479 resultados para Hyperspaces Topologies


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Strepsirhines comprise 10 living or recently extinct families, ≥50% of extant primate families. Their phylogenetic relationships have been intensively studied, but common topologies have only recently emerged; e.g. all recent reconstructions link the Lepilemuridae and Cheirogaleidae. The position of the indriids, however, remains uncertain, and molecular studies have placed them as the sister to every clade except Daubentonia, the preferred sister group of morphologists. The node subtending Afro-Asian lorisids has been similarly elusive. We probed these phylogenetic inconsistencies using a test data set including 20 strepsirhine taxa and 2 outgroups represented by 3,543 mtDNA base pairs, and 43 selected morphological characters, subjecting the data to maximum parsimony, maximum likelihood and Bayesian inference analyses, and reconstructing topology and node ages jointly from the molecular data using relaxed molecular clock analyses. Our permutations yielded compatible but not identical evolutionary histories, and currently popular techniques seem unable to deal adequately with morphological data. We investigated the influence of morphological characters on tree topologies, and examined the effect of taxon sampling in two experiments: (1) we removed the molecular data only for 5 endangered Malagasy taxa to simulate 'extinction leaving a fossil record'; (2) we removed both the sequence and morphological data for these taxa. Topologies were affected more by the inclusion of morphological data only, indicating that palaeontological studies that involve inserting a partial morphological data set into a combined data matrix of extant species should be interpreted with caution. The gap of approximately 10 million years between the daubentoniid divergence and those of the other Malagasy families deserves more study. The apparently contemporaneous divergence of African and non-daubentoniid Malagasy families 40-30 million years ago may be related to regional plume-induced uplift followed by a global period of cooling and drying. © 2013 S. Karger AG, Basel.

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Phylogenetic reconstructions are a major component of many studies in evolutionary biology, but their accuracy can be reduced under certain conditions. Recent studies showed that the convergent evolution of some phenotypes resulted from recurrent amino acid substitutions in genes belonging to distant lineages. It has been suggested that these convergent substitutions could bias phylogenetic reconstruction toward grouping convergent phenotypes together, but such an effect has never been appropriately tested. We used computer simulations to determine the effect of convergent substitutions on the accuracy of phylogenetic inference. We show that, in some realistic conditions, even a relatively small proportion of convergent codons can strongly bias phylogenetic reconstruction, especially when amino acid sequences are used as characters. The strength of this bias does not depend on the reconstruction method but varies as a function of how much divergence had occurred among the lineages prior to any episodes of convergent substitutions. While the occurrence of this bias is difficult to predict, the risk of spurious groupings is strongly decreased by considering only 3rd codon positions, which are less subject to selection, as long as saturation problems are not present. Therefore, we recommend that, whenever possible, topologies obtained with amino acid sequences and 3rd codon positions be compared to identify potential phylogenetic biases and avoid evolutionarily misleading conclusions.

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The drug discovery process has been deeply transformed recently by the use of computational ligand-based or structure-based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure-based computational methods for drug discovery mainly involve ligand-protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand-protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol(-1), and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer-aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

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Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.

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A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

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We demonstrate that the self-similarity of some scale-free networks with respect to a simple degree-thresholding renormalization scheme finds a natural interpretation in the assumption that network nodes exist in hidden metric spaces. Clustering, i.e., cycles of length three, plays a crucial role in this framework as a topological reflection of the triangle inequality in the hidden geometry. We prove that a class of hidden variable models with underlying metric spaces are able to accurately reproduce the self-similarity properties that we measured in the real networks. Our findings indicate that hidden geometries underlying these real networks are a plausible explanation for their observed topologies and, in particular, for their self-similarity with respect to the degree-based renormalization.

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We present a generator of random networks where both the degree-dependent clustering coefficient and the degree distribution are tunable. Following the same philosophy as in the configuration model, the degree distribution and the clustering coefficient for each class of nodes of degree k are fixed ad hoc and a priori. The algorithm generates corresponding topologies by applying first a closure of triangles and second the classical closure of remaining free stubs. The procedure unveils an universal relation among clustering and degree-degree correlations for all networks, where the level of assortativity establishes an upper limit to the level of clustering. Maximum assortativity ensures no restriction on the decay of the clustering coefficient whereas disassortativity sets a stronger constraint on its behavior. Correlation measures in real networks are seen to observe this structural bound.

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The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.

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Ubiquitination, deubiquitination, and the formation of specific ubiquitin chain topologies have been implicated in various cellular processes. Little is known, however, about the role of ubiquitin in the development of cellular organelles. Here, we identify and characterize the deubiquitinating enzyme AMSH3 from Arabidopsis thaliana. AMSH3 hydrolyzes K48- and K63-linked ubiquitin chains in vitro and accumulates both ubiquitin chain types in vivo. amsh3 mutants fail to form a central lytic vacuole, accumulate autophagosomes, and mis-sort vacuolar protein cargo to the intercellular space. Furthermore, AMSH3 is required for efficient endocytosis of the styryl dye FM4-64 and the auxin efflux facilitator PIN2. We thus present evidence for a role of deubiquitination in intracellular trafficking and vacuole biogenesis.

