Network by the U.S. Transportation Command. This report is one in a series of audit reports addressing DoD acquisition management of information technology systems. The Glo...

Global asymptotical ω-periodicity of a fractional-order non-autonomous neural networks.

Science.gov (United States)

Chen, Boshan; Chen, Jiejie

2015-08-01

We study the global asymptotic ω-periodicity for a fractional-order non-autonomous neural networks. Firstly, based on the Caputo fractional-order derivative it is shown that ω-periodic or autonomous fractional-order neural networks cannot generate exactly ω-periodic signals. Next, by using the contraction mapping principle we discuss the existence and uniqueness of S-asymptotically ω-periodic solution for a class of fractional-order non-autonomous neural networks. Then by using a fractional-order differential and integral inequality technique, we study global Mittag-Leffler stability and global asymptotical periodicity of the fractional-order non-autonomous neural networks, which shows that all paths of the networks, starting from arbitrary points and responding to persistent, nonconstant ω-periodic external inputs, asymptotically converge to the same nonconstant ω-periodic function that may be not a solution. Copyright © 2015 Elsevier Ltd. All rights reserved.

International collaboration in science: The global map and the network

NARCIS (Netherlands)

Leydesdorff, L.; Wagner, C.S.; Park, H.W.; Adams, J.

2013-01-01

The network of international co-authorship relations has been dominated by certain European nations and the USA, but this network is rapidly expanding at the global level. Between 40 and 50 countries appear in the center of the international network in 2011, and almost all (201) nations are nowadays

Mimoza: web-based semantic zooming and navigation in metabolic networks.

Science.gov (United States)

Zhukova, Anna; Sherman, David J

2015-02-26

The complexity of genome-scale metabolic models makes them quite difficult for human users to read, since they contain thousands of reactions that must be included for accurate computer simulation. Interestingly, hidden similarities between groups of reactions can be discovered, and generalized to reveal higher-level patterns. The web-based navigation system Mimoza allows a human expert to explore metabolic network models in a semantically zoomable manner: The most general view represents the compartments of the model; the next view shows the generalized versions of reactions and metabolites in each compartment; and the most detailed view represents the initial network with the generalization-based layout (where similar metabolites and reactions are placed next to each other). It allows a human expert to grasp the general structure of the network and analyze it in a top-down manner Mimoza can be installed standalone, or used on-line at http://mimoza.bordeaux.inria.fr/ , or installed in a Galaxy server for use in workflows. Mimoza views can be embedded in web pages, or downloaded as COMBINE archives.

Core Support to Global Development Network (GND) - Phase II ...

International Development Research Centre (IDRC) Digital Library (Canada)

The Global Development Network (GDN) was launched by the World Bank in 1999 on the premise that good policy research, properly applied, can accelerate development and improve people's lives. Working mainly through regional networks, GDN supports economic and, increasingly, social science research in and on ...

Global 4-H Network: Laying the Groundwork for Global Extension Opportunities

Science.gov (United States)

Major, Jennifer; Miller, Rhonda

2012-01-01

A descriptive study examining 4-H programs in Africa, Asia, and Europe was conducted to provide understanding and direction in the establishment of a Global 4-H Network. Information regarding structure, organizational support, funding, and programming areas was gathered. Programs varied greatly by country, and many partnered with other 4-H…

A Global Protein Kinase and Phosphatase Interaction Network in Yeast

Science.gov (United States)

Breitkreutz, Ashton; Choi, Hyungwon; Sharom, Jeffrey R.; Boucher, Lorrie; Neduva, Victor; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Bobby-Joe; Stark, Chris; Liu, Guomin; Ahn, Jessica; Dewar-Darch, Danielle; Reguly, Teresa; Tang, Xiaojing; Almeida, Ricardo; Qin, Zhaohui Steve; Pawson, Tony; Gingras, Anne-Claude; Nesvizhskii, Alexey I.; Tyers, Mike

2011-01-01

The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses. PMID:20489023

Novel results for global robust stability of delayed neural networks

International Nuclear Information System (INIS)

Yucel, Eylem; Arik, Sabri

2009-01-01

This paper investigates the global robust convergence properties of continuous-time neural networks with discrete time delays. By employing suitable Lyapunov functionals, some sufficient conditions for the existence, uniqueness and global robust asymptotic stability of the equilibrium point are derived. The conditions can be easily verified as they can be expressed in terms of the network parameters only. Some numerical examples are also given to compare our results with previous robust stability results derived in the literature.

Human-Centered Development of an Online Social Network for Metabolic Syndrome Management.

Science.gov (United States)

Núñez-Nava, Jefersson; Orozco-Sánchez, Paola A; López, Diego M; Ceron, Jesus D; Alvarez-Rosero, Rosa E

2016-01-01

According to the International Diabetes Federation (IDF), a quarter of the world's population has Metabolic Syndrome (MS). To develop (and assess the users' degree of satisfaction of) an online social network for patients who suffer from Metabolic Syndrome, based on the recommendations and requirements of the Human-Centered Design. Following the recommendations of the ISO 9241-210 for Human-Centered Design (HCD), an online social network was designed to promote physical activity and healthy nutrition. In order to guarantee the active participation of the users during the development of the social network, a survey, an in-depth interview, a focal group, and usability tests were carried out with people suffering from MS. The study demonstrated how the different activities, recommendations, and requirements of the ISO 9241-210 are integrated into a traditional software development process. Early usability tests demonstrated that the user's acceptance and the effectiveness and efficiency of the social network are satisfactory.

Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation.

Science.gov (United States)

Cordes, Henrik; Thiel, Christoph; Baier, Vanessa; Blank, Lars M; Kuepfer, Lars

2018-01-01

Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.

Development of global cortical networks in early infancy.

Science.gov (United States)

Homae, Fumitaka; Watanabe, Hama; Otobe, Takayuki; Nakano, Tamami; Go, Tohshin; Konishi, Yukuo; Taga, Gentaro

2010-04-07

Human cognition and behaviors are subserved by global networks of neural mechanisms. Although the organization of the brain is a subject of interest, the process of development of global cortical networks in early infancy has not yet been clarified. In the present study, we explored developmental changes in these networks from several days to 6 months after birth by examining spontaneous fluctuations in brain activity, using multichannel near-infrared spectroscopy. We set up 94 measurement channels over the frontal, temporal, parietal, and occipital regions of the infant brain. The obtained signals showed complex time-series properties, which were characterized as 1/f fluctuations. To reveal the functional connectivity of the cortical networks, we calculated the temporal correlations of continuous signals between all the pairs of measurement channels. We found that the cortical network organization showed regional dependency and dynamic changes in the course of development. In the temporal, parietal, and occipital regions, connectivity increased between homologous regions in the two hemispheres and within hemispheres; in the frontal regions, it decreased progressively. Frontoposterior connectivity changed to a "U-shaped" pattern within 6 months: it decreases from the neonatal period to the age of 3 months and increases from the age of 3 months to the age of 6 months. We applied cluster analyses to the correlation coefficients and showed that the bilateral organization of the networks begins to emerge during the first 3 months of life. Our findings suggest that these developing networks, which form multiple clusters, are precursors of the functional cerebral architecture.

A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

Science.gov (United States)

Röhl, Annika; Bockmayr, Alexander

2017-01-03

Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

Globalizing Social Justice Education: The Case of The Global Solidarity Network Study e-Broad Program

Science.gov (United States)

Harrison, Yvonne D.; Kostic, Kevin; Toton, Suzanne C.; Zurek, Jerome

2010-01-01

This paper documents the development, implementation, and evaluation of "The Global Solidarity Network Study e-Broad Program (GSNSeBP)", an online social justice educational program that is blended into an onsite academic course. This global electronic program, which was developed through a partnership between Catholic Relief Services (CRS) and…

In Search of a Network Organization for Innovation: A Multilevel Analysis on Transnational Corporations' Global Innovation

DEFF Research Database (Denmark)

Hu, Yimei

2013-01-01

4 explores how transnational corporations perceive and design an internal network organization to facilitate global innovation. Based on a multiple case study of three Danish transnational corporations’ global R&D organization, this paper shows three types of network organization design...... explores how an SME develops a network organization consisting of both interfirm innovation networks and an internal network organization to facilitate its global innovation strategy. Regarding the intraorganizational network organization, market mechanism is adopted to optimize internal resource...... corporations perceive/design a network organization to facilitate their global innovation? • To what extent and how can we manage a network organization? Research focus of the dissertation is on transnational corporations’ network organization for innovation. The first research question aims to clarify...

Managerial capabilities of the home base in an intra-organisational global network

DEFF Research Database (Denmark)

Mykhaylenko, Alona

of the HB change in the process of its global intra-organisational network evolution. In particular, the four papers constituting this thesis investigate how global intra-organisational networks evolve, how the types of network management capabilities of the HB change along with such network evolution....... This investigation was conducted through a retrospective longitudinal case study of one Danish original equipment manufacturer and its three subsidiaries in China, Slovakia, and the US. The findings, first of all, support, extend, and modify the revised Uppsala globalisation model with regard to the types...

Network thermodynamic curation of human and yeast genome-scale metabolic models.

Science.gov (United States)

Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

2014-07-15

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Global stability of stochastic high-order neural networks with discrete and distributed delays

International Nuclear Information System (INIS)

Wang Zidong; Fang Jianan; Liu Xiaohui

2008-01-01

High-order neural networks can be considered as an expansion of Hopfield neural networks, and have stronger approximation property, faster convergence rate, greater storage capacity, and higher fault tolerance than lower-order neural networks. In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with discrete and distributed time-delays. Based on an Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived, which guarantee the global asymptotic convergence of the equilibrium point in the mean square. It is shown that the stochastic high-order delayed neural networks under consideration are globally asymptotically stable in the mean square if two linear matrix inequalities (LMIs) are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox. It is also shown that the main results in this paper cover some recently published works. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria

The Global Climatology Network Precipitation data

International Nuclear Information System (INIS)

Peterson, T.C.; Easterling, D.R.; Eischeid, J.K.

1993-01-01

Several years ago, in response to growing concern about global climate change, the US National Climatic Data Center and the Carbon Dioxide Information Analysis Center undertook an effort to create a baseline global land surface climate data set called the Global Historical Climatology Network (GHCN, Vose et al., 1992). GHCN was created by merging several large existing climate data sets into one data base. Fifteen separate data sets went into the creation of the GHCN version 1.0. GHCN version 1.0 was released in 1992. It has 7,533 precipitation stations, but the number of stations varies with time. A slight majority (55%) have records in excess of 50 years, and a significant proportion (13%) have records in excess of 100 years. The longest period of record for any given station is 291 years (1697--1987 for Kew, United Kingdom)

From global agenda-setting to domestic implementation: successes and challenges of the global health network on tobacco control.

Science.gov (United States)

Gneiting, Uwe

2016-04-01

Global policy attention to tobacco control has increased significantly since the 1990 s and culminated in the first international treaty negotiated under the auspices of the World Health Organization--the Framework Convention on Tobacco Control (FCTC). Although the political process that led to the creation of the FCTC has been extensively researched, the FCTC's progression from an aspirational treaty towards a global health governance framework with tangible policy effects within FCTC member countries has not been well-understood to date. This article analyses the role of the global health network of tobacco control advocates and scientists, which formed during the FCTC negotiations during the late 1990 s, in translating countries' commitment to the FCTC into domestic policy change. By comparing the network's influence around two central tobacco control interventions (smoke-free environments and taxation), the study identifies several scope conditions, which have shaped the network's effectiveness around the FCTC's implementation: the complexity of the policy issue and the relative importance of non-health expertise, the required scope of domestic political buy-in, the role of the general public as network allies, and the strength of policy opposition. These political factors had a greater influence on the network's success than the evidence base for the effectiveness of tobacco control interventions. The network's variable success points to a trade-off faced by global health networks between their need to maintain internal cohesion and their ability to form alliances with actors in their social environment. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2015; all rights reserved.

Integration of metabolomics data into metabolic networks.

Science.gov (United States)

Töpfer, Nadine; Kleessen, Sabrina; Nikoloski, Zoran

2015-01-01

Metabolite levels together with their corresponding metabolic fluxes are integrative outcomes of biochemical transformations and regulatory processes and they can be used to characterize the response of biological systems to genetic and/or environmental changes. However, while changes in transcript or to some extent protein levels can usually be traced back to one or several responsible genes, changes in fluxes and particularly changes in metabolite levels do not follow such rationale and are often the outcome of complex interactions of several components. The increasing quality and coverage of metabolomics technologies have fostered the development of computational approaches for integrating metabolic read-outs with large-scale models to predict the physiological state of a system. Constraint-based approaches, relying on the stoichiometry of the considered reactions, provide a modeling framework amenable to analyses of large-scale systems and to the integration of high-throughput data. Here we review the existing approaches that integrate metabolomics data in variants of constrained-based approaches to refine model reconstructions, to constrain flux predictions in metabolic models, and to relate network structural properties to metabolite levels. Finally, we discuss the challenges and perspectives in the developments of constraint-based modeling approaches driven by metabolomics data.

China's evolving role in global production networks: Implications for Trump's trade war

OpenAIRE

Athukorala, Prema-chandra

2017-01-01

This paper examines China's evolving role in global production networks and its implications for assessing the potential impact of the "trade war" declared by President Trump. The analysis, which is based on a systematic disaggregation of trade based on global production sharing into components and final assembly, suggests that the Sino-US trade gap is a structural phenomenon driven by the pivotal role played by China within East Asia cantered production networks. The global competitiveness o...

Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

International Nuclear Information System (INIS)

Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

2015-01-01

Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

Global spatio-temporal patterns in human migration: a complex network perspective.

Science.gov (United States)

Davis, Kyle F; D'Odorico, Paolo; Laio, Francesco; Ridolfi, Luca

2013-01-01

Migration is a powerful adaptive strategy for humans to navigate hardship and pursue a better quality of life. As a universal vehicle facilitating exchanges of ideas, culture, money and goods, international migration is a major contributor to globalization. Consisting of countries linked by multiple connections of human movements, global migration constitutes a network. Despite the important role of human migration in connecting various communities in different parts of the world, the topology and behavior of the international migration network and its changes through time remain poorly understood. Here we show that the global human migration network became more interconnected during the latter half of the twentieth century and that migrant destination choice partly reflects colonial and postcolonial histories, language, religion, and distances. From 1960 to 2000 we found a steady increase in network transitivity (i.e. connectivity between nodes connected to the same node), a decrease in average path length and an upward shift in degree distribution, all of which strengthened the 'small-world' behavior of the migration network. Furthermore, we found that distinct groups of countries preferentially interact to form migration communities based largely on historical, cultural and economic factors.

Global spatio-temporal patterns in human migration: a complex network perspective.

Directory of Open Access Journals (Sweden)

Kyle F Davis

Full Text Available Migration is a powerful adaptive strategy for humans to navigate hardship and pursue a better quality of life. As a universal vehicle facilitating exchanges of ideas, culture, money and goods, international migration is a major contributor to globalization. Consisting of countries linked by multiple connections of human movements, global migration constitutes a network. Despite the important role of human migration in connecting various communities in different parts of the world, the topology and behavior of the international migration network and its changes through time remain poorly understood. Here we show that the global human migration network became more interconnected during the latter half of the twentieth century and that migrant destination choice partly reflects colonial and postcolonial histories, language, religion, and distances. From 1960 to 2000 we found a steady increase in network transitivity (i.e. connectivity between nodes connected to the same node, a decrease in average path length and an upward shift in degree distribution, all of which strengthened the 'small-world' behavior of the migration network. Furthermore, we found that distinct groups of countries preferentially interact to form migration communities based largely on historical, cultural and economic factors.

Multiobjective flux balancing using the NISE method for metabolic network analysis.

Science.gov (United States)

Oh, Young-Gyun; Lee, Dong-Yup; Lee, Sang Yup; Park, Sunwon

2009-01-01

Flux balance analysis (FBA) is well acknowledged as an analysis tool of metabolic networks in the framework of metabolic engineering. However, FBA has a limitation for solving a multiobjective optimization problem which considers multiple conflicting objectives. In this study, we propose a novel multiobjective flux balance analysis method, which adapts the noninferior set estimation (NISE) method (Solanki et al., 1993) for multiobjective linear programming (MOLP) problems. NISE method can generate an approximation of the Pareto curve for conflicting objectives without redundant iterations of single objective optimization. Furthermore, the flux distributions at each Pareto optimal solution can be obtained for understanding the internal flux changes in the metabolic network. The functionality of this approach is shown by applying it to a genome-scale in silico model of E. coli. Multiple objectives for the poly(3-hydroxybutyrate) [P(3HB)] production are considered simultaneously, and relationships among them are identified. The Pareto curve for maximizing succinic acid production vs. maximizing biomass production is used for the in silico analysis of various combinatorial knockout strains. This proposed method accelerates the strain improvement in the metabolic engineering by reducing computation time of obtaining the Pareto curve and analysis time of flux distribution at each Pareto optimal solution. (c) 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009.

Globally exponential stability of neural network with constant and variable delays

International Nuclear Information System (INIS)

Zhao Weirui; Zhang Huanshui

2006-01-01

This Letter presents new sufficient conditions of globally exponential stability of neural networks with delays. We show that these results generalize recently published globally exponential stability results. In particular, several different globally exponential stability conditions in the literatures which were proved using different Lyapunov functionals are generalized and unified by using the same Lyapunov functional and the technique of inequality of integral. A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed neural networks. Those conditions are less restrictive than those given in the earlier references

Enumeration of minimal stoichiometric precursor sets in metabolic networks.

Science.gov (United States)

Andrade, Ricardo; Wannagat, Martin; Klein, Cecilia C; Acuña, Vicente; Marchetti-Spaccamela, Alberto; Milreu, Paulo V; Stougie, Leen; Sagot, Marie-France

2016-01-01

What an organism needs at least from its environment to produce a set of metabolites, e.g. target(s) of interest and/or biomass, has been called a minimal precursor set. Early approaches to enumerate all minimal precursor sets took into account only the topology of the metabolic network (topological precursor sets). Due to cycles and the stoichiometric values of the reactions, it is often not possible to produce the target(s) from a topological precursor set in the sense that there is no feasible flux. Although considering the stoichiometry makes the problem harder, it enables to obtain biologically reasonable precursor sets that we call stoichiometric. Recently a method to enumerate all minimal stoichiometric precursor sets was proposed in the literature. The relationship between topological and stoichiometric precursor sets had however not yet been studied. Such relationship between topological and stoichiometric precursor sets is highlighted. We also present two algorithms that enumerate all minimal stoichiometric precursor sets. The first one is of theoretical interest only and is based on the above mentioned relationship. The second approach solves a series of mixed integer linear programming problems. We compared the computed minimal precursor sets to experimentally obtained growth media of several Escherichia coli strains using genome-scale metabolic networks. The results show that the second approach efficiently enumerates minimal precursor sets taking stoichiometry into account, and allows for broad in silico studies of strains or species interactions that may help to understand e.g. pathotype and niche-specific metabolic capabilities. sasita is written in Java, uses cplex as LP solver and can be downloaded together with all networks and input files used in this paper at http://www.sasita.gforge.inria.fr.

