194 resultados para ECOLOGICAL NETWORKS
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The use of artificial nest-boxes has led to significant progress in bird conservation and in our understanding of the functional and evolutionary ecology of free-ranging birds that exploit cavities for roosting and reproduction. Nest-boxes and their improved accessibility have made it easier to perform comparative and experimental field investigations. However, concerns about the generality and applicability of scientific studies involving birds breeding in nest-boxes have been raised because the occupants of boxes may differ from conspecifics occupying other nest sites. Here we review the existing evidence demonstrating the importance of nest-box design to individual life-history traits in three falcon (Falconiformes) and seven owl (Strigiformes) species, as well as the extent to which publications on these birds describe the characteristics of exploited artificial nest-boxes in their 'methods' sections. More than 60% of recent publications did not provide any details on nest-box design (e.g. size, shape, material), despite several calls >15 years ago to increase the reporting of such information. We exemplify and discuss how variation in nest-box characteristics can affect or confound conclusions from nest-box studies and conclude that it is of overall importance to present details of nest-box characteristics in scientific publications.
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MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.
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Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.
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BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.
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European regulatory networks (ERNs) constitute the main governance instrument for the informal co-ordination of public regulation at the European Union (EU) level. They are in charge of co-ordinating national regulators and ensuring the implementation of harmonized regulatory policies across the EU, while also offering sector-specific expertise to the Commission. To this aim, ERNs develop 'best practices' and benchmarking procedures in the form of standards, norms and guidelines to be adopted in member states. In this paper, we focus on the Committee of European Securities Regulators and examine the consequences of the policy-making structure of ERNs on the domestic adoption of standards. We find that the regulators of countries with larger financial industries tend to occupy more central positions in the network, especially among newer member states. In turn, network centrality is associated with a more prompt domestic adoption of standards.
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The reproductive assurance hypothesis emphasizes that self-fertilization should evolve in species with reduced dispersal capability, low population size or experiencing recurrent bottlenecks. Our work investigates the ecological components of the habitats colonized by the snail, Galba truncatula, that may influence the evolution of selfing. Galba truncatula is a preferential selfer inhabiting freshwater habitats, which vary with respect to the degree of permanence. We considered with a population genetic approach the spatial and the temporal degree of isolation of populations of G. truncatula. We showed that patches at distances of only a few meters are highly structured. The effective population sizes appear quite low, in the order of 10 individuals or less. This study indicates that individuals of the species G. truncatula are likely to be alone in a site and have a low probability of finding a partner from a nearby site to reproduce. These results emphasize the advantage of selfing in this species.
MetaNetX.org: a website and repository for accessing, analysing and manipulating metabolic networks.
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SUMMARY: MetaNetX.org is a website for accessing, analysing and manipulating genome-scale metabolic networks (GSMs) as well as biochemical pathways. It consistently integrates data from various public resources and makes the data accessible in a standardized format using a common namespace. Currently, it provides access to hundreds of GSMs and pathways that can be interactively compared (two or more), analysed (e.g. detection of dead-end metabolites and reactions, flux balance analysis or simulation of reaction and gene knockouts), manipulated and exported. Users can also upload their own metabolic models, choose to automatically map them into the common namespace and subsequently make use of the website's functionality. Availability and implementation: MetaNetX.org is available at http://metanetx.org. CONTACT: help@metanetx.org.
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Rapport de synthèse : Objectif : Les déficits cognitifs présents dans la phase aiguë d'une lésion hémisphérique focale ont tendance à être de nature plus importante et plus générale que les déficits résiduels qui persistent dans la phase chronique de récupération. Nous avons investigué, dans le cadre de ce travail, les modèles de récupération auditive et la relation qui se dessine entre les déficits et les dommages relatifs à des réseaux spécifiques, pris comme modèle cognitif des fonctions auditives. De nombreuses études humaines dans les domaines de la neuropsychologie, de la psychophysique ainsi que des études d'activation suggèrent que les processus de reconnaissance et de localisation sonores sont effectués par l'intermédiaire de réseaux distincts tant sur le plan anatomique que fonctionnel : il s'agit des zones de traitement du «What» et du «Where », qui sont toutes deux présentes dans les deux hémisphères. Des études ont démontré que des lésions hémisphériques focales gauches ou droites, centrées sur ces réseaux, sont associées dans la phase chronique de récupération à des déficits correspondant en ce qui concerne la reconnaissance et/ou la localisation sonore. Méthode : Dans le cadre de ce travail, nous avons analysé les résultats concernant les performances auditives chez 24 patients ayant subi des lésions hémisphériques focales avec déficits secondaires dans des tâches de reconnaissance, de localisation et/ou de perception du mouvement sonore lors d'un premier testing effectué en phase aiguë (9 patients), en phase subaiguë (6 patients) ou en phase chronique précoce (9 patients). La totalité de ces patients ont bénéficié d'un second testing en phase chronique. Les observations effectuées ont servi à l'élaboration de patterns de récupération auditive. Résultats : Tous les 24 patients avaient initialement un déficit dans le domaine de la localisation et/ou de la perception du mouvement sonore. Dans la phase aiguë, ce déficit survenait sans atteinte spécifique du réseau «Where » chez presque la moitié des patients ; en revanche, cette situation n'était jamais observée chez les patients testés en phase chronique précoce. Une absence de récupération avait tendance à être associée à un dommage spécifique au réseau concerné ainsi qu'à la persistance d'un déficit au-delà de la phase aiguë. Les déficits résiduels n'étaient par ailleurs pas strictement en lien avec la taille lésionnelle ou l'étendue de l'atteinte du réseau spécifique. Conclusion : Nos résultats suggèrent que des mécanismes distincts sous-tendent la récupération et la plasticité à différentes périodes temporelles post-lésionnelles.
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The geometry and connectivity of fractures exert a strong influence on the flow and transport properties of fracture networks. We present a novel approach to stochastically generate three-dimensional discrete networks of connected fractures that are conditioned to hydrological and geophysical data. A hierarchical rejection sampling algorithm is used to draw realizations from the posterior probability density function at different conditioning levels. The method is applied to a well-studied granitic formation using data acquired within two boreholes located 6 m apart. The prior models include 27 fractures with their geometry (position and orientation) bounded by information derived from single-hole ground-penetrating radar (GPR) data acquired during saline tracer tests and optical televiewer logs. Eleven cross-hole hydraulic connections between fractures in neighboring boreholes and the order in which the tracer arrives at different fractures are used for conditioning. Furthermore, the networks are conditioned to the observed relative hydraulic importance of the different hydraulic connections by numerically simulating the flow response. Among the conditioning data considered, constraints on the relative flow contributions were the most effective in determining the variability among the network realizations. Nevertheless, we find that the posterior model space is strongly determined by the imposed prior bounds. Strong prior bounds were derived from GPR measurements and helped to make the approach computationally feasible. We analyze a set of 230 posterior realizations that reproduce all data given their uncertainties assuming the same uniform transmissivity in all fractures. The posterior models provide valuable statistics on length scales and density of connected fractures, as well as their connectivity. In an additional analysis, effective transmissivity estimates of the posterior realizations indicate a strong influence of the DFN structure, in that it induces large variations of equivalent transmissivities between realizations. The transmissivity estimates agree well with previous estimates at the site based on pumping, flowmeter and temperature data.