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Nonstructural protein 4B (NS4B) is a key organizer of hepatitis C virus (HCV) replication complex formation. In concert with other nonstructural proteins, it induces a specific membrane rearrangement, designated as membranous web, which serves as a scaffold for the HCV replicase. The N-terminal part of NS4B comprises a predicted and a structurally resolved amphipathic α-helix, designated as AH1 and AH2, respectively. Here, we report a detailed structure-function analysis of NS4B AH1. Circular dichroism and nuclear magnetic resonance structural analyses revealed that AH1 folds into an amphipathic α-helix extending from NS4B amino acid 4 to 32, with positively charged residues flanking the helix. These residues are conserved among hepaciviruses. Mutagenesis and selection of pseudorevertants revealed an important role of these residues in RNA replication by affecting the biogenesis of double-membrane vesicles making up the membranous web. Moreover, alanine substitution of conserved acidic residues on the hydrophilic side of the helix reduced infectivity without significantly affecting RNA replication, indicating that AH1 is also involved in virus production. Selective membrane permeabilization and immunofluorescence microscopy analyses of a functional replicon harboring an epitope tag between NS4B AH1 and AH2 revealed a dual membrane topology of the N-terminal part of NS4B during HCV RNA replication. Luminal translocation was unaffected by the mutations introduced into AH1, but was abrogated by mutations introduced into AH2. In conclusion, our study reports the three-dimensional structure of AH1 from HCV NS4B, and highlights the importance of positively charged amino acid residues flanking this amphipathic α-helix in membranous web formation and RNA replication. In addition, we demonstrate that AH1 possesses a dual role in RNA replication and virus production, potentially governed by different topologies of the N-terminal part of NS4B.

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We analyze the process of informational exchange through complex networks by measuring network efficiencies. Aiming to study nonclustered systems, we propose a modification of this measure on the local level. We apply this method to an extension of the class of small worlds that includes declustered networks and show that they are locally quite efficient, although their clustering coefficient is practically zero. Unweighted systems with small-world and scale-free topologies are shown to be both globally and locally efficient. Our method is also applied to characterize weighted networks. In particular we examine the properties of underground transportation systems of Madrid and Barcelona and reinterpret the results obtained for the Boston subway network.

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A common operation in wireless ad hoc networks is the flooding of broadcast messages to establish network topologies and routing tables. The flooding of broadcast messages is, however, a resource consuming process. It might require the retransmission of messages by most network nodes. It is, therefore, very important to optimize this operation. In this paper, we first analyze the multipoint relaying (MPR) flooding mechanism used by the Optimized Link State Routing (OLSR) protocol to distribute topology control (TC) messages among all the system nodes. We then propose a new flooding method, based on the fusion of two key concepts: distance-enabled multipoint relaying and connected dominating set (CDS) flooding. We present experimental simulationsthat show that our approach improves the performance of previous existing proposals.