Global terrestrial water storage connectivity revealed using complex climate network analyses

Science.gov (United States)

Sun, A. Y.; Chen, J.; Donges, J.

2015-07-01

Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

Network master planning for a global manufacturing company

OpenAIRE

Heinz, Michael Pierre

2006-01-01

Production in global, intra-organisational networks is becoming more common. In this context, the allocation of production quantities to constrained manufacturing capacity is a challenging process. Due to a volatile environment it is argued to be impossible to achieve a ‘clean’ system design with dedicated resources which exactly meets future demand. Thus, recursive ‘Network Master Planning’ (NMP) becomes necessary. The aim of this research is to generate an understanding of th...

Networks of global bird invasion altered by regional trade ban.

Science.gov (United States)

Reino, Luís; Figueira, Rui; Beja, Pedro; Araújo, Miguel B; Capinha, César; Strubbe, Diederik

2017-11-01

Wildlife trade is a major pathway for introduction of invasive species worldwide. However, how exactly wildlife trade influences invasion risk, beyond the transportation of individuals to novel areas, remains unknown. We analyze the global trade network of wild-caught birds from 1995 to 2011 as reported by CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora). We found that before the European Union ban on imports of wild-caught birds, declared in 2005, invasion risk was closely associated with numbers of imported birds, diversity of import sources, and degree of network centrality of importer countries. After the ban, fluxes of global bird trade declined sharply. However, new trade routes emerged, primarily toward the Nearctic, Afrotropical, and Indo-Malay regions. Although regional bans can curtail invasion risk globally, to be fully effective and prevent rerouting of trade flows, bans should be global.

Architectural Design for the Global Legal Information Network

Science.gov (United States)

Kalpakis, Konstantinos

1999-01-01

In this report, we provide a summary of our activities regarding the goals, requirements analysis, design, and prototype implementation for the Global Legal Information Network, a joint effort between the Law Library of Congress and NASA.

Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

Directory of Open Access Journals (Sweden)

Heavner Benjamin D

2012-06-01

Full Text Available Abstract Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Additional file 1 Function testYeastModel.m.m. Click here for file Additional file 2 Function model

International Children's Palliative Care Network: A Global Action Network for Children With Life-Limiting Conditions.

Science.gov (United States)

Marston, Joan; Boucher, Sue; Downing, Julia

2018-02-01

The International Children's Palliative Care Network (ICPCN) is a global network of individuals and organizations working together to reach the estimated 21 million children with life-limiting conditions and life-threatening illnesses. The drive to establish the ICPCN was born from the recognition of the gaps in service provision for children's palliative care and the need to collaborate, network, and share resources. Established in 2005 during a meeting in Seoul, South Korea, the ICPCN has developed over the years into an established network with a global membership. The history of the organization is described, including some of the key events since its inception. Working in collaboration with others, ICPCN has five key focus areas: Communication; Advocacy; Research; Education; and Strategic development, and is the only international charity working globally for the rights of children with palliative care needs. Activities in these areas are discussed, along with the inter-connection between the five areas. Without the ICPCN, palliative care for children would not have developed as far as it has over the years and the organization is committed to ongoing work in this area until all children requiring palliative care have access to quality services, wherever they live around the world. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Global patterns in lake ecosystem responses to warming based on the temperature dependence of metabolism.

Science.gov (United States)

Kraemer, Benjamin M; Chandra, Sudeep; Dell, Anthony I; Dix, Margaret; Kuusisto, Esko; Livingstone, David M; Schladow, S Geoffrey; Silow, Eugene; Sitoki, Lewis M; Tamatamah, Rashid; McIntyre, Peter B

2017-05-01

Climate warming is expected to have large effects on ecosystems in part due to the temperature dependence of metabolism. The responses of metabolic rates to climate warming may be greatest in the tropics and at low elevations because mean temperatures are warmer there and metabolic rates respond exponentially to temperature (with exponents >1). However, if warming rates are sufficiently fast in higher latitude/elevation lakes, metabolic rate responses to warming may still be greater there even though metabolic rates respond exponentially to temperature. Thus, a wide range of global patterns in the magnitude of metabolic rate responses to warming could emerge depending on global patterns of temperature and warming rates. Here we use the Boltzmann-Arrhenius equation, published estimates of activation energy, and time series of temperature from 271 lakes to estimate long-term (1970-2010) changes in 64 metabolic processes in lakes. The estimated responses of metabolic processes to warming were usually greatest in tropical/low-elevation lakes even though surface temperatures in higher latitude/elevation lakes are warming faster. However, when the thermal sensitivity of a metabolic process is especially weak, higher latitude/elevation lakes had larger responses to warming in parallel with warming rates. Our results show that the sensitivity of a given response to temperature (as described by its activation energy) provides a simple heuristic for predicting whether tropical/low-elevation lakes will have larger or smaller metabolic responses to warming than higher latitude/elevation lakes. Overall, we conclude that the direct metabolic consequences of lake warming are likely to be felt most strongly at low latitudes and low elevations where metabolism-linked ecosystem services may be most affected. © 2016 John Wiley & Sons Ltd.

The Global Alzheimer's Association Interactive Network.

Science.gov (United States)

Toga, Arthur W; Neu, Scott C; Bhatt, Priya; Crawford, Karen L; Ashish, Naveen

2016-01-01

The Global Alzheimer's Association Interactive Network (GAAIN) is consolidating the efforts of independent Alzheimer's disease data repositories around the world with the goals of revealing more insights into the causes of Alzheimer's disease, improving treatments, and designing preventative measures that delay the onset of physical symptoms. We developed a system for federating these repositories that is reliant on the tenets that (1) its participants require incentives to join, (2) joining the network is not disruptive to existing repository systems, and (3) the data ownership rights of its members are protected. We are currently in various phases of recruitment with over 55 data repositories in North America, Europe, Asia, and Australia and can presently query >250,000 subjects using GAAIN's search interfaces. GAAIN's data sharing philosophy, which guided our architectural choices, is conducive to motivating membership in a voluntary data sharing network. Copyright © 2016 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

The Global Geodetic Observing System: Space Geodesy Networks for the Future

Science.gov (United States)

Pearlman, Michael; Pavlis, Erricos; Ma, Chopo; Altamini, Zuheir; Noll, Carey; Stowers, David

2011-01-01

Ground-based networks of co-located space geodetic techniques (VLBI, SLR, GNSS. and DORIS) are the basis for the development and maintenance of the International Terrestrial Reference frame (ITRF), which is our metric of reference for measurements of global change, The Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG) has established a task to develop a strategy to design, integrate and maintain the fundamental geodetic network and supporting infrastructure in a sustainable way to satisfy the long-term requirements for the reference frame. The GGOS goal is an origin definition at 1 mm or better and a temporal stability on the order of 0.1 mm/y, with similar numbers for the scale and orientation components. These goals are based on scientific requirements to address sea level rise with confidence, but other applications are not far behind. Recent studies including one by the US National Research Council has strongly stated the need and the urgency for the fundamental space geodesy network. Simulations are underway to examining accuracies for origin, scale and orientation of the resulting ITRF based on various network designs and system performance to determine the optimal global network to achieve this goal. To date these simulations indicate that 24 - 32 co-located stations are adequate to define the reference frame and a more dense GNSS and DORIS network will be required to distribute the reference frame to users anywhere on Earth. Stations in the new global network will require geologically stable sites with good weather, established infrastructure, and local support and personnel. GGOS wil seek groups that are interested in participation. GGOS intends to issues a Call for Participation of groups that would like to contribute in the network implementation and operation. Some examples of integrated stations currently in operation or under development will be presented. We will examine necessary conditions and challenges in

Transcriptional regulation and steady-state modeling of metabolic networks

DEFF Research Database (Denmark)

Zelezniak, Aleksej

Biological systems are characterized by a high degree of complexity wherein the individual components (e.g. proteins) are inter-linked in a way that leads to emergent behaviors that are difficult to decipher. Uncovering system complexity requires, at least, answers to the following three questions......: what are the components of the systems, how are the different components interconnected and how do these networks perform the functions that make the resulting system behavior? Modern analytical technologies allow us to unravel the constituents and interactions happening in a given system; however......, the third question is the ultimate challenge for systems biology. The work of this thesis systematically addresses this question in the context of metabolic networks, which are arguably the most well characterized cellular networks in terms of their constituting components and interactions among them...

A FDG-PET Study of Metabolic Networks in Apolipoprotein E ε4 Allele Carriers.

Directory of Open Access Journals (Sweden)

Zhijun Yao

Full Text Available Recently, some studies have applied the graph theory in brain network analysis in Alzheimer's disease (AD and Mild Cognitive Impairment (MCI. However, relatively little research has specifically explored the properties of the metabolic network in apolipoprotein E (APOE ε4 allele carriers. In our study, all the subjects, including ADs, MCIs and NCs (normal controls were divided into 165 APOE ε4 carriers and 165 APOE ε4 noncarriers. To establish the metabolic network for all brain regions except the cerebellum, cerebral glucose metabolism data obtained from FDG-PET (18F-fluorodeoxyglucose positron emission tomography were segmented into 90 areas with automated anatomical labeling (AAL template. Then, the properties of the networks were computed to explore the between-group differences. Our results suggested that both APOE ε4 carriers and noncarriers showed the small-world properties. Besides, compared with APOE ε4 noncarriers, the carriers showed a lower clustering coefficient. In addition, significant changes in 6 hub brain regions were found in between-group nodal centrality. Namely, compared with APOE ε4 noncarriers, significant decreases of the nodal centrality were found in left insula, right insula, right anterior cingulate, right paracingulate gyri, left cuneus, as well as significant increases in left paracentral lobule and left heschl gyrus in APOE ε4 carriers. Increased local short distance interregional correlations and disrupted long distance interregional correlations were found, which may support the point that the APOE ε4 carriers were more similar with AD or MCI in FDG uptake. In summary, the organization of metabolic network in APOE ε4 carriers indicated a less optimal pattern and APOE ε4 might be a risk factor for AD.

Global similarity and local divergence in human and mouse gene co-expression networks

Directory of Open Access Journals (Sweden)

Koonin Eugene V

2006-09-01

Full Text Available Abstract Background A genome-wide comparative analysis of human and mouse gene expression patterns was performed in order to evaluate the evolutionary divergence of mammalian gene expression. Tissue-specific expression profiles were analyzed for 9,105 human-mouse orthologous gene pairs across 28 tissues. Expression profiles were resolved into species-specific coexpression networks, and the topological properties of the networks were compared between species. Results At the global level, the topological properties of the human and mouse gene coexpression networks are, essentially, identical. For instance, both networks have topologies with small-world and scale-free properties as well as closely similar average node degrees, clustering coefficients, and path lengths. However, the human and mouse coexpression networks are highly divergent at the local level: only a small fraction ( Conclusion The dissonance between global versus local network divergence suggests that the interspecies similarity of the global network properties is of limited biological significance, at best, and that the biologically relevant aspects of the architectures of gene coexpression are specific and particular, rather than universal. Nevertheless, there is substantial evolutionary conservation of the local network structure which is compatible with the notion that gene coexpression networks are subject to purifying selection.

Conducting network penetration and espionage in a global environment

CERN Document Server

Middleton, Bruce

2014-01-01

When it's all said and done, penetration testing remains the most effective way to identify security vulnerabilities in computer networks. Conducting Network Penetration and Espionage in a Global Environment provides detailed guidance on how to perform effective penetration testing of computer networks-using free, open source, and commercially available tools, including Backtrack, Metasploit, Wireshark, Nmap, Netcat, and Nessus. It also considers exploits and other programs using Python, PERL, BASH, PHP, Ruby, and Windows PowerShell.The book taps into Bruce Middleton's decades of experience wi

65 Years of influenza surveillance by a WHO-coordinated global network.

Science.gov (United States)

Ziegler, Thedi; Mamahit, Awandha; Cox, Nancy J

2018-05-04

The 1918 devastating influenza pandemic left a lasting impact on influenza experts and the public, and the importance of global influenza surveillance was soon recognized. The WHO Global Influenza Surveillance Network (GISN) was founded in 1952 and renamed to Global Influenza Surveillance and Response System in 2011 upon the adoption by the World Health Assembly, of the Pandemic Influenza Preparedness Framework for the Sharing of Influenza Viruses and Access to Vaccines and Other Benefits ("PIP Framework"). The importance of influenza surveillance had been recognized and promoted by experts prior to the years leading up to the establishment of WHO. In the 65 years of its existence, the Network has grown to comprise 143 National Influenza Centers recognized by WHO, 6 WHO Collaborating Centers, 4 Essential Regulatory Laboratories, and 13 H5 Reference Laboratories. The Network has proven its excellence throughout these 65 years, providing detailed information on circulating seasonal influenza viruses, as well as immediate response to the influenza pandemics in 1957, 1968, and 2009, and to threats caused by animal influenza viruses and by zoonotic transmission of coronaviruses. For its central role in global public health, the Network has been highly recognized by its many partners and by international bodies. Several generations of world renown influenza scientists have brought the Network to where it is now and they will take it forward to the future, as influenza will remain a pre-eminent threat to humans and to animals. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Correlation and network topologies in global and local stock indices

Science.gov (United States)

Nobi, Ashadun; Lee, Sungmin; Kim, Doo Hwan; Lee, Jae Woo

2014-07-01

We examined how the correlation and network structure of the global indices and local Korean indices have changed during years 2000-2012. The average correlations of the global indices increased with time, while the local indices showed a decreasing trend except for drastic changes during the crises. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities identified the change in the market state due to a crisis in both markets. The dynamic change of the Jaccard index can be used as an indicator of systemic risk or precursors of the crisis.

Developmental changes in the metabolic network of snapdragon flowers.

Directory of Open Access Journals (Sweden)

Joëlle K Muhlemann

Full Text Available Evolutionary and reproductive success of angiosperms, the most diverse group of land plants, relies on visual and olfactory cues for pollinator attraction. Previous work has focused on elucidating the developmental regulation of pathways leading to the formation of pollinator-attracting secondary metabolites such as scent compounds and flower pigments. However, to date little is known about how flowers control their entire metabolic network to achieve the highly regulated production of metabolites attracting pollinators. Integrative analysis of transcripts and metabolites in snapdragon sepals and petals over flower development performed in this study revealed a profound developmental remodeling of gene expression and metabolite profiles in petals, but not in sepals. Genes up-regulated during petal development were enriched in functions related to secondary metabolism, fatty acid catabolism, and amino acid transport, whereas down-regulated genes were enriched in processes involved in cell growth, cell wall formation, and fatty acid biosynthesis. The levels of transcripts and metabolites in pathways leading to scent formation were coordinately up-regulated during petal development, implying transcriptional induction of metabolic pathways preceding scent formation. Developmental gene expression patterns in the pathways involved in scent production were different from those of glycolysis and the pentose phosphate pathway, highlighting distinct developmental regulation of secondary metabolism and primary metabolic pathways feeding into it.

Globally homochiral assembly of two-dimensional molecular networks triggered by co-absorbers.

Science.gov (United States)

Chen, Ting; Yang, Wen-Hong; Wang, Dong; Wan, Li-Jun

2013-01-01

Understanding the chirality induction and amplification processes, and the construction of globally homochiral surfaces, represent essential challenges in surface chirality studies. Here we report the induction of global homochirality in two-dimensional enantiomorphous networks of achiral molecules via co-assembly with chiral co-absorbers. The scanning tunnelling microscopy investigations and molecular mechanics simulations demonstrate that the point chirality of the co-absorbers transfers to organizational chirality of the assembly units via enantioselective supramolecular interactions, and is then hierarchically amplified to the global homochirality of two-dimensional networks. The global homochirality of the network assembly shows nonlinear dependence on the enantiomeric excess of chiral co-absorber in the solution phase, demonstrating, for the first time, the validation of the 'majority rules' for the homochirality control of achiral molecules at the liquid/solid interface. Such an induction and nonlinear chirality amplification effect promises a new approach towards two-dimensional homochirality control and may reveal important insights into asymmetric heterogeneous catalysis, chiral separation and chiral crystallization.

Alignment of global supply networks based on strategic groups of supply chains

OpenAIRE

Nikos G. Moraitakis; Jiazhen Huo; Hans-Christian Pfohl

2017-01-01

Background: From a supply chain perspective, often big differences exist between global raw material suppliers’ approaches to supply their respective local markets. The progressing complexity of large centrally managed global supply networks and their often-unknown upstream ramifications increase the likelihood of undetected bottlenecks and inefficiencies. It is therefore necessary to develop an approach to strategically master the upstream complexity of such networks from a holistic su...

Competition between global and local online social networks

Science.gov (United States)

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-01

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Competition between global and local online social networks.

Science.gov (United States)

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-27

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

A simple model of global cascades on random networks

Science.gov (United States)

Watts, Duncan J.

2002-04-01

The origin of large but rare cascades that are triggered by small initial shocks is a phenomenon that manifests itself as diversely as cultural fads, collective action, the diffusion of norms and innovations, and cascading failures in infrastructure and organizational networks. This paper presents a possible explanation of this phenomenon in terms of a sparse, random network of interacting agents whose decisions are determined by the actions of their neighbors according to a simple threshold rule. Two regimes are identified in which the network is susceptible to very large cascadesherein called global cascadesthat occur very rarely. When cascade propagation is limited by the connectivity of the network, a power law distribution of cascade sizes is observed, analogous to the cluster size distribution in standard percolation theory and avalanches in self-organized criticality. But when the network is highly connected, cascade propagation is limited instead by the local stability of the nodes themselves, and the size distribution of cascades is bimodal, implying a more extreme kind of instability that is correspondingly harder to anticipate. In the first regime, where the distribution of network neighbors is highly skewed, it is found that the most connected nodes are far more likely than average nodes to trigger cascades, but not in the second regime. Finally, it is shown that heterogeneity plays an ambiguous role in determining a system's stability: increasingly heterogeneous thresholds make the system more vulnerable to global cascades; but an increasingly heterogeneous degree distribution makes it less vulnerable.

Future global SLR network evolution and its impact on the terrestrial reference frame

Science.gov (United States)

Kehm, Alexander; Bloßfeld, Mathis; Pavlis, Erricos C.; Seitz, Florian

2018-06-01

Satellite laser ranging (SLR) is an important technique that contributes to the determination of terrestrial geodetic reference frames, especially to the realization of the origin and the scale of global networks. One of the major limiting factors of SLR-derived reference frame realizations is the datum accuracy which significantly suffers from the current global SLR station distribution. In this paper, the impact of a potential future development of the SLR network on the estimated datum parameters is investigated. The current status of the SLR network is compared to a simulated potential future network featuring additional stations improving the global network geometry. In addition, possible technical advancements resulting in a higher amount of observations are taken into account as well. As a result, we find that the network improvement causes a decrease in the scatter of the network translation parameters of up to 24%, and up to 20% for the scale, whereas the technological improvement causes a reduction in the scatter of up to 27% for the translations and up to 49% for the scale. The Earth orientation parameters benefit by up to 15% from both effects.

The relation between global migration and trade networks

Science.gov (United States)

Sgrignoli, Paolo; Metulini, Rodolfo; Schiavo, Stefano; Riccaboni, Massimo

2015-01-01

In this paper we develop a methodology to analyze and compare multiple global networks, focusing our analysis on the relation between human migration and trade. First, we identify the subset of products for which the presence of a community of migrants significantly increases trade intensity, where to assure comparability across networks we apply a hypergeometric filter that lets us identify those links which intensity is significantly higher than expected. Next, proposing a new way to define country neighbors based on the most intense links in the trade network, we use spatial econometrics techniques to measure the effect of migration on international trade, while controlling for network interdependences. Overall, we find that migration significantly boosts trade across countries and we are able to identify product categories for which this effect is particularly strong.

Global Historical Climatology Network - Daily (GHCN-Daily), Version 3

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Historical Climatology Network - Daily (GHCN-Daily) dataset integrates daily climate observations from approximately 30 different data sources. Version 3...

Energetics of glucose metabolism: a phenomenological approach to metabolic network modeling.

Science.gov (United States)

Diederichs, Frank

2010-08-12

A new formalism to describe metabolic fluxes as well as membrane transport processes was developed. The new flux equations are comparable to other phenomenological laws. Michaelis-Menten like expressions, as well as flux equations of nonequilibrium thermodynamics, can be regarded as special cases of these new equations. For metabolic network modeling, variable conductances and driving forces are required to enable pathway control and to allow a rapid response to perturbations. When applied to oxidative phosphorylation, results of simulations show that whole oxidative phosphorylation cannot be described as a two-flux-system according to nonequilibrium thermodynamics, although all coupled reactions per se fulfill the equations of this theory. Simulations show that activation of ATP-coupled load reactions plus glucose oxidation is brought about by an increase of only two different conductances: a [Ca(2+)] dependent increase of cytosolic load conductances, and an increase of phosphofructokinase conductance by [AMP], which in turn becomes increased through [ADP] generation by those load reactions. In ventricular myocytes, this feedback mechanism is sufficient to increase cellular power output and O(2) consumption several fold, without any appreciable impairment of energetic parameters. Glucose oxidation proceeds near maximal power output, since transformed input and output conductances are nearly equal, yielding an efficiency of about 0.5. This conductance matching is fulfilled also by glucose oxidation of β-cells. But, as a price for the metabolic mechanism of glucose recognition, β-cells have only a limited capability to increase their power output.

A Global Network Alignment Method Using Discrete Particle Swarm Optimization.

Science.gov (United States)

Huang, Jiaxiang; Gong, Maoguo; Ma, Lijia

2016-10-19

Molecular interactions data increase exponentially with the advance of biotechnology. This makes it possible and necessary to comparatively analyse the different data at a network level. Global network alignment is an important network comparison approach to identify conserved subnetworks and get insight into evolutionary relationship across species. Network alignment which is analogous to subgraph isomorphism is known to be an NP-hard problem. In this paper, we introduce a novel heuristic Particle-Swarm-Optimization based Network Aligner (PSONA), which optimizes a weighted global alignment model considering both protein sequence similarity and interaction conservations. The particle statuses and status updating rules are redefined in a discrete form by using permutation. A seed-and-extend strategy is employed to guide the searching for the superior alignment. The proposed initialization method "seeds" matches with high sequence similarity into the alignment, which guarantees the functional coherence of the mapping nodes. A greedy local search method is designed as the "extension" procedure to iteratively optimize the edge conservations. PSONA is compared with several state-of-art methods on ten network pairs combined by five species. The experimental results demonstrate that the proposed aligner can map the proteins with high functional coherence and can be used as a booster to effectively refine the well-studied aligners.

Collaboration tools for the global accelerator network Workshop Report

CERN Document Server

Agarwal, D; Olson, J

2002-01-01

The concept of a ''Global Accelerator Network'' (GAN) has been put forward as a means for inter-regional collaboration in the operation of internationally constructed and operated frontier accelerator facilities. A workshop was held to allow representatives of the accelerator community and of the collaboratory development community to meet and discuss collaboration tools for the GAN environment. This workshop, called the Collaboration Tools for the Global Accelerator Network (GAN) Workshop, was held on August 26, 2002 at Lawrence Berkeley National Laboratory. The goal was to provide input about collaboration tools in general and to provide a strawman for the GAN collaborative tools environment. The participants at the workshop represented accelerator physicists, high-energy physicists, operations, technology tool developers, and social scientists that study scientific collaboration.

Collaboration tools for the global accelerator network: Workshop Report

International Nuclear Information System (INIS)

Agarwal, Deborah; Olson, Gary; Olson, Judy

2002-01-01

The concept of a ''Global Accelerator Network'' (GAN) has been put forward as a means for inter-regional collaboration in the operation of internationally constructed and operated frontier accelerator facilities. A workshop was held to allow representatives of the accelerator community and of the collaboratory development community to meet and discuss collaboration tools for the GAN environment. This workshop, called the Collaboration Tools for the Global Accelerator Network (GAN) Workshop, was held on August 26, 2002 at Lawrence Berkeley National Laboratory. The goal was to provide input about collaboration tools in general and to provide a strawman for the GAN collaborative tools environment. The participants at the workshop represented accelerator physicists, high-energy physicists, operations, technology tool developers, and social scientists that study scientific collaboration

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

Directory of Open Access Journals (Sweden)

Jorge Fernandez-de-Cossio-Diaz

2017-11-01

Full Text Available In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

Representation of global and national conservation priorities by Colombia's Protected Area Network.

Science.gov (United States)

Forero-Medina, German; Joppa, Lucas

2010-10-12

How do national-level actions overlap with global priorities for conservation? Answering this question is especially important in countries with high and unique biological diversity like Colombia. Global biodiversity schemes provide conservation guidance at a large scale, while national governments gazette land for protection based on a combination of criteria at regional or local scales. Information on how a protected area network represents global and national conservation priorities is crucial for finding gaps in coverage and for future expansion of the system. We evaluated the agreement of Colombia's protected area network with global conservation priorities, and the extent to which the network reflects the country's biomes, species richness, and common environmental and physical conditions. We used this information to identify priority biomes for conservation. We find the dominant strategy in Colombia has been a proactive one, allocating the highest proportion of protected land on intact, difficult to access and species rich areas like the Amazon. Threatened and unique areas are disproportionately absent from Colombia's protected lands. We highlight six biomes in Colombia as conservation priorities that should be considered in any future expansion of Colombia's protected area network. Two of these biomes have less than 3% of their area protected and more than 70% of their area transformed for human use. One has less than 3% protected and high numbers of threatened vertebrates. Three biomes fall in both categories. Expansion of Colombia's Protected Area Network should consider the current representativeness of the network. We indicate six priority biomes that can contribute to improving the representation of threatened species and biomes in Colombia.

Global Talent Management in Multinational Corporations and the Role of Social Networks

NARCIS (Netherlands)

Ruel, Hubertus Johannes Maria; Bondarouk, Tatiana; Dresselhaus, Lena; Olivas-Lujan, M.R.; Bondarouk, T.V.

2013-01-01

Purpose — Current global business challenges and circumstances are responsible for the need for global talent management (GTM) within multinational corporations (MNCs). Social media and networks are becoming key channels for global communication and collaboration. For GTM in MNCs, an effective usage

Competition, transmission and pattern evolution: A network analysis of global oil trade

International Nuclear Information System (INIS)

Zhang, Hai-Ying; Ji, Qiang; Fan, Ying

2014-01-01

This paper studies the competition among oil importers using complex network theory, combined with several alternative measures of competition intensity, to analyze the evolution of the pattern and transmission of oil-trading competition. The results indicate that oil trade has formed a global competition pattern and that the role played by the Asian-Pacific region in the evolution of this competition pattern is becoming increasingly prominent. In addition, global competition intensity has continued to rise, and non-OECD countries have become the main driving force for this increase in global competition intensity. The large oil importers are the most significant parts of the global oil-trading competition pattern. They are not only the major participants in the competition for oil resources but also play important roles in the transmission of oil-trading competition. China and the United States especially display the feature of globalization, whose impacts of transmission reach across the whole oil-trading competition network. Finally, a “5C” (changeability, contestability, cooperation, commitment and circumstances) policy framework is put forward to maintain the stability of oil trade and improve the energy security of oil importers in various aspects. - Highlights: • An oil-trading competition network is constructed using complex network theory. • Oil trade has formed a global competition pattern and its intensity has kept rising. • The status of the Asian-Pacific region in the competition pattern becomes prominent. • Large oil importers play important roles in transmitting the trading competition. • A “5C” policy framework is put forward to cope with the intensive competition

Sierra Stars Observatory Network: An Accessible Global Network

Science.gov (United States)

Williams, Richard; Beshore, Edward

2011-03-01

The Sierra Stars Observatory Network (SSON) is a unique partnership among professional observatories that provides its users with affordable high-quality calibrated image data. SSON comprises observatories in the Northern and Southern Hemisphere and is in the process of expanding to a truly global network capable of covering the entire sky 24 hours a day in the near future. The goal of SSON is to serve the needs of science-based projects and programs. Colleges, universities, institutions, and individuals use SSON for their education and research projects. The mission of SSON is to promote and expand the use of its facilities among the thousands of colleges and schools worldwide that do not have access to professional-quality automated observatory systems to use for astronomy education and research. With appropriate leadership and guidance educators can use SSON to help teach astronomy and do meaningful scientific projects. The relatively small cost of using SSON for this type of work makes it affordable and accessible for educators to start using immediately. Remote observatory services like SSON need to evolve to better support education and research initiatives of colleges, institutions and individual investigators. To meet these needs, SSON is developing a sophisticated interactive scheduling system to integrate among the nodes of the observatory network. This will enable more dynamic observations, including immediate priority interrupts, acquiring moving objects using ephemeris data, and more.

The role of “network of cities” in construction of global urban culture

OpenAIRE

Baycan-Levent, Tüzin; Kundak, Seda; Gülümser, Aliye Ahu

2004-01-01

The globalization process has led to an increased interaction between cities and to a new urban system/network in which they need to be competitive and complementary at the same time. “Network of cities”, such as World Cities, Eurocities or Sister Cities are among the well known examples of interaction and cooperation of the cities at the regional and global level. The cities of different regions and countries tend to share their experiences and their cultures within these networks in order t...

Computers and networks in the age of globalization

DEFF Research Database (Denmark)

Bloch Rasmussen, Leif; Beardon, Colin; Munari, Silvio

In modernity, an individual identity was constituted from civil society, while in a globalized network society, human identity, if it develops at all, must grow from communal resistance. A communal resistance to an abstract conceptualized world, where there is no possibility for perception and ex...

Global Nuclear Safety and Security Network

International Nuclear Information System (INIS)

Guo Lingquan

2013-01-01

The objectives of the Regulatory Network are: - to contribute to the effectiveness of nuclear regulatory systems; - to contribute to continuous enhancements, and - to achieve and promote radiation and nuclear safety and security by: • Enhancing the effectiveness and efficiency of international cooperation in the regulation of nuclear and radiation safety of facilities and activities; • Enabling adequate access by regulators to relevant safety and security information; • Promoting dissemination of information on safety and security issues as well as information of good practices for addressing and resolving these issues; • Enabling synergies among different web based networks with a view to strengthening and enhancing the global nuclear safety framework and serving the specific needs of regulators and international organizations; • Providing additional information to the public on international regulatory cooperation in safety and security matters

Correlation and network topologies in global and local stock indices

DEFF Research Database (Denmark)

Nobi, A.; Lee, S.; Kim, D. H.

2014-01-01

the crises. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities identified the change in the market state due to a crisis in both markets. The dynamic change of the Jaccard index can be used as an indicator of systemic risk......We examined how the correlation and network structure of the global indices and local Korean indices have changed during years 2000-2012. The average correlations of the global indices increased with time, while the local indices showed a decreasing trend except for drastic changes during...... or precursors of the crisis. (C) 2014 Elsevier B.V. All rights reserved....

TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

Directory of Open Access Journals (Sweden)

Jensen Paul A

2011-09-01

Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

The necessity of a theory of biology for tissue engineering: metabolism-repair systems.

Science.gov (United States)

Ganguli, Suman; Hunt, C Anthony

2004-01-01

Since there is no widely accepted global theory of biology, tissue engineering and bioengineering lack a theoretical understanding of the systems being engineered. By default, tissue engineering operates with a "reductionist" theoretical approach, inherited from traditional engineering of non-living materials. Long term, that approach is inadequate, since it ignores essential aspects of biology. Metabolism-repair systems are a theoretical framework which explicitly represents two "functional" aspects of living organisms: self-repair and self-replication. Since repair and replication are central to tissue engineering, we advance metabolism-repair systems as a potential theoretical framework for tissue engineering. We present an overview of the framework, and indicate directions to pursue for extending it to the context of tissue engineering. We focus on biological networks, both metabolic and cellular, as one such direction. The construction of these networks, in turn, depends on biological protocols. Together these concepts may help point the way to a global theory of biology appropriate for tissue engineering.

Global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms

International Nuclear Information System (INIS)

Wang Jian; Lu Junguo

2008-01-01

In this paper, we study the global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms. By constructing a suitable Lyapunov functional and utilizing some inequality techniques, we obtain a sufficient condition for the uniqueness and global exponential stability of the equilibrium solution for a class of fuzzy cellular neural networks with delays and reaction-diffusion terms. The result imposes constraint conditions on the network parameters independently of the delay parameter. The result is also easy to check and plays an important role in the design and application of globally exponentially stable fuzzy neural circuits

SONG-China Project: A Global Automated Observation Network

Science.gov (United States)

Yang, Z. Z.; Lu, X. M.; Tian, J. F.; Zhuang, C. G.; Wang, K.; Deng, L. C.

2017-09-01

Driven by advancements in technology and scientific objectives, data acquisition in observational astronomy has been changed greatly in recent years. Fully automated or even autonomous ground-based network of telescopes has now become a tendency for time-domain observational projects. The Stellar Observations Network Group (SONG) is an international collaboration with the participation and contribution of the Chinese astronomy community. The scientific goal of SONG is time-domain astrophysics such as asteroseismology and open cluster research. The SONG project aims to build a global network of 1 m telescopes equipped with high-precision and high-resolution spectrographs, and two-channel lucky-imaging cameras. It is the Chinese initiative to install a 50 cm binocular photometry telescope at each SONG node sharing the network platform and infrastructure. This work is focused on design and implementation in technology and methodology of SONG/50BiN, a typical ground-based network composed of multiple sites and a variety of instruments.

Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

Directory of Open Access Journals (Sweden)

Tommi Aho

2010-05-01

Full Text Available Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our

A global interaction network maps a wiring diagram of cellular function

Science.gov (United States)

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

New paradigms for metabolic modeling of human cells

DEFF Research Database (Denmark)

Mardinoglu, Adil; Nielsen, Jens

2015-01-01

review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally......, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented.......Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we...

Indications of marine bioinvasion from network theory. An analysis of the global cargo ship network

Science.gov (United States)

Kölzsch, A.; Blasius, B.

2011-12-01

The transport of huge amounts of small aquatic organisms in the ballast tanks and at the hull of large cargo ships leads to ever increasing rates of marine bioinvasion. In this study, we apply a network theoretic approach to examine the introduction of invasive species into new ports by global shipping. This is the first stage of the invasion process where it is still possible to intervene with regulating measures. We compile a selection of widely used and newly developed network properties and apply these to analyse the structure and spread characteristics of the directed and weighted global cargo ship network (GCSN). Our results reveal that the GCSN is highly efficient, shows small world characteristics and is positive assortative, indicating that quick spread of invasive organisms between ports is likely. The GCSN shows strong community structure and contains two large communities, the Atlantic and Pacific trading groups. Ports that appear as connector hubs and are of high centralities are the Suez and Panama Canal, Singapore and Shanghai. Furthermore, from robustness analyses and the network's percolation behaviour, we evaluate differences of onboard and in-port ballast water treatment, set them into context with previous studies and advise bioinvasion management strategies.

Global synchronization of general delayed complex networks with stochastic disturbances

International Nuclear Information System (INIS)

Tu Li-Lan

2011-01-01

In this paper, global synchronization of general delayed complex networks with stochastic disturbances, which is a zero-mean real scalar Wiener process, is investigated. The networks under consideration are continuous-time networks with time-varying delay. Based on the stochastic Lyapunov stability theory, Ito's differential rule and the linear matrix inequality (LMI) optimization technique, several delay-dependent synchronous criteria are established, which guarantee the asymptotical mean-square synchronization of drive networks and response networks with stochastic disturbances. The criteria are expressed in terms of LMI, which can be easily solved using the Matlab LMI Control Toolbox. Finally, two examples show the effectiveness and feasibility of the proposed synchronous conditions. (general)

Global asymptotic stability of Cohen-Grossberg neural networks with constant and variable delays

International Nuclear Information System (INIS)

Wu Wei; Cui Baotong; Huang Min

2007-01-01

Global asymptotic stability of Cohen-Grossberg neural networks with constant and variable delays is studied. Some sufficient conditions for the neural networks are proposed to guarantee the global asymptotic convergence by using different Lyapunov functionals. Our criteria represent an extension of the existing results in literatures. A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed Cohen-Grossberg neural networks. Those conditions are less restrictive than those given in the earlier reference

Development of an internet based system for modeling biotin metabolism using Bayesian networks.

Science.gov (United States)

Zhou, Jinglei; Wang, Dong; Schlegel, Vicki; Zempleni, Janos

2011-11-01

Biotin is an essential water-soluble vitamin crucial for maintaining normal body functions. The importance of biotin for human health has been under-appreciated but there is plenty of opportunity for future research with great importance for human health. Currently, carrying out predictions of biotin metabolism involves tedious manual manipulations. In this paper, we report the development of BiotinNet, an internet based program that uses Bayesian networks to integrate published data on various aspects of biotin metabolism. Users can provide a combination of values on the levels of biotin related metabolites to obtain the predictions on other metabolites that are not specified. As an inherent feature of Bayesian networks, the uncertainty of the prediction is also quantified and reported to the user. This program enables convenient in silico experiments regarding biotin metabolism, which can help researchers design future experiments while new data can be continuously incorporated. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Approach on a global HTGR R and D network

International Nuclear Information System (INIS)

Lensa, W. von

1997-01-01

The present situation of nuclear power in general and of the innovative nuclear reactor systems in particular requires more comprehensive, coordinated R and D efforts on a broad international level to respond to today's requirements with respect to public and economic acceptance as well as to globalization trends and global environmental problems. HTGR technology development has already reached a high degree of maturity that will be complemented by the operation of the two new test reactors in Japan and China, representing technological milestones for the demonstration of HTGR safety characteristics and Nuclear Process Heat generation capabilities. It is proposed by the IAEA 'International Working Group on Gas-Cooled Reactors' to establish a 'Global HTGR R and D Network' on basic HTGR technology for the stable, long-term advancement of the specific HTGR features and as a basis for the future market introduction of this innovative reactor system. The background and the motivation for this approach are illustrated, as well as first proposals on the main objectives, the structure and the further procedures for the implementation of such a multinational working sharing R and D network. Modern telecooperation methods are foreseen as an interactive tool for effective communication and collaboration on a global scale. (author)

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

Science.gov (United States)

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

Global exponential stability of mixed discrete and distributively delayed cellular neural network

International Nuclear Information System (INIS)

Yao Hong-Xing; Zhou Jia-Yan

2011-01-01

This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point, then by employing the Lyapunov—Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays, in addition, the example is provided to illustrate the applicability of the result. (general)

Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

NARCIS (Netherlands)

Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.

2016-01-01

Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes

Cerebral energy metabolism and the brain's functional network architecture: an integrative review.

Science.gov (United States)

Lord, Louis-David; Expert, Paul; Huckins, Jeremy F; Turkheimer, Federico E

2013-09-01

Recent functional magnetic resonance imaging (fMRI) studies have emphasized the contributions of synchronized activity in distributed brain networks to cognitive processes in both health and disease. The brain's 'functional connectivity' is typically estimated from correlations in the activity time series of anatomically remote areas, and postulated to reflect information flow between neuronal populations. Although the topological properties of functional brain networks have been studied extensively, considerably less is known regarding the neurophysiological and biochemical factors underlying the temporal coordination of large neuronal ensembles. In this review, we highlight the critical contributions of high-frequency electrical oscillations in the γ-band (30 to 100 Hz) to the emergence of functional brain networks. After describing the neurobiological substrates of γ-band dynamics, we specifically discuss the elevated energy requirements of high-frequency neural oscillations, which represent a mechanistic link between the functional connectivity of brain regions and their respective metabolic demands. Experimental evidence is presented for the high oxygen and glucose consumption, and strong mitochondrial performance required to support rhythmic cortical activity in the γ-band. Finally, the implications of mitochondrial impairments and deficits in glucose metabolism for cognition and behavior are discussed in the context of neuropsychiatric and neurodegenerative syndromes characterized by large-scale changes in the organization of functional brain networks.

MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

Science.gov (United States)

Kelley, James J; Maor, Shay; Kim, Min Kyung; Lane, Anatoliy; Lun, Desmond S

2017-08-15

Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. dslun@rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The global health network on alcohol control: successes and limits of evidence-based advocacy.

Science.gov (United States)

Schmitz, Hans Peter

2016-04-01

Global efforts to address alcohol harm have significantly increased since the mid-1990 s. By 2010, the World Health Organization (WHO) had adopted the non-binding Global Strategy to Reduce the Harmful Use of Alcohol. This study investigates the role of a global health network, anchored by the Global Alcohol Policy Alliance (GAPA), which has used scientific evidence on harm and effective interventions to advocate for greater global public health efforts to reduce alcohol harm. The study uses process-tracing methodology and expert interviews to evaluate the accomplishments and limitations of this network. The study documents how network members have not only contributed to greater global awareness about alcohol harm, but also advanced a public health approach to addressing this issue at the global level. Although the current network represents an expanding global coalition of like-minded individuals, it faces considerable challenges in advancing its cause towards successful implementation of effective alcohol control policies across many low- and middle-income countries (LMICs). The analysis reveals a need to transform the network into a formal coalition of regional and national organizations that represent a broader variety of constituents, including the medical community, consumer groups and development-focused non-governmental organizations. Considering the growing harm of alcohol abuse in LMICs and the availability of proven and cost-effective public health interventions, alcohol control represents an excellent 'buy' for donors interested in addressing non-communicable diseases. Alcohol control has broad beneficial effects for human development, including promoting road safety and reducing domestic violence and health care costs across a wide variety of illnesses caused by alcohol consumption. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2015; all rights reserved.

Global efficiency of local immunization on complex networks.

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Hébert-Dufresne, Laurent; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J

2013-01-01

Epidemics occur in all shapes and forms: infections propagating in our sparse sexual networks, rumours and diseases spreading through our much denser social interactions, or viruses circulating on the Internet. With the advent of large databases and efficient analysis algorithms, these processes can be better predicted and controlled. In this study, we use different characteristics of network organization to identify the influential spreaders in 17 empirical networks of diverse nature using 2 epidemic models. We find that a judicious choice of local measures, based either on the network's connectivity at a microscopic scale or on its community structure at a mesoscopic scale, compares favorably to global measures, such as betweenness centrality, in terms of efficiency, practicality and robustness. We also develop an analytical framework that highlights a transition in the characteristic scale of different epidemic regimes. This allows to decide which local measure should govern immunization in a given scenario.

Global efficiency of local immunization on complex networks

Science.gov (United States)

Hébert-Dufresne, Laurent; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J.

2013-07-01

Epidemics occur in all shapes and forms: infections propagating in our sparse sexual networks, rumours and diseases spreading through our much denser social interactions, or viruses circulating on the Internet. With the advent of large databases and efficient analysis algorithms, these processes can be better predicted and controlled. In this study, we use different characteristics of network organization to identify the influential spreaders in 17 empirical networks of diverse nature using 2 epidemic models. We find that a judicious choice of local measures, based either on the network's connectivity at a microscopic scale or on its community structure at a mesoscopic scale, compares favorably to global measures, such as betweenness centrality, in terms of efficiency, practicality and robustness. We also develop an analytical framework that highlights a transition in the characteristic scale of different epidemic regimes. This allows to decide which local measure should govern immunization in a given scenario.

The Theoretical Aspects of the Development of Global Production Networks and Value Chains: the New Paradigm of Globalization

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Cherkas Nataliia I.

2018-03-01

Full Text Available The article is aimed at systematizing the contemporary perceptions of the changing paradigms of globalization and international competition as a result of the spread of global networks and value chains. The development of global value chains (GVC occurred as a result of two distributions of globalization: (1 global competition is manifested at the level of sectors and companies (from the mid-nineteenth century (2 the concept of trade in tasks arises (at the end of XX century. The publication analyzes the impact of globalization on the international competitiveness of both the EU and the developing countries in the trade of final products and tasks. The model takes into consideration differences in wages, technology gap and trade costs, and provides for assessing the comparative advantages of individual sectors or segments of GVC. Features of the conception of global production networks have been identified as: «imports for production» and «imports for exports», which define international competitiveness on the basis of creation of the intrinsic value added. It is determined that the competitiveness of the economy is determined by the country’s positions in the GVC, and the increase in productivity of companies depends on their involvement in the segments (tasks with a high level of value added.

Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

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Matthew B Biggs

2017-03-01

Full Text Available Genome-scale metabolic network reconstructions (GENREs are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA. We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model

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Kese Pontes Freitas Alberton

2015-01-01

Full Text Available This work proposes a procedure for simultaneous parameters identifiability and estimation in metabolic networks in order to overcome difficulties associated with lack of experimental data and large number of parameters, a common scenario in the modeling of such systems. As case study, the complex real problem of parameters identifiability of the Escherichia coli K-12 W3110 dynamic model was investigated, composed by 18 differential ordinary equations and 35 kinetic rates, containing 125 parameters. With the procedure, model fit was improved for most of the measured metabolites, achieving 58 parameters estimated, including 5 unknown initial conditions. The results indicate that simultaneous parameters identifiability and estimation approach in metabolic networks is appealing, since model fit to the most of measured metabolites was possible even when important measures of intracellular metabolites and good initial estimates of parameters are not available.

Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy.

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Quinn, Robert A; Nothias, Louis-Felix; Vining, Oliver; Meehan, Michael; Esquenazi, Eduardo; Dorrestein, Pieter C

2017-02-01

Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine. Copyright © 2016. Published by Elsevier Ltd.

Global exponential stability of reaction-diffusion recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Liang Jinling; Cao Jinde

2003-01-01

Employing general Halanay inequality, we analyze the global exponential stability of a class of reaction-diffusion recurrent neural networks with time-varying delays. Several new sufficient conditions are obtained to ensure existence, uniqueness and global exponential stability of the equilibrium point of delayed reaction-diffusion recurrent neural networks. The results extend and improve the earlier publications. In addition, an example is given to show the effectiveness of the obtained result

Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks

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Liu, Jun; Wang, Gang; Duan, Ling-Yu; Abdiyeva, Kamila; Kot, Alex C.

2018-04-01

Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, Long Short-Term Memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynamics in sequential data. As not all skeletal joints are informative for action recognition, and the irrelevant joints often bring noise which can degrade the performance, we need to pay more attention to the informative ones. However, the original LSTM network does not have explicit attention ability. In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition. This network is capable of selectively focusing on the informative joints in each frame of each skeleton sequence by using a global context memory cell. To further improve the attention capability of our network, we also introduce a recurrent attention mechanism, with which the attention performance of the network can be enhanced progressively. Moreover, we propose a stepwise training scheme in order to train our network effectively. Our approach achieves state-of-the-art performance on five challenging benchmark datasets for skeleton based action recognition.

Global stability of a susceptible-infected-susceptible epidemic model on networks with individual awareness

International Nuclear Information System (INIS)

Li Ke-Zan; Xu Zhong-Pu; Zhu Guang-Hu; Ding Yong

2014-01-01

Recent research results indicate that individual awareness can play an important influence on epidemic spreading in networks. By local stability analysis, a significant conclusion is that the embedded awareness in an epidemic network can increase its epidemic threshold. In this paper, by using limit theory and dynamical system theory, we further give global stability analysis of a susceptible-infected-susceptible (SIS) epidemic model on networks with awareness. Results show that the obtained epidemic threshold is also a global stability condition for its endemic equilibrium, which implies the embedded awareness can enhance the epidemic threshold globally. Some numerical examples are presented to verify the theoretical results. (interdisciplinary physics and related areas of science and technology)

XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks.

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Zaretzki, Jed; Matlock, Matthew; Swamidass, S Joshua

2013-12-23

Understanding how xenobiotic molecules are metabolized is important because it influences the safety, efficacy, and dose of medicines and how they can be modified to improve these properties. The cytochrome P450s (CYPs) are proteins responsible for metabolizing 90% of drugs on the market, and many computational methods can predict which atomic sites of a molecule--sites of metabolism (SOMs)--are modified during CYP-mediated metabolism. This study improves on prior methods of predicting CYP-mediated SOMs by using new descriptors and machine learning based on neural networks. The new method, XenoSite, is faster to train and more accurate by as much as 4% or 5% for some isozymes. Furthermore, some "incorrect" predictions made by XenoSite were subsequently validated as correct predictions by revaluation of the source literature. Moreover, XenoSite output is interpretable as a probability, which reflects both the confidence of the model that a particular atom is metabolized and the statistical likelihood that its prediction for that atom is correct.

Sustaining a Global Social Network: a quasi-experimental study.

Science.gov (United States)

Benton, D C; Ferguson, S L

2017-03-01

To examine the longer term impact on the social network of participating nurses in the Global Nursing Leadership Institute (GNLI2013) through using differing frequencies of follow-up to assess impact on maintenance of network cohesion. Social network analysis is increasingly been used by nurse researchers, however, studies tend to use single point-in-time descriptive methods. This study utilizes a repeated measures, block group, control-intervention, quasi-experimental design. Twenty-eight nurse leaders, competitively selected through a double-blind peer review process, were allocated to five action learning-based learning groups. Network architecture, measures of cohesion and node degree frequency were all used to assess programme impact. The programme initiated and sustained connections between nurse leaders drawn from a geographically dispersed heterogeneous group. Modest inputs of two to three e-mails over a 6-month period seem sufficient to maintain connectivity as indicated by measures of network density, diameter and path length. Due to the teaching methodology used, the study sample was relatively small and the follow-up data collection took place after a relatively short time. Replication and further cohort data collection would be advantageous. In an era where many policy solutions are being debated and initiated at the global level, action learning leadership development that utilizes new technology follow-up appears to show significant impact and is worthy of wider application. The approach warrants further inquiry and testing as to its longer term effects on nursing's influence on policy formulation and implementation. © 2016 International Council of Nurses.

Global robust exponential stability for interval neural networks with delay

International Nuclear Information System (INIS)

Cui Shihua; Zhao Tao; Guo Jie

2009-01-01

In this paper, new sufficient conditions for globally robust exponential stability of neural networks with either constant delays or time-varying delays are given. We show the sufficient conditions for the existence, uniqueness and global robust exponential stability of the equilibrium point by employing Lyapunov stability theory and linear matrix inequality (LMI) technique. Numerical examples are given to show the approval of our results.

Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

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Kovaleva Galina

2011-06-01

Full Text Available Abstract Background Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. Results To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR, numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp. Conclusions We tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S

Beyond the network effect: towards an alternative understanding of global urban organizations

NARCIS (Netherlands)

James, P.; Verrest, H.; Gupta, J.; Pfeffer, K.; Verrest, H.; Ros-Tonen, M.

2015-01-01

Global organizations providing network relations for cities are bourgeoning. Organizations such as Metropolis, UN-Habitat, ICLEI - Local Governments for Sustainability, the Global Compact Cities Programme, and the C40, as well as City-to-City arrangements, have become increasingly important to

The Pan-University Network for Global Health: framework for collaboration and review of global health needs.

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Winchester, M S; BeLue, R; Oni, T; Wittwer-Backofen, U; Deobagkar, D; Onya, H; Samuels, T A; Matthews, S A; Stone, C; Airhihenbuwa, C

2016-04-21

In the current United Nations efforts to plan for post 2015-Millennium Development Goals, global partnership to address non-communicable diseases (NCDs) has become a critical goal to effectively respond to the complex global challenges of which inequity in health remains a persistent challenge. Building capacity in terms of well-equipped local researchers and service providers is a key to bridging the inequity in global health. Launched by Penn State University in 2014, the Pan University Network for Global Health responds to this need by bridging researchers at more than 10 universities across the globe. In this paper we outline our framework for international and interdisciplinary collaboration, as well the rationale for our research areas, including a review of these two themes. After its initial meeting, the network has established two central thematic priorities: 1) urbanization and health and 2) the intersection of infectious diseases and NCDs. The urban population in the global south will nearly double in 25 years (approx. 2 billion today to over 3.5 billion by 2040). Urban population growth will have a direct impact on global health, and this growth will be burdened with uneven development and the persistence of urban spatial inequality, including health disparities. The NCD burden, which includes conditions such as hypertension, stroke, and diabetes, is outstripping infectious disease in countries in the global south that are considered to be disproportionately burdened by infectious diseases. Addressing these two priorities demands an interdisciplinary and multi-institutional model to stimulate innovation and synergy that will influence the overall framing of research questions as well as the integration and coordination of research.

Coupling Strength and System Size Induce Firing Activity of Globally Coupled Neural Network

International Nuclear Information System (INIS)

Wei Duqu; Luo Xiaoshu; Zou Yanli

2008-01-01

We investigate how firing activity of globally coupled neural network depends on the coupling strength C and system size N. Network elements are described by space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values of parameters at which no firing activity occurs. It is found that for a given appropriate coupling strength, there is an intermediate range of system size where the firing activity of globally coupled SCFHN neural network is induced and enhanced. On the other hand, for a given intermediate system size level, there exists an optimal value of coupling strength such that the intensity of firing activity reaches its maximum. These phenomena imply that the coupling strength and system size play a vital role in firing activity of neural network

Find_tfSBP: find thermodynamics-feasible and smallest balanced pathways with high yield from large-scale metabolic networks.

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Xu, Zixiang; Sun, Jibin; Wu, Qiaqing; Zhu, Dunming

2017-12-11

Biologically meaningful metabolic pathways are important references in the design of industrial bacterium. At present, constraint-based method is the only way to model and simulate a genome-scale metabolic network under steady-state criteria. Due to the inadequate assumption of the relationship in gene-enzyme-reaction as one-to-one unique association, computational difficulty or ignoring the yield from substrate to product, previous pathway finding approaches can't be effectively applied to find out the high yield pathways that are mass balanced in stoichiometry. In addition, the shortest pathways may not be the pathways with high yield. At the same time, a pathway, which exists in stoichiometry, may not be feasible in thermodynamics. By using mixed integer programming strategy, we put forward an algorithm to identify all the smallest balanced pathways which convert the source compound to the target compound in large-scale metabolic networks. The resulting pathways by our method can finely satisfy the stoichiometric constraints and non-decomposability condition. Especially, the functions of high yield and thermodynamics feasibility have been considered in our approach. This tool is tailored to direct the metabolic engineering practice to enlarge the metabolic potentials of industrial strains by integrating the extensive metabolic network information built from systems biology dataset.

Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI.

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Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T

2012-10-15

Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. Copyright © 2012 Elsevier Inc. All rights reserved.

Analysing the Outbound logistics process enhancements in Nokia-Siemens Networks Global Distribution Center

OpenAIRE

Marjeta, Katri

2011-01-01

Marjeta, Katri. 2011. Analysing the outbound logistics process enhancements in Nokia-Siemens Networks Global Distribution Center. Master´s thesis. Kemi-Tornio University of Applied Sciences. Business and Culture. Pages 57. Due to confidentiality issues, this work has been modified from its original form. The aim of this Master Thesis work is to describe and analyze the outbound logistics process enhancement projects executed in Nokia-Siemens Networks Global Distribution Center after the N...

The Transition from Alliance Networks to Multilateral Alliances in the Global Airline Industry

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Sergio G. Lazzarini

2008-01-01

Full Text Available This study examines conditions in which alliance networks (informal webs of bilateral entanglements between firms may or may not evolve into multilateral alliances (broad, formal multiple-firm arrangements. I offer a theory to explain the formation of multilateral alliances based on both the resource profile and the structure of existing interfirm networks, and provide an initial test of that theory in the context of the global airline industry. Using data from 75 global airlines and their alliances, I propose a methodology to retrieve samples of alliance networks and then use regression analysis to assess how the resource profile and the structure of these networks influence their formalization into multilateral alliances. I find that multilateral alliances are more likely to emerge when alliance networks exhibit high resource diversity and network structure characterized by moderate density and high centralization. Apparently, while highly sparse networks reduce actors’ awareness of their potential joint collaboration, highly dense or embedded networks substitute for the need for formal controls accompanying multilateral agreements. The effect of centralization suggests that the formation of multilateral alliances tends to be triggered by leading actors directly connected to other network members.

Ecological network analysis for carbon metabolism of eco-industrial parks: a case study of a typical eco-industrial park in Beijing.

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Lu, Yi; Chen, Bin; Feng, Kuishuang; Hubacek, Klaus

2015-06-16

Energy production and industrial processes are crucial economic sectors accounting for about 62% of greenhouse gas (GHG) emissions globally in 2012. Eco-industrial parks are practical attempts to mitigate GHG emissions through cooperation among businesses and the local community in order to reduce waste and pollution, efficiently share resources, and help with the pursuit of sustainable development. This work developed a framework based on ecological network analysis to trace carbon metabolic processes in eco-industrial parks and applied it to a typical eco-industrial park in Beijing. Our findings show that the entire metabolic system is dominated by supply of primary goods from the external environment and final demand. The more carbon flows through a sector, the more influence it would exert upon the whole system. External environment and energy providers are the most active and dominating part of the carbon metabolic system, which should be the first target to mitigate emissions by increasing efficiencies. The carbon metabolism of the eco-industrial park can be seen as an evolutionary system with high levels of efficiency, but this may come at the expense of larger levels of resilience. This work may provide a useful modeling framework for low-carbon design and management of industrial parks.

Integrated in silico Analyses of Regulatory and Metabolic Networks of Synechococcus sp. PCC 7002 Reveal Relationships between Gene Centrality and Essentiality

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Hyun-Seob Song

2015-03-01

Full Text Available Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as “topologically important.” Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termed as “functionally important” genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.

Inferring general relations between network characteristics from specific network ensembles.

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Cardanobile, Stefano; Pernice, Volker; Deger, Moritz; Rotter, Stefan

2012-01-01

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their ability to generate networks with large structural variability. In particular, we consider the statistical constraints which the respective construction scheme imposes on the generated networks. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This makes it possible to infer global features from local ones using regression models trained on networks with high generalization power. Our results confirm and extend previous findings regarding the synchronization properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks in good approximation. Finally, we demonstrate on three different data sets (C. elegans neuronal network, R. prowazekii metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models.

A novel strategy involved in [corrected] anti-oxidative defense: the conversion of NADH into NADPH by a metabolic network.

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Ranji Singh

Full Text Available The reduced nicotinamide adenine dinucleotide phosphate (NADPH is pivotal to the cellular anti-oxidative defence strategies in most organisms. Although its production mediated by different enzyme systems has been relatively well-studied, metabolic networks dedicated to the biogenesis of NADPH have not been fully characterized. In this report, a metabolic pathway that promotes the conversion of reduced nicotinamide adenine dinucleotide (NADH, a pro-oxidant into NADPH has been uncovered in Pseudomonas fluorescens exposed to oxidative stress. Enzymes such as pyruvate carboxylase (PC, malic enzyme (ME, malate dehydrogenase (MDH, malate synthase (MS, and isocitrate lyase (ICL that are involved in disparate metabolic modules, converged to create a metabolic network aimed at the transformation of NADH into NADPH. The downregulation of phosphoenol carboxykinase (PEPCK and the upregulation of pyruvate kinase (PK ensured that this metabolic cycle fixed NADH into NADPH to combat the oxidative stress triggered by the menadione insult. This is the first demonstration of a metabolic network invoked to generate NADPH from NADH, a process that may be very effective in combating oxidative stress as the increase of an anti-oxidant is coupled to the decrease of a pro-oxidant.

Novel global robust stability criterion for neural networks with delay

International Nuclear Information System (INIS)

Singh, Vimal

2009-01-01

A novel criterion for the global robust stability of Hopfield-type interval neural networks with delay is presented. An example illustrating the improvement of the present criterion over several recently reported criteria is given.

Differential network analysis reveals evolutionary complexity in secondary metabolism of Rauvolfia serpentina over Catharanthus roseus

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Shivalika Pathania

2016-08-01

Full Text Available Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Towards these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These mechanisms may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of Rauvolfia serpentina, and key genes that contribute towards diversification of specific metabolites.

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus.

Science.gov (United States)

Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S

2016-01-01

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.

Local communities obstruct global consensus: Naming game on multi-local-world networks

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Lou, Yang; Chen, Guanrong; Fan, Zhengping; Xiang, Luna

2018-02-01

Community structure is essential for social communications, where individuals belonging to the same community are much more actively interacting and communicating with each other than those in different communities within the human society. Naming game, on the other hand, is a social communication model that simulates the process of learning a name of an object within a community of humans, where the individuals can generally reach global consensus asymptotically through iterative pair-wise conversations. The underlying network indicates the relationships among the individuals. In this paper, three typical topologies, namely random-graph, small-world and scale-free networks, are employed, which are embedded with the multi-local-world community structure, to study the naming game. Simulations show that (1) the convergence process to global consensus is getting slower as the community structure becomes more prominent, and eventually might fail; (2) if the inter-community connections are sufficiently dense, neither the number nor the size of the communities affects the convergence process; and (3) for different topologies with the same (or similar) average node-degree, local clustering of individuals obstruct or prohibit global consensus to take place. The results reveal the role of local communities in a global naming game in social network studies.

Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis.

Science.gov (United States)

Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

2016-05-10

In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as "responding biomarkers" by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress.

Adenylate Kinase and AMP Signaling Networks: Metabolic Monitoring, Signal Communication and Body Energy Sensing

Directory of Open Access Journals (Sweden)

Andre Terzic

2009-04-01

Full Text Available Adenylate kinase and downstream AMP signaling is an integrated metabolic monitoring system which reads the cellular energy state in order to tune and report signals to metabolic sensors. A network of adenylate kinase isoforms (AK1-AK7 are distributed throughout intracellular compartments, interstitial space and body fluids to regulate energetic and metabolic signaling circuits, securing efficient cell energy economy, signal communication and stress response. The dynamics of adenylate kinase-catalyzed phosphotransfer regulates multiple intracellular and extracellular energy-dependent and nucleotide signaling processes, including excitation-contraction coupling, hormone secretion, cell and ciliary motility, nuclear transport, energetics of cell cycle, DNA synthesis and repair, and developmental programming. Metabolomic analyses indicate that cellular, interstitial and blood AMP levels are potential metabolic signals associated with vital functions including body energy sensing, sleep, hibernation and food intake. Either low or excess AMP signaling has been linked to human disease such as diabetes, obesity and hypertrophic cardiomyopathy. Recent studies indicate that derangements in adenylate kinase-mediated energetic signaling due to mutations in AK1, AK2 or AK7 isoforms are associated with hemolytic anemia, reticular dysgenesis and ciliary dyskinesia. Moreover, hormonal, food and antidiabetic drug actions are frequently coupled to alterations of cellular AMP levels and associated signaling. Thus, by monitoring energy state and generating and distributing AMP metabolic signals adenylate kinase represents a unique hub within the cellular homeostatic network.

Astroglial Metabolic Networks Sustain Hippocampal Synaptic Transmission

Science.gov (United States)

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-01

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Astroglial metabolic networks sustain hippocampal synaptic transmission.

Science.gov (United States)

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-05

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Network Fictions and the Global Unhomely

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Aris Mousoutzanis

2016-04-01

Full Text Available The paper suggests that the increasing proliferation of network fictions in literature, film, television and the internet may be interpreted through a theoretical framework that reconceptuallises the originally strictly psychoanalytic concept of the 'Unheimlich' (Freud’s idea of the ‘unhomely’ or ‘uncanny’ within the context of political, economic and cultural disources fo globalisation. ‘Network fictions’ are those texts consisting of multiple interlocking narratives set in various times and places that explore the interconnections of characters and events across different storylines: novels such as William Gibson’s 'Pattern Recognition' (2003, Hari Kunzro’s 'Transmission' (2005 and 'Gods Without Men' (2011, David Mitchell’s 'Cloud Atlas' (2004, or Rana Dasgupta’s 'Tokyo Cancelled' (2005 are some examples. My argument is that central to these fictions is a sense of a ‘global unhomely’. The sense of displacement, unhomeliness and global mobility that is conveyed in these fictions is fundamental to the experience of the 'Unheimlich'. In addition, the ability of the concept to convey a combined sense of the familiar and the strange is useful in exploring the ways in which these fictions engage with theoretical debates on globalisation that perceive the interaction between global flows and local cultures either in terms of homogenisation and uniformity or of heterogenisation and hybridity. Moreover, the repetitive temporality of the 'Unheimlich' is another distinctive aspect that allows a reading of the disjunctive, non-linear temporal structure of these fictions from this perspective. The ‘repetition compulsion’, however, that Freud considered to be an example of uncanniness was also theorised by him as a post-traumatic symptom, and this implicit association of uncanniness with post-traumatic experience also allows to interpret the persistent preoccupation of these fictions with suffering and disaster, as well as

Rhinal hypometabolism on FDG PET in healthy APO-E4 carriers: impact on memory function and metabolic networks

International Nuclear Information System (INIS)

Didic, Mira; Felician, Olivier; Gour, Natalina; Ceccaldi, Mathieu; Bernard, Rafaelle; Pecheux, Christophe; Mundler, Olivier; Guedj, Eric

2015-01-01

The ε4 allele of the apolipoprotein E (APO-E4) gene, a genetic risk factor for Alzheimer's disease (AD), also modulates brain metabolism and function in healthy subjects. The aim of the present study was to explore cerebral metabolism using FDG PET in healthy APO-E4 carriers by comparing cognitively normal APO-E4 carriers to noncarriers and to assess if patterns of metabolism are correlated with performance on cognitive tasks. Moreover, metabolic connectivity patterns were established in order to assess if the organization of neural networks is influenced by genetic factors. Whole-brain PET statistical analysis was performed at voxel-level using SPM8 with a threshold of p < 0.005, corrected for volume, with age, gender and level of education as nuisance variables. Significant hypometabolism between APO-E4 carriers (n = 11) and noncarriers (n = 30) was first determined. Mean metabolic values with clinical/neuropsychological data were extracted at the individual level, and correlations were searched using Spearman's rank test in the whole group. To evaluate metabolic connectivity from metabolic cluster(s) previously identified in the intergroup comparison, voxel-wise interregional correlation analysis (IRCA) was performed between groups of subjects. APO-E4 carriers had reduced metabolism within the left anterior medial temporal lobe (MTL), where neuropathological changes first appear in AD, including the entorhinal and perirhinal cortices. A correlation between metabolism in this area and performance on the DMS48 (delayed matching to sample-48 items) was found, in line with converging evidence involving the perirhinal cortex in object-based memory. Finally, a voxel-wise IRCA revealed stronger metabolic connectivity of the MTL cluster with neocortical frontoparietal regions in carriers than in noncarriers, suggesting compensatory metabolic networks. Exploring cerebral metabolism using FDG PET can contribute to a better understanding of the influence of

Rhinal hypometabolism on FDG PET in healthy APO-E4 carriers: impact on memory function and metabolic networks

Energy Technology Data Exchange (ETDEWEB)

Didic, Mira; Felician, Olivier; Gour, Natalina; Ceccaldi, Mathieu [Pole de Neurosciences Cliniques, Centre Hospitalo-Universitaire de la Timone, AP-HM, Service de Neurologie and Neuropsychologie, Marseille (France); Aix Marseille Universite, Inserm, INS UMRS 1106, Marseille (France); Bernard, Rafaelle; Pecheux, Christophe [Centre Hospitalo-Universitaire de la Timone, AP-HM, et INSERM UMRS 910: ' ' Genetique Medicale et Genomique fonctionnelle' ' , Departement de Genetique Medicale, Marseille (France); Mundler, Olivier; Guedj, Eric [Centre Hospitalo-Universitaire de la Timone, AP-HM, Service Central de Biophysique et Medecine Nucleaire, Marseille (France); Aix Marseille Universite, CERIMED, CNRS UMR7289, INT, Marseille (France); Aix Marseille Universite, CNRS UMR7289, INT, Marseille (France)

2015-09-15

The ε4 allele of the apolipoprotein E (APO-E4) gene, a genetic risk factor for Alzheimer's disease (AD), also modulates brain metabolism and function in healthy subjects. The aim of the present study was to explore cerebral metabolism using FDG PET in healthy APO-E4 carriers by comparing cognitively normal APO-E4 carriers to noncarriers and to assess if patterns of metabolism are correlated with performance on cognitive tasks. Moreover, metabolic connectivity patterns were established in order to assess if the organization of neural networks is influenced by genetic factors. Whole-brain PET statistical analysis was performed at voxel-level using SPM8 with a threshold of p < 0.005, corrected for volume, with age, gender and level of education as nuisance variables. Significant hypometabolism between APO-E4 carriers (n = 11) and noncarriers (n = 30) was first determined. Mean metabolic values with clinical/neuropsychological data were extracted at the individual level, and correlations were searched using Spearman's rank test in the whole group. To evaluate metabolic connectivity from metabolic cluster(s) previously identified in the intergroup comparison, voxel-wise interregional correlation analysis (IRCA) was performed between groups of subjects. APO-E4 carriers had reduced metabolism within the left anterior medial temporal lobe (MTL), where neuropathological changes first appear in AD, including the entorhinal and perirhinal cortices. A correlation between metabolism in this area and performance on the DMS48 (delayed matching to sample-48 items) was found, in line with converging evidence involving the perirhinal cortex in object-based memory. Finally, a voxel-wise IRCA revealed stronger metabolic connectivity of the MTL cluster with neocortical frontoparietal regions in carriers than in noncarriers, suggesting compensatory metabolic networks. Exploring cerebral metabolism using FDG PET can contribute to a better understanding of the influence of

Only (Dis-)Connect: Pentecostal Global Networking as Revelation and Concealment

OpenAIRE

Coleman, Simon

2013-01-01

Contemporary forms of Pentecostalism, such as that of the Faith Movement, are often represented as inherently global, constituting a religion ‘made to travel’ and to missionize across the world. I argue that while much attention has been paid to proselytization as a catalyst in encouraging transnational activities among such Christians, more analysis is needed of how Pentecostalists represent each other in the construction of global imaginaries. The imagined and enacted networks that result a...

Power and Networks in Worldwide Knowledge Coordination: The Case of Global Science

Science.gov (United States)

King, Roger

2011-01-01

The article considers the global governance of knowledge systems, exploring concepts of power, networks, standards (defined as normative practices), and structuration. The focus is on science as a form of predominantly private global governance, particularly the self-regulatory and collaborative processes stretching across time and space. These…

Global Asymptotic Stability of Switched Neural Networks with Delays

Directory of Open Access Journals (Sweden)

Zhenyu Lu

2015-01-01

Full Text Available This paper investigates the global asymptotic stability of a class of switched neural networks with delays. Several new criteria ensuring global asymptotic stability in terms of linear matrix inequalities (LMIs are obtained via Lyapunov-Krasovskii functional. And here, we adopt the quadratic convex approach, which is different from the linear and reciprocal convex combinations that are extensively used in recent literature. In addition, the proposed results here are very easy to be verified and complemented. Finally, a numerical example is provided to illustrate the effectiveness of the results.

Building dynamic capabilities in large global advertising agency networks: managing the shift from mass communication to digital interactivity

DEFF Research Database (Denmark)

Suheimat, Wisam; Prætorius, Thim; Brambini-Pedersen, Jan Vang

2018-01-01

Interactive digital technologies result in significant managerial challenges for the largest global advertising agency networks. This paper, based on original data from in-depth case research in three of the largest global advertising networks, investigates how advertising agency networks manage...

Comparing biological networks via graph compression

Directory of Open Access Journals (Sweden)

Hayashida Morihiro

2010-09-01

Full Text Available Abstract Background Comparison of various kinds of biological data is one of the main problems in bioinformatics and systems biology. Data compression methods have been applied to comparison of large sequence data and protein structure data. Since it is still difficult to compare global structures of large biological networks, it is reasonable to try to apply data compression methods to comparison of biological networks. In existing compression methods, the uniqueness of compression results is not guaranteed because there is some ambiguity in selection of overlapping edges. Results This paper proposes novel efficient methods, CompressEdge and CompressVertices, for comparing large biological networks. In the proposed methods, an original network structure is compressed by iteratively contracting identical edges and sets of connected edges. Then, the similarity of two networks is measured by a compression ratio of the concatenated networks. The proposed methods are applied to comparison of metabolic networks of several organisms, H. sapiens, M. musculus, A. thaliana, D. melanogaster, C. elegans, E. coli, S. cerevisiae, and B. subtilis, and are compared with an existing method. These results suggest that our methods can efficiently measure the similarities between metabolic networks. Conclusions Our proposed algorithms, which compress node-labeled networks, are useful for measuring the similarity of large biological networks.

A global genetic interaction network maps a wiring diagram of cellular function.

Science.gov (United States)

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D; Pelechano, Vicent; Styles, Erin B; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F; Li, Sheena C; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; San Luis, Bryan-Joseph; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M; Moore, Claire L; Rosebrock, Adam P; Caudy, Amy A; Myers, Chad L; Andrews, Brenda; Boone, Charles

2016-09-23

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. Copyright © 2016, American Association for the Advancement of Science.

Global existence of periodic solutions of BAM neural networks with variable coefficients

International Nuclear Information System (INIS)

Guo Shangjiang; Huang Lihong; Dai Binxiang; Zhang Zhongzhi

2003-01-01

In this Letter, we study BAM (bidirectional associative memory) networks with variable coefficients. By some spectral theorems and a continuation theorem based on coincidence degree, we not only obtain some new sufficient conditions ensuring the existence, uniqueness, and global exponential stability of the periodic solution but also estimate the exponentially convergent rate. Our results are less restrictive than previously known criteria and can be applied to neural networks with a broad range of activation functions assuming neither differentiability nor strict monotonicity. Moreover, these conclusions are presented in terms of system parameters and can be easily verified for the globally Lipschitz and the spectral radius being less than 1. Therefore, our results should be useful in the design and applications of periodic oscillatory neural circuits for neural networks with delays

REMOTE OPERATIONS IN A GLOBAL ACCELERATOR NETWORK

International Nuclear Information System (INIS)

PEGGS, S.; SATOGATA, T.; AGARWAL, D.; RICE, D.

2003-01-01

The INTRODUCTION to this paper summarizes the history of the Global Accelerator Network (GAN) concept and the recent workshops that discussed the relationship between GAN and Remote Operations. The REMOTE OPERATIONS SCENARIOS section brings out the organizational philosophy embodied in GAN-like and to non-GAN-like scenarios. The set of major TOPICS RAISED AT THE WORKSHOPS are only partially resolved. COLLABORATION TOOLS are described and discussed, followed by examples of REMOTE ACCELERATOR CONTROL PROJECTS around the world

Remote operations in a global accelerator network

International Nuclear Information System (INIS)

Peggs, Steve; Satogata, Todd; Agarwal, Deborah; Rice, David

2003-01-01

The INTRODUCTION to this paper summarizes the history of the Global Accelerator Network (GAN) concept and the recent workshops that discussed the relationship between GAN and Remote Operations. The REMOTE OPERATIONS SCENARIOS section brings out the organizational philosophy embodied in GAN-like and to non-GAN-like scenarios. The set of major TOPICS RAISED AT THE WORKSHOPS are only partially resolved. COLLABORATION TOOLS are described and discussed, followed by examples of REMOTE ACCELERATOR CONTROL PROJECTS around the world

REMOTE OPERATIONS IN A GLOBAL ACCELERATOR NETWORK.

Energy Technology Data Exchange (ETDEWEB)

PEGGS,S.; SATOGATA,T.; AGARWAL,D.; RICE,D.

2003-05-12

The INTRODUCTION to this paper summarizes the history of the Global Accelerator Network (GAN) concept and the recent workshops that discussed the relationship between GAN and Remote Operations. The REMOTE OPERATIONS SCENARIOS section brings out the organizational philosophy embodied in GAN-like and to non-GAN-like scenarios. The set of major TOPICS RAISED AT THE WORKSHOPS are only partially resolved. COLLABORATION TOOLS are described and discussed, followed by examples of REMOTE ACCELERATOR CONTROL PROJECTS around the world.

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

Energy Technology Data Exchange (ETDEWEB)

Anderson-Teixeira, Kristina J. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Davies, Stuart J. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; National Museum of Natural History, Washington, DC (United States). Dept. of Botany; Bennett, Amy C. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Gonzalez-Akre, Erika B. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Muller-Landau, Helene C. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Joseph Wright, S. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Abu Salim, Kamariah [Univ. of Brunei Darussalam, Bandar Seri Begawan (Brunei). Faculty of Science. Environmental and Life Sciences; Almeyda Zambrano, Angélica M. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Stanford Univ., CA (United States). Stanford Woods Inst. for the Environment; Univ. of Alabama, Tuscaloosa, AL (United States). Dept. of Geography; Alonso, Alfonso [Smithsonian Conservation Biology Inst., Washington, DC (United States). National Zoological Park. Center for Conservation Education and Sustainability; Baltzer, Jennifer L. [Wilfrid Laurier Univ., Waterloo, ON (Canada). Dept. of Biology; Basset, Yves [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Bourg, Norman A. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Broadbent, Eben N. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Stanford Univ., CA (United States). Stanford Woods Inst. for the Environment; Univ. of Alabama, Tuscaloosa, AL (United States). Dept. of Geography; Brockelman, Warren Y. [Mahidol Univ., Bangkok (Thailand). Dept. of Biology; Bunyavejchewin, Sarayudh [Dept. of National Parks, Wildlife and Plant Conservation, Bangkok (Thailand). Research Office; Burslem, David F. R. P. [Univ. of Aberdeen (United Kingdom). School of Biological Sciences; Butt, Nathalie [Univ. of Queensland, St. Lucia (Australia). School of Biological Sciences; Univ. of Oxford (United Kingdom). School of Geography and the Environment. Environmental Change Inst.; Cao, Min [Chinese Academy of Sciences (CAS), Kunming (China). Xishuangbanna Tropical Botanical Garden. Key Lab. of Tropical Forest Ecology; Cardenas, Dairon [Sinchi Amazonic Inst. of Scientific Research, Bogota (Colombia); Chuyong, George B. [Univ. of Buea (Cameroon). Dept. of Botany and Plant Physiology; Clay, Keith [Indiana Univ., Bloomington, IN (United States). Dept. of Biology; Cordell, Susan [USDA Forest Service, Hilo, HI (United States). Inst. of Pacific Islands Forestry; Dattaraja, Handanakere S. [Indian Inst. of Science, Bangalore (India). Centre for Ecological Sciences; Deng, Xiaobao [Chinese Academy of Sciences (CAS), Kunming (China). Xishuangbanna Tropical Botanical Garden. Key Lab. of Tropical Forest Ecology; Detto, Matteo [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Du, Xiaojun [Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Botany; Duque, Alvaro [Univ. Nacional de Colombia, Medellin (Colombia). Dept. de Ciencias Forestales; Erikson, David L. [National Museum of Natural History, Washington, DC (United States). Dept. of Botany; Ewango, Corneille E. N. [Okapi Wildlife Reserve, Epulu (Democratic Republic of the Congo). Centre de Formation et de Recherche en Conservation Forestiere (CEFRECOF); Fischer, Gunter A. [Kadoorie Farm and Botanic Garden, Tai Po, Hong Kong (China); Fletcher, Christine [Forest Research Inst. Malaysia (FRIM), Selangor (Malaysia); Foster, Robin B. [The Field Museum, Chicago, IL (United States). Botany Dept.; Giardina, Christian P. [USDA Forest Service, Hilo, HI (United States). Inst. of Pacific Islands Forestry; Gilbert, Gregory S. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Univ. of California, Santa Cruz, CA (United States). Environmental Studies Dept.; Gunatilleke, Nimal [Univ. of Peradeniya (Sri Lanka). Faculty of Science. Dept. of Botany; Gunatilleke, Savitri [Univ. of Peradeniya (Sri Lanka). Faculty of Science. Dept. of Botany; Hao, Zhanqing [Chinese Academy of Sciences (CAS), Shenyang (China). State Key Lab. of Forest and Soil Ecology. Inst. of Applied Ecology; Hargrove, William W. [USDA-Forest Service Station Headquarters, Asheville, NC (United States). Eastern Forest Environmental Threat Assessment Center; Hart, Terese B. [Lukuru Wildlife Research Foundation, Kinshasa (Democratic Republic of the Congo). Tshuapa-Lomami-Lualaba Project; Hau, Billy C. H. [Univ. of Hong Kong (China). School of Biological Sciences. Kadoorie Inst.; He, Fangliang [Univ. of Alberta, Edmonton, AB (Canada). Dept. of Renewable Resources; Hoffman, Forrest M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Earth Sciences Group; Howe, Robert W. [Univ. of Wisconsin, Green Bay, WI (United States). Dept. of Natural and Applied Sciences; Hubbell, Stephen P. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Univ. of California, Los Angeles, CA (United States). Dept. of Ecology and Evolutionary Biology; Inman-Narahari, Faith M. [Univ. of Hawaii, Honolulu, HI (United States). College of Tropical Agriculture and Human Resources; Jansen, Patrick A. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Wageningen Univ. (Netherlands). Resource Ecology Group; Jiang, Mingxi [Chinese Academy of Sciences (CAS), Wuhan (China). Wuhan Botanical Garden; Johnson, Daniel J. [Indiana Univ., Bloomington, IN (United States). Dept. of Biology; Kanzaki, Mamoru [Kyoto Univ. (Japan). Graduate School of Agriculture; Kassim, Abdul Rahman [Forest Research Inst. Malaysia (FRIM), Selangor (Malaysia); Kenfack, David [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; National Museum of Natural History, Washington, DC (United States). Dept. of Botany; Kibet, Staline [National Museums of Kenya, Nairobi (Kenya); Univ. of Nairobi (Kenya). Land Resource Management and Agricultural Technology Dept.; Kinnaird, Margaret F. [Mpala Research Centre, Nanyuki (Kenya); Wildlife Conservation Society, New York, NY (United States). Global Conservation Programs; Korte, Lisa [Smithsonian Conservation Biology Inst., Washington, DC (United States). National Zoological Park. Center for Conservation Education and Sustainability; Kral, Kamil [Silva Tarouca Research Inst., Brno (Czech Republic). Dept. of Forest Ecology; Kumar, Jitendra [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Earth Sciences Group; Larson, Andrew J. [Univ. of Montana, Missoula, MT (United States). College of Forestry and Conservation. Dept. of Forest Management; Li, Yide [Chinese Academy of Forestry, Guangzhou (China). Research Inst. of Tropical Forestry; Li, Xiankun [Chinese Academy of Sciences (CAS), Guilin (China). Guangxi Inst. of Botany; Liu, Shirong [Chinese Academy of Forestry, Beijing (China). Research Inst. of Forest Ecology, Environment and Protection; Lum, Shawn K. Y. [Nanyang Technological Univ. (Singapore). National Inst. of Education. Natural Sciences and Science Education Academic Group; Lutz, James A. [Utah State Univ., Logan, UT (United States). Wildland Resources Dept.; Ma, Keping [Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Botany; Maddalena, Damian M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Earth Sciences Group; Makana, Jean-Remy [Wildlife Conservation Society, Brazzaville (Democratic Republic of the Congo); Malhi, Yadvinder [Univ. of Oxford (United Kingdom). School of Geography and the Environment. Environmental Change Inst.; Marthews, Toby [Univ. of Oxford (United Kingdom). School of Geography and the Environment. Environmental Change Inst.; Mat Serudin, Rafizah [Univ. of Brunei Darussalam, Bandar Seri Begawan (Brunei). Faculty of Science. Environmental and Life Sciences; McMahon, Sean M. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Smithsonian Environmental Research Center, Edgewater, MD (United States). Forest Ecology Group; McShea, William J. [Smithsonian Conservation Biology Inst., Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Memiaghe, Hervé R. [Inst. de Recherche en Ecologie Tropicale, Libreville (Gabon). Centre National de la Recherche Scientifique et Technologique; Mi, Xiangcheng [Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Botany; Mizuno, Takashi [Kyoto Univ. (Japan). Graduate School of Agriculture; Morecroft, Michael [Natural England, Sheffield (United Kingdom); Myers, Jonathan A. [Washington Univ., St. Louis, MO (United States). Dept. of Biology; Novotny, Vojtech [New Guinea Binatang Research Centre, Madang (Papua New Guinea); Univ. of South Bohemia, Ceske Budejovice (Czech Republic). Academy of Sciences of the Czech Republic. Faculty of Science. Biology Centre; de Oliveira, Alexandre A. [Univ. of Sao Paulo (Brazil). Inst. of Biosciences. Ecology Dept.; Ong, Perry S. [Univ. of the Philippines Diliman, Quezon City (Philippines). Inst. of Biology; Orwig, David A. [Harvard Univ., Petersham, MA (United States). Harvard Forest; Ostertag, Rebecca [Univ. of Hawaii, Hilo, HI (United States). Dept. of Biology; den Ouden, Jan [Wageningen Univ. (Netherlands). Forest Ecology and Forest Management Group; Parker, Geoffrey G. [Smithsonian Environmental Research Center, Edgewater, MD (United States). Forest Ecology Group; Phillips, Richard P. [Indiana Univ., Bloomington, IN (United States). Dept. of Biology; Sack, Lawren [Univ. of California, Los Angeles, CA (United States). Dept. of Ecology and Evolutionary Biology; Sainge, Moses N. [Tropical Plant Exploration Group (TroPEG), Mundemba (Cameroon); Sang, Weiguo [Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Botany; Sri-ngernyuang, Kriangsak [Maejo Univ., Chiang Mai (Thailand). Faculty of Architecture and Environmental Design; Sukumar, Raman [Indian Inst. of Science, Bangalore (India). Centre for Ecological Sciences; Sun, I-Fang [National Dong Hwa Univ., Hualian (Taiwan). Dept. of Natural Resources and Environmental Studies; Sungpalee, Witchaphart [Maejo Univ., Chiang Mai (Thailand). Faculty of Architecture and Environmental Design; Suresh, Hebbalalu Sathyanarayana [Indian Inst. of Science, Bangalore (India). Centre for Ecological Sciences; Tan, Sylvester [Sarawak Forest Dept., Kuching (Malaysia); Thomas, Sean C. [Univ. of Toronto, ON (Canada). Faculty of Forestry; Thomas, Duncan W. [Washington State Univ., Vancouver, WA (United States). School of Biological Sciences; Thompson, Jill [Centre for Ecology and Hydrology, Penicuik, Scotland (United Kingdom); Univ. of Puerto Rico Rio Pedras, San Juan (Puerto Rico). Dept. of Environmental Science. Inst. for Tropical Ecosystem Studies; Turner, Benjamin L. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Uriarte, Maria [Columbia Univ., New York, NY (United States). Dept. of Ecology, Evolution and Environmental Biology; Valencia, Renato [Pontifical Catholic Univ. of Ecuador, Quito (Ecuador). Dept. of Biological Sciences; Vallejo, Marta I. [Inst. Alexander von Humboldt, Bogota (Colombia); Vicentini, Alberto [National Inst. of Amazonian Research (INPA), Manaus (Brazil); Vrška, Tomáš [Silva Tarouca Research Inst., Brno (Czech Republic). Dept. of Forest Ecology; Wang, Xihua [East China Normal Univ. (ECNU), Shanghai (China). School of Ecological and Environmental Sciences; Wang, Xugao [Lukuru Wildlife Research Foundation, Kinshasa (Democratic Republic of the Congo). Tshuapa-Lomami-Lualaba Project; Weiblen, George [Univ. of Minnesota, St. Paul, MN (United States). Dept. of Plant Biology; Wolf, Amy [Univ. of Wisconsin, Green Bay, WI (United States). Dept. of Biology. Dept. of Natural and Applied Sciences; Xu, Han [Chinese Academy of Forestry, Guangzhou (China). Research Inst. of Tropical Forestry; Yap, Sandra [Univ. of the Philippines Diliman, Quezon City (Philippines). Inst. of Biology; Zimmerman, Jess [Univ. of Puerto Rico Rio Piedras, San Juan (Puerto Rico). Dept. of Environmental Science. Inst. for Tropical Ecosystem Studies

2014-09-25

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services, including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamic research sites useful for characterizing forest responses to global change. The broad suite of measurements made at the CTFS-ForestGEO sites make it possible to investigate the complex ways in which global change is impacting forest dynamics. ongoing research across the network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in a era of global change

EnzDP: improved enzyme annotation for metabolic network reconstruction based on domain composition profiles.

Science.gov (United States)

Nguyen, Nam-Ninh; Srihari, Sriganesh; Leong, Hon Wai; Chong, Ket-Fah

2015-10-01

Determining the entire complement of enzymes and their enzymatic functions is a fundamental step for reconstructing the metabolic network of cells. High quality enzyme annotation helps in enhancing metabolic networks reconstructed from the genome, especially by reducing gaps and increasing the enzyme coverage. Currently, structure-based and network-based approaches can only cover a limited number of enzyme families, and the accuracy of homology-based approaches can be further improved. Bottom-up homology-based approach improves the coverage by rebuilding Hidden Markov Model (HMM) profiles for all known enzymes. However, its clustering procedure relies firmly on BLAST similarity score, ignoring protein domains/patterns, and is sensitive to changes in cut-off thresholds. Here, we use functional domain architecture to score the association between domain families and enzyme families (Domain-Enzyme Association Scoring, DEAS). The DEAS score is used to calculate the similarity between proteins, which is then used in clustering procedure, instead of using sequence similarity score. We improve the enzyme annotation protocol using a stringent classification procedure, and by choosing optimal threshold settings and checking for active sites. Our analysis shows that our stringent protocol EnzDP can cover up to 90% of enzyme families available in Swiss-Prot. It achieves a high accuracy of 94.5% based on five-fold cross-validation. EnzDP outperforms existing methods across several testing scenarios. Thus, EnzDP serves as a reliable automated tool for enzyme annotation and metabolic network reconstruction. Available at: www.comp.nus.edu.sg/~nguyennn/EnzDP .

Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks

DEFF Research Database (Denmark)

Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.

2012-01-01

the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results...

Global exponential stability for reaction-diffusion recurrent neural networks with multiple time varying delays

International Nuclear Information System (INIS)

Lou, X.; Cui, B.

2008-01-01

In this paper we consider the problem of exponential stability for recurrent neural networks with multiple time varying delays and reaction-diffusion terms. The activation functions are supposed to be bounded and globally Lipschitz continuous. By means of Lyapunov functional, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network. Finally, a numerical example is given to show the correctness of our analysis. (author)

The Global Environment Radiation Monitoring Network (GERMON)

International Nuclear Information System (INIS)

Zakheim, B.J.; Goellner, D.A.

1994-01-01

Following the Chernobyl accident in 1986, a group of experts from the World Health Organization (WHO) and the United Nations Environment Program (UNEP) met in France to discuss and develop the basic principles of a global environmental radiation monitoring network (GERMON). The basic functions of this network were to provide regular reports on environmental radiation levels and to be in a position to provide reliable and accurate radiation measurements on a quick and accurate radiation measurements on a quick turnaround basis in the event of a major radiation release. By 1992, although 58 countries had indicated an interest in becoming a part of the GERMON system, only 16 were providing data on a regular basis. This paper traces the history of GERMON from its inception in 1987 through its activities during 1993-4. It details the objectives of the network, describes functions, lists its participants, and presents obstacles in the current network. The paper examines the data requirements for radiological emergency preparedness and offers suggestions for the current system. The paper also describes the growing need for such a network. To add a domestic perspective, the authors present a summary of the environmental monitoring information system that was used by the NRC in 1986 in its analyses of the Chernobyl incident. Then we will use this 1986 experience to propose a method for the use of GERMON should a similar occasion arise in the future

Experimental observation of chimera and cluster states in a minimal globally coupled network

Energy Technology Data Exchange (ETDEWEB)

Hart, Joseph D. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Physics, University of Maryland, College Park, Maryland 20742 (United States); Bansal, Kanika [Department of Mathematics, University at Buffalo, SUNY Buffalo, New York 14260 (United States); US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005 (United States); Murphy, Thomas E. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742 (United States); Roy, Rajarshi [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Physics, University of Maryland, College Park, Maryland 20742 (United States); Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742 (United States)

2016-09-15

A “chimera state” is a dynamical pattern that occurs in a network of coupled identical oscillators when the symmetry of the oscillator population is broken into synchronous and asynchronous parts. We report the experimental observation of chimera and cluster states in a network of four globally coupled chaotic opto-electronic oscillators. This is the minimal network that can support chimera states, and our study provides new insight into the fundamental mechanisms underlying their formation. We use a unified approach to determine the stability of all the observed partially synchronous patterns, highlighting the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization. Our approach is general in terms of network size and connectivity. We also find that chimera states often appear in regions of multistability between global, cluster, and desynchronized states.

Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome

Science.gov (United States)

Kim, Woonsu; Park, Hyesun; Seo, Seongwon

2016-01-01

The sequence of cattle genome provided a valuable opportunity to systematically link genetic and metabolic traits of cattle. The objectives of this study were 1) to reconstruct genome-scale cattle-specific metabolic pathways based on the most recent and updated cattle genome build and 2) to identify duplicated metabolic genes in the cattle genome for better understanding of metabolic adaptations in cattle. A bioinformatic pipeline of an organism for amalgamating genomic annotations from multiple sources was updated. Using this, an amalgamated cattle genome database based on UMD_3.1, was created. The amalgamated cattle genome database is composed of a total of 33,292 genes: 19,123 consensus genes between NCBI and Ensembl databases, 8,410 and 5,493 genes only found in NCBI or Ensembl, respectively, and 266 genes from NCBI scaffolds. A metabolic reconstruction of the cattle genome and cattle pathway genome database (PGDB) was also developed using Pathway Tools, followed by an intensive manual curation. The manual curation filled or revised 68 pathway holes, deleted 36 metabolic pathways, and added 23 metabolic pathways. Consequently, the curated cattle PGDB contains 304 metabolic pathways, 2,460 reactions including 2,371 enzymatic reactions, and 4,012 enzymes. Furthermore, this study identified eight duplicated genes in 12 metabolic pathways in the cattle genome compared to human and mouse. Some of these duplicated genes are related with specific hormone biosynthesis and detoxifications. The updated genome-scale metabolic reconstruction is a useful tool for understanding biology and metabolic characteristics in cattle. There has been significant improvements in the quality of cattle genome annotations and the MetaCyc database. The duplicated metabolic genes in the cattle genome compared to human and mouse implies evolutionary changes in the cattle genome and provides a useful information for further research on understanding metabolic adaptations of cattle. PMID

Forced disappearance in an era of globalization: biopolitics, shadow networks, and imagined worlds.

Science.gov (United States)

Rozema, Ralph

2011-01-01

In this article, I argue that the practice of forced disappearance of persons on the part of paramilitary groups has become linked to specific processes of globalization. Global flows related to biopolitics, global crime networks, and dehumanizing imaginations reproduced by mass media together constitute a driving force behind forced disappearances. Drawing on ethnographic fieldwork in the Colombian city of Medellín, I analyze how these global flows interact with local armed actors, helping create a climate conducive to forced disappearance. These mechanisms in Colombia show similarities to those in some African and Asian countries. Gaining insight into the mechanisms behind forced disappearance may help prevent it from occurring in the future. Enhancing social inclusion of residents, unraveling the transnational crime networks in which perpetrators are involved, and disseminating rehumanizing images of victims all contribute to curbing the practice of forced disappearance.

Application of random matrix theory to biological networks

Energy Technology Data Exchange (ETDEWEB)

Luo Feng [Department of Computer Science, Clemson University, 100 McAdams Hall, Clemson, SC 29634 (United States); Department of Pathology, U.T. Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390-9072 (United States); Zhong Jianxin [Department of Physics, Xiangtan University, Hunan 411105 (China) and Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)]. E-mail: zhongjn@ornl.gov; Yang Yunfeng [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Scheuermann, Richard H. [Department of Pathology, U.T. Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390-9072 (United States); Zhou Jizhong [Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019 (United States) and Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)]. E-mail: zhouj@ornl.gov

2006-09-25

We show that spectral fluctuation of interaction matrices of a yeast protein-protein interaction network and a yeast metabolic network follows the description of the Gaussian orthogonal ensemble (GOE) of random matrix theory (RMT). Furthermore, we demonstrate that while the global biological networks evaluated belong to GOE, removal of interactions between constituents transitions the networks to systems of isolated modules described by the Poisson distribution. Our results indicate that although biological networks are very different from other complex systems at the molecular level, they display the same statistical properties at network scale. The transition point provides a new objective approach for the identification of functional modules.

The global historical climatology network: Long-term monthly temperature, precipitation, and pressure data

International Nuclear Information System (INIS)

Vose, R.S.; Schmoyer, R.L.; Peterson, T.C.; Steurer, P.M.; Heim, R.R. Jr.; Karl, T.R.; Eischeid, J.K.

1992-01-01

Interest in global climate change has risen dramatically during the past several decades. In a similar fashion, the number of data sets available to study global change has also increased. Unfortunately, many different organizations and researchers have compiled these data sets, making it confusing and time consuming for individuals to acquire the most comprehensive data. In response to this rapid growth in the number of global data sets, DOE's Carbon Dioxide Information Analysis Center (CDIAC) and NOAA's National Climatic Data Center (NCDC) established the Global Historical Climatology Network (GHCN) project. The purpose of this project is to compile an improved data set of long-term monthly mean temperature, precipitation, sea level pressure, and station pressure for as dense a network of global stations as possible. Specifically, the GHCN project seeks to consolidate the numerous preexisting national-, regional-, and global-scale data sets into a single global data base; to subject the data to rigorous quality control; and to update, enhance, and distribute the data set at regular intervals. The purpose of this paper is to describe the compilation and contents of the GHCN data base (i.e., GHCN Version 1.0)

Linking metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways.

Directory of Open Access Journals (Sweden)

Adam M Wentzell

2007-09-01

Full Text Available Phenotypic variation between individuals of a species is often under quantitative genetic control. Genomic analysis of gene expression polymorphisms between individuals is rapidly gaining popularity as a way to query the underlying mechanistic causes of variation between individuals. However, there is little direct evidence of a linkage between global gene expression polymorphisms and phenotypic consequences. In this report, we have mapped quantitative trait loci (QTLs-controlling glucosinolate content in a population of 403 Arabidopsis Bay x Sha recombinant inbred lines, 211 of which were previously used to identify expression QTLs controlling the transcript levels of biosynthetic genes. In a comparative study, we have directly tested two plant biosynthetic pathways for association between polymorphisms controlling biosynthetic gene transcripts and the resulting metabolites within the Arabidopsis Bay x Sha recombinant inbred line population. In this analysis, all loci controlling expression variation also affected the accumulation of the resulting metabolites. In addition, epistasis was detected more frequently for metabolic traits compared to transcript traits, even when both traits showed similar distributions. An analysis of candidate genes for QTL-controlling networks of transcripts and metabolites suggested that the controlling factors are a mix of enzymes and regulatory factors. This analysis showed that regulatory connections can feedback from metabolism to transcripts. Surprisingly, the most likely major regulator of both transcript level for nearly the entire pathway and aliphatic glucosinolate accumulation is variation in the last enzyme in the biosynthetic pathway, AOP2. This suggests that natural variation in transcripts may significantly impact phenotypic variation, but that natural variation in metabolites or their enzymatic loci can feed back to affect the transcripts.

Metabolic networks of Cucurbita maxima phloem.

Science.gov (United States)

Fiehn, Oliver

2003-03-01

Metabolomic analysis aims at a comprehensive characterization of biological samples. Yet, biologically meaningful interpretations are often limited by the poor spatial and temporal resolution of the acquired data sets. One way to remedy this is to limit the complexity of the cell types being studied. Cucurbita maxima Duch. vascular exudates provide an excellent material for metabolomics in this regard. Using automated mass spectral deconvolution, over 400 components have been detected in these exudates, but only 90 of them were tentatively identified. Many amino compounds were found in vascular exudates from leaf petioles at concentrations several orders of magnitude higher than in tissue disks from the same leaves, whereas hexoses and sucrose were found in far lower amounts. In order to find the expected impact of assimilation rates on sugar levels, total phloem composition of eight leaves from four plants was followed over 4.5 days. Surprisingly, no diurnal rhythm was found for any of the phloem metabolites that was statistically valid for all eight leaves. Instead, each leaf had its own distinct vascular exudate profile similar to leaves from the same plant, but clearly different from leaves harvested from plants at the same developmental stage. Thirty to forty per cent of all metabolite levels of individual leaves were different from the average of all metabolite profiles. Using metabolic co-regulation analysis, similarities and differences between the exudate profiles were more accurately characterized through network computation, specifically with respect to nitrogen metabolism.

Global exponential stability of BAM neural networks with delays and impulses

International Nuclear Information System (INIS)

Li Yongkun

2005-01-01

Sufficient conditions are obtained for the existence and global exponential stability of a unique equilibrium of a class of two-layer heteroassociative networks called bidirectional associative memory (BAM) networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. An illustrative example is given to demonstrate the effectiveness of the obtained results

Virtual Global Accelerator Network (VGAN)(LCC-0083)

International Nuclear Information System (INIS)

Larsen, R

2003-01-01

The concept of a Global Accelerator Network (GAN) has been proposed by key members of ICFA as a cornerstone of a future International Linear Collider (LC). GAN would provide a tool for the participants of an international collaboration to participate in the actual running of the machine from different parts of the world. Some technical experts view the concept as technologically trivial, and instead point out the significant sociological, organizational and administrative problems that must be surmounted in creating a truly workable system. This note proposes that many real issues can be explored by building a simulator (VGAN) consisting of a virtual accelerator model, a global controls model, and a functioning human organizational model, a tool that would explore and resolve many real problems of GAN and the LC enterprise during the LC preliminary design and testing phase

Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

Directory of Open Access Journals (Sweden)

Elena Vinay-Lara

Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

Remote consultation and diagnosis in medical imaging using a global PACS backbone network

Science.gov (United States)

Martinez, Ralph; Sutaria, Bijal N.; Kim, Jinman; Nam, Jiseung

1993-10-01

A Global PACS is a national network which interconnects several PACS networks at medical and hospital complexes using a national backbone network. A Global PACS environment enables new and beneficial operations between radiologists and physicians, when they are located in different geographical locations. One operation allows the radiologist to view the same image folder at both Local and Remote sites so that a diagnosis can be performed. The paper describes the user interface, database management, and network communication software which has been developed in the Computer Engineering Research Laboratory and Radiology Research Laboratory. Specifically, a design for a file management system in a distributed environment is presented. In the remote consultation and diagnosis operation, a set of images is requested from the database archive system and sent to the Local and Remote workstation sites on the Global PACS network. Viewing the same images, the radiologists use pointing overlay commands, or frames to point out features on the images. Each workstation transfers these frames, to the other workstation, so that an interactive session for diagnosis takes place. In this phase, we use fixed frames and variable size frames, used to outline an object. The data pockets for these frames traverses the national backbone in real-time. We accomplish this feature by using TCP/IP protocol sockets for communications. The remote consultation and diagnosis operation has been tested in real-time between the University Medical Center and the Bowman Gray School of Medicine at Wake Forest University, over the Internet. In this paper, we show the feasibility of the operation in a Global PACS environment. Future improvements to the system will include real-time voice and interactive compressed video scenarios.

Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies.

Science.gov (United States)

Kalnenieks, Uldis; Pentjuss, Agris; Rutkis, Reinis; Stalidzans, Egils; Fell, David A

2014-01-01

Mathematical modeling of metabolism is essential for rational metabolic engineering. The present work focuses on several types of modeling approach to quantitative understanding of central metabolic network and energetics in the bioethanol-producing bacterium Zymomonas mobilis. Combined use of Flux Balance, Elementary Flux Mode, and thermodynamic analysis of its central metabolism, together with dynamic modeling of the core catabolic pathways, can help to design novel substrate and product pathways by systematically analyzing the solution space for metabolic engineering, and yields insights into the function of metabolic network, hardly achievable without applying modeling tools.

Urban metabolism: A review of research methodologies

International Nuclear Information System (INIS)

Zhang, Yan

2013-01-01

Urban metabolism analysis has become an important tool for the study of urban ecosystems. The problems of large metabolic throughput, low metabolic efficiency, and disordered metabolic processes are a major cause of unhealthy urban systems. In this paper, I summarize the international research on urban metabolism, and describe the progress that has been made in terms of research methodologies. I also review the methods used in accounting for and evaluating material and energy flows in urban metabolic processes, simulation of these flows using a network model, and practical applications of these methods. Based on this review of the literature, I propose directions for future research, and particularly the need to study the urban carbon metabolism because of the modern context of global climate change. Moreover, I recommend more research on the optimal regulation of urban metabolic systems. Highlights: •Urban metabolic processes can be analyzed by regarding cities as superorganisms. •Urban metabolism methods include accounting, assessment, modeling, and regulation. •Research methodologies have improved greatly since this field began in 1965. •Future research should focus on carbon metabolism and optimal regulation. -- The author reviews research progress in the field of urban metabolism, and based on her literature review, proposes directions for future research

Network advocacy and the emergence of global attention to newborn survival.

Science.gov (United States)

Shiffman, Jeremy

2016-04-01

Globally 2.9 million babies die each year before reaching 28 days of life. Over the past quarter century, neonatal mortality has declined at a slower pace than post-neonatal under-five mortality: in consequence newborns now comprise 44% of all deaths to children under five years. Despite high numbers of newborn deaths, global organizations and national governments paid little attention to the issue until 2000, and resources, while growing since then, remain inadequate. This study examines the factors behind these patterns of policy attention: the delayed emergence of attention, its sudden appearance in 2000, its growth thereafter, but the dearth of resources to date. Drawing on a framework on global health networks grounded in collective action theory, the study finds that a newborn survival network helped to shift perceptions about the problem's severity and tractability, contributing to the rise of global attention. Its efforts were facilitated by pressure on governments to achieve the child survival Millennium Development Goal and by growing awareness that the neonatal period constituted a growing percentage of under-five mortality, a fact the network publicized. The network's relatively recent emergence, its predominantly technical rather than political composition and strategies, and its inability to date to find a framing of the issue that has convinced national political leaders of the issue's urgency, in part explain the insufficiency of resources. However, since 2010 a number of non-health oriented inter-governmental organizations have begun to pay attention to the issue, and several countries with high neonatal mortality have created national plans, developments which augur well for the future. The study points to two broader implications concerning how neglected global health issues come to attract attention: priority emerges from a confluence of factors, rather than any single cause; and growth in priority may depend on the creation of a broader

Shifting Tides in Global Higher Education: Agency, Autonomy, and Governance in the Global Network. Global Studies in Education, Volume 9

Science.gov (United States)

Witt, Mary Allison

2011-01-01

The increasing connection among higher education institutions worldwide is well documented. What is less understood is how this connectivity is enacted and manifested on specific levels of the global education network. This book details the planning process of a multi-institutional program in engineering between institutions in the US and…

Global stability of an SIR model with differential infectivity on complex networks

Science.gov (United States)

Yuan, Xinpeng; Wang, Fang; Xue, Yakui; Liu, Maoxing

2018-06-01

In this paper, an SIR model with birth and death on complex networks is analyzed, where infected individuals are divided into m groups according to their infection and contact between human is treated as a scale-free social network. We obtain the basic reproduction number R0 as well as the effects of various immunization schemes. The results indicate that the disease-free equilibrium is locally and globally asymptotically stable in some conditions, otherwise disease-free equilibrium is unstable and exists an unique endemic equilibrium that is globally asymptotically stable. Our theoretical results are confirmed by numerical simulations and a promising way for infectious diseases control is suggested.

Global Proteome Response to Deletion of Genes Related to Mercury Methylation and Dissimilatory Metal Reduction Reveals Changes in Respiratory Metabolism in Geobacter sulfurreducens PCA.

Science.gov (United States)

Qian, Chen; Johs, Alexander; Chen, Hongmei; Mann, Benjamin F; Lu, Xia; Abraham, Paul E; Hettich, Robert L; Gu, Baohua

2016-10-07

Geobacter sulfurreducens PCA can reduce, sorb, and methylate mercury (Hg); however, the underlying biochemical mechanisms of these processes and interdependent metabolic pathways remain unknown. In this study, shotgun proteomics was used to compare global proteome profiles between wild-type G. sulfurreducens PCA and two mutant strains: a ΔhgcAB mutant, which is deficient in two genes known to be essential for Hg methylation and a ΔomcBESTZ mutant, which is deficient in five outer membrane c-type cytochromes and thus impaired in its ability for dissimilatory metal ion reduction. We were able to delineate the global response of G. sulfurreducens PCA in both mutants and identify cellular networks and metabolic pathways that were affected by the loss of these genes. Deletion of hgcAB increased the relative abundances of proteins implicated in extracellular electron transfer, including most of the c-type cytochromes, PilA-C, and OmpB, and is consistent with a previously observed increase in Hg reduction in the ΔhgcAB mutant. Deletion of omcBESTZ was found to significantly increase relative abundances of various methyltransferases, suggesting that a loss of dissimilatory reduction capacity results in elevated activity among one-carbon (C1) metabolic pathways and thus increased methylation. We show that G. sulfurreducens PCA encodes only the folate branch of the acetyl-CoA pathway, and proteins associated with the folate branch were found at lower abundance in the ΔhgcAB mutant strain than the wild type. This observation supports the hypothesis that the function of HgcA and HgcB is linked to C1 metabolism through the folate branch of the acetyl-CoA pathway by providing methyl groups required for Hg methylation.

Tracing the Slow Food Movement: local foodscapes and global networks

NARCIS (Netherlands)

Hendrikx, B.; Dormans, S.E.M.; Lagendijk, A.

2012-01-01

Over the last two decades alternative food practices have mushroomed across the globe. This proliferation has changed local food scapes, infusing localities with new ideas and ways of food production, circulation and consumption. It has also created global networks of innovation and

The Continuing Growth of Global Cooperation Networks in Research: A Conundrum for National Governments.

Directory of Open Access Journals (Sweden)

Caroline S Wagner

Full Text Available Global collaboration continues to grow as a share of all scientific cooperation, measured as coauthorships of peer-reviewed, published papers. The percent of all scientific papers that are internationally coauthored has more than doubled in 20 years, and they account for all the growth in output among the scientifically advanced countries. Emerging countries, particularly China, have increased their participation in global science, in part by doubling their spending on R&D; they are increasingly likely to appear as partners on internationally coauthored scientific papers. Given the growth of connections at the international level, it is helpful to examine the phenomenon as a communications network and to consider the network as a new organization on the world stage that adds to and complements national systems. When examined as interconnections across the globe over two decades, a global network has grown denser but not more clustered, meaning there are many more connections but they are not grouping into exclusive 'cliques'. This suggests that power relationships are not reproducing those of the political system. The network has features an open system, attracting productive scientists to participate in international projects. National governments could gain efficiencies and influence by developing policies and strategies designed to maximize network benefits-a model different from those designed for national systems.

Global Stability of Complex-Valued Genetic Regulatory Networks with Delays on Time Scales

Directory of Open Access Journals (Sweden)

Wang Yajing

2016-01-01

Full Text Available In this paper, the global exponential stability of complex-valued genetic regulatory networks with delays is investigated. Besides presenting conditions guaranteeing the existence of a unique equilibrium pattern, its global exponential stability is discussed. Some numerical examples for different time scales.

Monthly Summaries of the Global Historical Climatology Network - Daily (GHCN-D)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Monthly Summaries of Global Historical Climatology Network (GHCN)-Daily is a dataset derived from GHCN-Daily. The data are produced by computing simple averages or...

Indications of marine bioinvasion from network theory. An analysis of the global cargo ship network

NARCIS (Netherlands)

Kölzsch, A.; Blasius, B.

2011-01-01

The transport of huge amounts of small aquatic organisms in the ballast tanks and at the hull of large cargo ships leads to ever increasing rates of marine bioinvasion. In this study, we apply a network theoretic approach to examine the introduction of invasive species into new ports by global

European network for research in global change (ENRICH)

Energy Technology Data Exchange (ETDEWEB)

Ghazi, A [European Commission, Bruxelles (Belgium). DG XII/JRC

1996-12-31

While approaching the beginning of the twenty first century, the scientific community is faced with the formidable tasks of monitoring and detecting, understanding and predicting changes in the Earth System and its interactions with human beings. A crucial challenge is to make scientific research results accessible and usable for those involved in the decision making process related to the concept of Sustainable Development. Major international scientific programmes under the umbrella of ICSU, such as the IGBP and WCRP, are dealing with these issues. Although there exist many well developed global change research programmes in several European countries and effective collaboration networks between research institutes, there is an urgent need for overall communication with a view to promoting wider international links ensuring complementarity, synergy and coherence. Recognizing the importance of promoting coherence in research and utilising research results for various European Union (EU) policies, the European Commissioner responsible for Science, Research and Development wrote in March 1992 to all the EU Research Ministers to propose an initiative in this domain. In a rapid response, a group of Senior Experts from the EU Member States was set up in April 1992. This Group established a Task Force to develop the concept of the European Network for Research In Global CHange (ENRICH) which was approved in July 1993

European network for research in global change (ENRICH)

Energy Technology Data Exchange (ETDEWEB)

Ghazi, A. [European Commission, Bruxelles (Belgium). DG XII/JRC

1995-12-31

While approaching the beginning of the twenty first century, the scientific community is faced with the formidable tasks of monitoring and detecting, understanding and predicting changes in the Earth System and its interactions with human beings. A crucial challenge is to make scientific research results accessible and usable for those involved in the decision making process related to the concept of Sustainable Development. Major international scientific programmes under the umbrella of ICSU, such as the IGBP and WCRP, are dealing with these issues. Although there exist many well developed global change research programmes in several European countries and effective collaboration networks between research institutes, there is an urgent need for overall communication with a view to promoting wider international links ensuring complementarity, synergy and coherence. Recognizing the importance of promoting coherence in research and utilising research results for various European Union (EU) policies, the European Commissioner responsible for Science, Research and Development wrote in March 1992 to all the EU Research Ministers to propose an initiative in this domain. In a rapid response, a group of Senior Experts from the EU Member States was set up in April 1992. This Group established a Task Force to develop the concept of the European Network for Research In Global CHange (ENRICH) which was approved in July 1993

New results on global exponential dissipativity analysis of memristive inertial neural networks with distributed time-varying delays.

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Zhang, Guodong; Zeng, Zhigang; Hu, Junhao

2018-01-01

This paper is concerned with the global exponential dissipativity of memristive inertial neural networks with discrete and distributed time-varying delays. By constructing appropriate Lyapunov-Krasovskii functionals, some new sufficient conditions ensuring global exponential dissipativity of memristive inertial neural networks are derived. Moreover, the globally exponential attractive sets and positive invariant sets are also presented here. In addition, the new proposed results here complement and extend the earlier publications on conventional or memristive neural network dynamical systems. Finally, numerical simulations are given to illustrate the effectiveness of obtained results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Global robust exponential stability analysis for interval recurrent neural networks

International Nuclear Information System (INIS)

Xu Shengyuan; Lam, James; Ho, Daniel W.C.; Zou Yun

2004-01-01

This Letter investigates the problem of robust global exponential stability analysis for interval recurrent neural networks (RNNs) via the linear matrix inequality (LMI) approach. The values of the time-invariant uncertain parameters are assumed to be bounded within given compact sets. An improved condition for the existence of a unique equilibrium point and its global exponential stability of RNNs with known parameters is proposed. Based on this, a sufficient condition for the global robust exponential stability for interval RNNs is obtained. Both of the conditions are expressed in terms of LMIs, which can be checked easily by various recently developed convex optimization algorithms. Examples are provided to demonstrate the reduced conservatism of the proposed exponential stability condition

Earthquake Monitoring with the MyShake Global Smartphone Seismic Network

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Inbal, A.; Kong, Q.; Allen, R. M.; Savran, W. H.

2017-12-01

Smartphone arrays have the potential for significantly improving seismic monitoring in sparsely instrumented urban areas. This approach benefits from the dense spatial coverage of users, as well as from communication and computational capabilities built into smartphones, which facilitate big seismic data transfer and analysis. Advantages in data acquisition with smartphones trade-off with factors such as the low-quality sensors installed in phones, high noise levels, and strong network heterogeneity, all of which limit effective seismic monitoring. Here we utilize network and array-processing schemes to asses event detectability with the MyShake global smartphone network. We examine the benefits of using this network in either triggered or continuous modes of operation. A global database of ground motions measured on stationary phones triggered by M2-6 events is used to establish detection probabilities. We find that the probability of detecting an M=3 event with a single phone located 20 nearby phones closely match the regional catalog locations. We use simulated broadband seismic data to examine how location uncertainties vary with user distribution and noise levels. To this end, we have developed an empirical noise model for the metropolitan Los-Angeles (LA) area. We find that densities larger than 100 stationary phones/km2 are required to accurately locate M 2 events in the LA basin. Given the projected MyShake user distribution, that condition may be met within the next few years.

Tensor network decompositions in the presence of a global symmetry

International Nuclear Information System (INIS)

Singh, Sukhwinder; Pfeifer, Robert N. C.; Vidal, Guifre

2010-01-01

Tensor network decompositions offer an efficient description of certain many-body states of a lattice system and are the basis of a wealth of numerical simulation algorithms. We discuss how to incorporate a global symmetry, given by a compact, completely reducible group G, in tensor network decompositions and algorithms. This is achieved by considering tensors that are invariant under the action of the group G. Each symmetric tensor decomposes into two types of tensors: degeneracy tensors, containing all the degrees of freedom, and structural tensors, which only depend on the symmetry group. In numerical calculations, the use of symmetric tensors ensures the preservation of the symmetry, allows selection of a specific symmetry sector, and significantly reduces computational costs. On the other hand, the resulting tensor network can be interpreted as a superposition of exponentially many spin networks. Spin networks are used extensively in loop quantum gravity, where they represent states of quantum geometry. Our work highlights their importance in the context of tensor network algorithms as well, thus setting the stage for cross-fertilization between these two areas of research.

Global Production Networks and International Inequality: Making a Case for a Meso-Level Turn in Macro-Comparative Sociology

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Mathew Mahutga

2015-08-01

Full Text Available In this article, I extend recent macro-comparative empirical research on the developmental implications of global production networks. I draw from theories of commodity/value chains, global production networks and economic sociology to identify three contending theoretical perspectives for exactly how the developmental returns to network participants should be distributed-cooperation, exploitation and differential gains-and derive testable hypotheses for each. Adding to recent empirical advances for measuring the average network position of firms at the country level, I evaluate these hypotheses by way of dynamic panel regression models of hourly wage rates in the garment and transportation equipment industries. The results suggest that macro-sociological theories linking underdevelopment to the structure of the world-economy, as well as theories of the distribution of the gains from network participation, miss important variation at the industry level. Cooperation provides a poor account of the distribution of the gains from network participation. Instead, both industries appear to distribute the gains from network participation differentially across network participants. However, the extent of this inequality increases, and the garment industry transitions to exploitation, when global production networks become entrenched organizational logics. Variation in the distribution of the returns to network participation is explicable only by accounting for production-network governance as it varies across industries and over time. I conclude by highlighting the analytical utility to macro-comparative sociology of a turn toward the mesa-level of global industries.

AN INITIATIVE FOR CONSTRUCTION OF NEW-GENERATION LUNAR GLOBAL CONTROL NETWORK USING MULTI-MISSION DATA

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K. Di

2017-07-01

Full Text Available A lunar global control network provides geodetic datum and control points for mapping of the lunar surface. The widely used Unified Lunar Control Network 2005 (ULCN2005 was built based on a combined photogrammetric solution of Clementine images acquired in 1994 and earlier photographic data. In this research, we propose an initiative for construction of a new-generation lunar global control network using multi-mission data newly acquired in the 21st century, which have much better resolution and precision than the old data acquired in the last century. The new control network will be based on a combined photogrammetric solution of an extended global image and laser altimetry network. The five lunar laser ranging retro-reflectors, which can be identified in LROC NAC images and have cm level 3D position accuracy, will be used as absolute control points in the least squares photogrammetric adjustment. Recently, a new radio total phase ranging method has been developed and used for high-precision positioning of Chang’e-3 lander; this shall offer a new absolute control point. Systematic methods and key techniques will be developed or enhanced, including rigorous and generic geometric modeling of orbital images, multi-scale feature extraction and matching among heterogeneous multi-mission remote sensing data, optimal selection of images at areas of multiple image coverages, and large-scale adjustment computation, etc. Based on the high-resolution new datasets and developed new techniques, the new generation of global control network is expected to have much higher accuracy and point density than the ULCN2005.

Challenges for modeling global gene regulatory networks during development: insights from Drosophila.

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Wilczynski, Bartek; Furlong, Eileen E M

2010-04-15

Development is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative "coarse-grain" models operating at the gene level to very "fine-grain" quantitative models operating at the biophysical "transcription factor-DNA level". Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Global Horizontal Control Network of Shanghai Synchrotron Radiation Facility

International Nuclear Information System (INIS)

Yu Chenghao; Ke Ming; Du Hanwen; Yin Lixin; Zhao Zhentang; Dong Lan; Huang Kaixi

2009-01-01

As a national big scientific engineering, Shanghai Synchrotron Radiation Facility (SSRF) has rigid requirement to the components with sub-millimeter accuracy. In the process of survey and positioning global control network is a connecting link, which determines the position relationship between building and accelerator devices, and provides high accuracy datum to local control network. Within the designing process, building and devices are very restrict. While among observation, it's hard to be observed and abound with disadvantages. With continuous optimization and careful operation, super-high accuracy of 0.3 mm within 400 m circumference was achieved and slab's periodic movement could be seen through 3 times measurement. (authors)

Dynamics on networks: the role of local dynamics and global networks on the emergence of hypersynchronous neural activity.

Directory of Open Access Journals (Sweden)

Helmut Schmidt

2014-11-01

Full Text Available Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3-6 Hz and low-alpha (6-9 Hz bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80% predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic

Global network structure of dominance hierarchy of ant workers.

Science.gov (United States)

Shimoji, Hiroyuki; Abe, Masato S; Tsuji, Kazuki; Masuda, Naoki

2014-10-06

Dominance hierarchy among animals is widespread in various species and believed to serve to regulate resource allocation within an animal group. Unlike small groups, however, detection and quantification of linear hierarchy in large groups of animals are a difficult task. Here, we analyse aggression-based dominance hierarchies formed by worker ants in Diacamma sp. as large directed networks. We show that the observed dominance networks are perfect or approximate directed acyclic graphs, which are consistent with perfect linear hierarchy. The observed networks are also sparse and random but significantly different from networks generated through thinning of the perfect linear tournament (i.e. all individuals are linearly ranked and dominance relationship exists between every pair of individuals). These results pertain to global structure of the networks, which contrasts with the previous studies inspecting frequencies of different types of triads. In addition, the distribution of the out-degree (i.e. number of workers that the focal worker attacks), not in-degree (i.e. number of workers that attack the focal worker), of each observed network is right-skewed. Those having excessively large out-degrees are located near the top, but not the top, of the hierarchy. We also discuss evolutionary implications of the discovered properties of dominance networks. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

Science.gov (United States)

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti

Metabolic engineering of Bacillus subtilis fueled by systems biology: Recent advances and future directions.

Science.gov (United States)

Liu, Yanfeng; Li, Jianghua; Du, Guocheng; Chen, Jian; Liu, Long

By combining advanced omics technology and computational modeling, systems biologists have identified and inferred thousands of regulatory events and system-wide interactions of the bacterium Bacillus subtilis, which is commonly used both in the laboratory and in industry. This dissection of the multiple layers of regulatory networks and their interactions has provided invaluable information for unraveling regulatory mechanisms and guiding metabolic engineering. In this review, we discuss recent advances in the systems biology and metabolic engineering of B. subtilis and highlight current gaps in our understanding of global metabolism and global pathway engineering in this organism. We also propose future perspectives in the systems biology of B. subtilis and suggest ways that this approach can be used to guide metabolic engineering. Specifically, although hundreds of regulatory events have been identified or inferred via systems biology approaches, systematic investigation of the functionality of these events in vivo has lagged, thereby preventing the elucidation of regulatory mechanisms and further rational pathway engineering. In metabolic engineering, ignoring the engineering of multilayer regulation hinders metabolic flux redistribution. Post-translational engineering, allosteric engineering, and dynamic pathway analyses and control will also contribute to the modulation and control of the metabolism of engineered B. subtilis, ultimately producing the desired cellular traits. We hope this review will aid metabolic engineers in making full use of available systems biology datasets and approaches for the design and perfection of microbial cell factories through global metabolism optimization. Copyright © 2016 Elsevier Inc. All rights reserved.

Production of L-valine from metabolically engineered Corynebacterium glutamicum.

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Wang, Xiaoyuan; Zhang, Hailing; Quinn, Peter J

2018-05-01

L-Valine is one of the three branched-chain amino acids (valine, leucine, and isoleucine) essential for animal health and important in metabolism; therefore, it is widely added in the products of food, medicine, and feed. L-Valine is predominantly produced through microbial fermentation, and the production efficiency largely depends on the quality of microorganisms. In recent years, continuing efforts have been made in revealing the mechanisms and regulation of L-valine biosynthesis in Corynebacterium glutamicum, the most utilitarian bacterium for amino acid production. Metabolic engineering based on the metabolic biosynthesis and regulation of L-valine provides an effective alternative to the traditional breeding for strain development. Industrially competitive L-valine-producing C. glutamicum strains have been constructed by genetically defined metabolic engineering. This article reviews the global metabolic and regulatory networks responsible for L-valine biosynthesis, the molecular mechanisms of regulation, and the strategies employed in C. glutamicum strain engineering.

Spike propagation in driven chain networks with dominant global inhibition

International Nuclear Information System (INIS)

Chang Wonil; Jin, Dezhe Z.

2009-01-01

Spike propagation in chain networks is usually studied in the synfire regime, in which successive groups of neurons are synaptically activated sequentially through the unidirectional excitatory connections. Here we study the dynamics of chain networks with dominant global feedback inhibition that prevents the synfire activity. Neural activity is driven by suprathreshold external inputs. We analytically and numerically demonstrate that spike propagation along the chain is a unique dynamical attractor in a wide parameter regime. The strong inhibition permits a robust winner-take-all propagation in the case of multiple chains competing via the inhibition.

Metformin regulates global DNA methylation via mitochondrial one-carbon metabolism.

Science.gov (United States)

Cuyàs, E; Fernández-Arroyo, S; Verdura, S; García, R Á-F; Stursa, J; Werner, L; Blanco-González, E; Montes-Bayón, M; Joven, J; Viollet, B; Neuzil, J; Menendez, J A

2018-02-15

The anti-diabetic biguanide metformin may exert health-promoting effects via metabolic regulation of the epigenome. Here we show that metformin promotes global DNA methylation in non-cancerous, cancer-prone and metastatic cancer cells by decreasing S-adenosylhomocysteine (SAH), a strong feedback inhibitor of S-adenosylmethionine (SAM)-dependent DNA methyltransferases, while promoting the accumulation of SAM, the universal methyl donor for cellular methylation. Using metformin and a mitochondria/complex I (mCI)-targeted analog of metformin (norMitoMet) in experimental pairs of wild-type and AMP-activated protein kinase (AMPK)-, serine hydroxymethyltransferase 2 (SHMT2)- and mCI-null cells, we provide evidence that metformin increases the SAM:SAH ratio-related methylation capacity by targeting the coupling between serine mitochondrial one-carbon flux and CI activity. By increasing the contribution of one-carbon units to the SAM from folate stores while decreasing SAH in response to AMPK-sensed energetic crisis, metformin can operate as a metabolo-epigenetic regulator capable of reprogramming one of the key conduits linking cellular metabolism to the DNA methylation machinery.

Design concepts for a Global Telemetered Seismograph Network

Science.gov (United States)

Peterson, Jon; Orsini, Nicholas A.

1982-01-01

This study represents a first step in developing an integrated, real-time global seismic data acquisition system a Global Telemetered Seismograph Network (GTSN). The principal objective of the GTSN will be to acquire reliable, high-quality, real-time seismic data for rapid location and analysis of seismic events. A secondary, but important, objective of the GTSN is to augment the existing off-line seismic data base available for research. The deployment of the GTSN will involve a variety of interrelated activities development of the data acquisition and receiving equipment, establishment of satellite and terrestrial communication links, site selection and preparation, training of station personnel, equipment installation, and establishment of support facilities. It is a complex program and the development of a sound management plan will be essential. The purpose of this study is not to fix design goals or dictate avenues of approach but to develop working concepts that may be used as a framework for program planning.The international exchange of seismic data has been an important factor in the progress that has been made during the past two decades in our understanding of earthquakes and global tectonics. The seismic data base available for analysis and research is derived principally from the Global Seismograph Network (GSN), which is funded and managed by the U.S. Geological Survey (USGS). The GSN comprises some 120 seismograph stations located in more than 60 countries of the world. Established during the 1960 s with the installation of the World-Wide Standardized Seismograph Network (WWSSN) , the GSN has been augmented in recent years by the installation of more advanced data systems, such as the Seismic Research Observatories (SRO), the modified High-Gain LongPeriod (ASRO) seismographs, and the digital WWSSN (DWWSSN). The SRO, ASRO, and DWWSSN stations have the common, distinctive feature of digital data recording, so they are known collectively as the Global

Tradeoff between robustness and elaboration in carotenoid networks produces cycles of avian color diversification.

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Badyaev, Alexander V; Morrison, Erin S; Belloni, Virginia; Sanderson, Michael J

2015-08-20

Resolution of the link between micro- and macroevolution calls for comparing both processes on the same deterministic landscape, such as genomic, metabolic or fitness networks. We apply this perspective to the evolution of carotenoid pigmentation that produces spectacular diversity in avian colors and show that basic structural properties of the underlying carotenoid metabolic network are reflected in global patterns of elaboration and diversification in color displays. Birds color themselves by consuming and metabolizing several dietary carotenoids from the environment. Such fundamental dependency on the most upstream external compounds should intrinsically constrain sustained evolutionary elongation of multi-step metabolic pathways needed for color elaboration unless the metabolic network gains robustness - the ability to synthesize the same carotenoid from an additional dietary starting point. We found that gains and losses of metabolic robustness were associated with evolutionary cycles of elaboration and stasis in expressed carotenoids in birds. Lack of metabolic robustness constrained lineage's metabolic explorations to the immediate biochemical vicinity of their ecologically distinct dietary carotenoids, whereas gains of robustness repeatedly resulted in sustained elongation of metabolic pathways on evolutionary time scales and corresponding color elaboration. The structural link between length and robustness in metabolic pathways may explain periodic convergence of phylogenetically distant and ecologically distinct species in expressed carotenoid pigmentation; account for stasis in carotenoid colors in some ecological lineages; and show how the connectivity of the underlying metabolic network provides a mechanistic link between microevolutionary elaboration and macroevolutionary diversification.

The scaling structure of the global road network.

Science.gov (United States)

Strano, Emanuele; Giometto, Andrea; Shai, Saray; Bertuzzo, Enrico; Mucha, Peter J; Rinaldo, Andrea

2017-10-01

Because of increasing global urbanization and its immediate consequences, including changes in patterns of food demand, circulation and land use, the next century will witness a major increase in the extent of paved roads built worldwide. To model the effects of this increase, it is crucial to understand whether possible self-organized patterns are inherent in the global road network structure. Here, we use the largest updated database comprising all major roads on the Earth, together with global urban and cropland inventories, to suggest that road length distributions within croplands are indistinguishable from urban ones, once rescaled to account for the difference in mean road length. Such similarity extends to road length distributions within urban or agricultural domains of a given area. We find two distinct regimes for the scaling of the mean road length with the associated area, holding in general at small and at large values of the latter. In suitably large urban and cropland domains, we find that mean and total road lengths increase linearly with their domain area, differently from earlier suggestions. Scaling regimes suggest that simple and universal mechanisms regulate urban and cropland road expansion at the global scale. As such, our findings bear implications for global road infrastructure growth based on land-use change and for planning policies sustaining urban expansions.

Adaptive Global Sliding Mode Control for MEMS Gyroscope Using RBF Neural Network

Directory of Open Access Journals (Sweden)

Yundi Chu

2015-01-01

Full Text Available An adaptive global sliding mode control (AGSMC using RBF neural network (RBFNN is proposed for the system identification and tracking control of micro-electro-mechanical system (MEMS gyroscope. Firstly, a new kind of adaptive identification method based on the global sliding mode controller is designed to update and estimate angular velocity and other system parameters of MEMS gyroscope online. Moreover, the output of adaptive neural network control is used to adjust the switch gain of sliding mode control dynamically to approach the upper bound of unknown disturbances. In this way, the switch item of sliding mode control can be converted to the output of continuous neural network which can weaken the chattering in the sliding mode control in contrast to the conventional fixed gain sliding mode control. Simulation results show that the designed control system can get satisfactory tracking performance and effective estimation of unknown parameters of MEMS gyroscope.