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Résumé Les mousses sont la plus ancienne lignée de plantes terrestres et leur longue évolution a été accompagnée par des tendances à la simplification des caractères morphologiques. Ce phénomène a quelque peu compliqué les reconstructions phylogénétiques basées sur la morphologie. Les analyses génétiques ont permis de donner de nouvelles informations dans le cadre des analyses phylogénétiques et une réévaluation de certains caractères morphologiques. La plupart des études combinant les données morphologiques et moléculaires ne concernent que des niveaux systématiques élevés comme l'ordre ou la famille et très peu considèrent le niveau du genre. La présente étude tend à tester les relations phylogénétiques du genre Grimmia à l'aide d'une combinaison de caractères morphologiques et moléculaires. Les 40 espèces de Grimmia utilisées dans la première partie de cette étude représentent la majorité des espèces trouvées en Eurasie, un des centres de diversification du genre. Lors de l'analyse morphologique, 52 caractères morphologiques/anatomiques (33 du gamétophyte et 19 du sporophyte) ont été numérisés. Malgré le peu de support statistique des arbres, la topologie des arbres est stable. Les Grimmia, comme décrit précédemment, sont paraphylétiques. Trois clades, correspondant respectivement aux sous-genres Rhabdogrimmia Limpr, Litoneuron I.Hagen et Gasterogrimmia Schimp. sont présents, tandis que le restant des taxons appartenant aux Grimmia forment un groupe non-résolu et indistinct des autres Grimmiaceae. Les séquences chloroplastiques trnL-trnF et rps4 combinés à la morphologie ont été ensuite utilisés pour reconstruire la phylogénie des Grimmia. Les arbres obtenus soutiennent la monophylie des Grimmiaceae tandis que les Grimmia, sont paraphylétiques. Deux clades principaux correspondant aux "Rhabdogrimmia" et aux "Grimmia" se détachent. Seules les espèces de "Rhabdogrimmia" produisent des gemmules foliaires (reproduction asexuée). Dans une étude considèrant 91 séquences trrIL-trnF les espèces appartenant aux "Rhabdogrimrnia" (reproduction asexuée essentiellement) ont des variabilités intraspécifique très faible et interspécifique relativement élevée tandis que les "Grimmia" possèdent la tendance inverse (plus de reproduction sexuée). Summary The mosses are a very old land plant lineage and their long evolutionary history has been accompanied by a trend of morphological character simplifications. This phenomenon has somewhat complicated morphological based phylogenetic reconstructions. Genetic analyses have provided new insights for phylogenetic studies, and have allowed morphological data to be re¬evaluated. Most of the studies combining morphological and molecular data have concerned the higher systematic levels of order and family and only have few considered the genus. The present study aims to test the phylogenetic relationships of the genus Grimmia using a combination of morphological and molecular characters. The 40 chosen Grimmia species represent the majority of those found in Eurasia, one diversification centers of the genus. For the morphological analysis, 52 morphological/anatomical characters (33 gametophyte and 19 sporophyte characters) were numerized. Although the internal statistical support was relatively low, the tree topologies were stable. Grimmia as currently defined was found to be paraphyletic. Three subclades, corresponding to the subgenera Rhabdogrimmia Limpr., Litoneuron I.Hagen, and Gasterogrimmia Schimp. were observed in the trees, while the reminder of the Grimmia species formed an unresolved group indistinct from other Grimmiaceae. Chloroplast (trnL-trnF and rps4) DNA sequences combined with morphology were used to reconstruct the phylogeny of Grimmia. The resulting trees supported the monophyly of Grimmiaceae and that the genus Grimmia, as currently defined, as paraphyletic. Two main clades were resolved corresponding to "Rhabdogrimmia" and "Grimmia". The species belonging to "Rhabdogrimmia" produce foliar-gemmae (asexual reproduction). In a study using 91 sequences of trnL-trnF,"Rhabdogrimmia" species (mainly asexual reproduction) have very low intraspecific variability and high interspecific variability whereas the "Grimmia" species possess the inverse tendency.

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Abstract The main objective of this work is to show how the choice of the temporal dimension and of the spatial structure of the population influences an artificial evolutionary process. In the field of Artificial Evolution we can observe a common trend in synchronously evolv¬ing panmictic populations, i.e., populations in which any individual can be recombined with any other individual. Already in the '90s, the works of Spiessens and Manderick, Sarma and De Jong, and Gorges-Schleuter have pointed out that, if a population is struc¬tured according to a mono- or bi-dimensional regular lattice, the evolutionary process shows a different dynamic with respect to the panmictic case. In particular, Sarma and De Jong have studied the selection pressure (i.e., the diffusion of a best individual when the only selection operator is active) induced by a regular bi-dimensional structure of the population, proposing a logistic modeling of the selection pressure curves. This model supposes that the diffusion of a best individual in a population follows an exponential law. We show that such a model is inadequate to describe the process, since the growth speed must be quadratic or sub-quadratic in the case of a bi-dimensional regular lattice. New linear and sub-quadratic models are proposed for modeling the selection pressure curves in, respectively, mono- and bi-dimensional regu¬lar structures. These models are extended to describe the process when asynchronous evolutions are employed. Different dynamics of the populations imply different search strategies of the resulting algorithm, when the evolutionary process is used to solve optimisation problems. A benchmark of both discrete and continuous test problems is used to study the search characteristics of the different topologies and updates of the populations. In the last decade, the pioneering studies of Watts and Strogatz have shown that most real networks, both in the biological and sociological worlds as well as in man-made structures, have mathematical properties that set them apart from regular and random structures. In particular, they introduced the concepts of small-world graphs, and they showed that this new family of structures has interesting computing capabilities. Populations structured according to these new topologies are proposed, and their evolutionary dynamics are studied and modeled. We also propose asynchronous evolutions for these structures, and the resulting evolutionary behaviors are investigated. Many man-made networks have grown, and are still growing incrementally, and explanations have been proposed for their actual shape, such as Albert and Barabasi's preferential attachment growth rule. However, many actual networks seem to have undergone some kind of Darwinian variation and selection. Thus, how these networks might have come to be selected is an interesting yet unanswered question. In the last part of this work, we show how a simple evolutionary algorithm can enable the emrgence o these kinds of structures for two prototypical problems of the automata networks world, the majority classification and the synchronisation problems. Synopsis L'objectif principal de ce travail est de montrer l'influence du choix de la dimension temporelle et de la structure spatiale d'une population sur un processus évolutionnaire artificiel. Dans le domaine de l'Evolution Artificielle on peut observer une tendence à évoluer d'une façon synchrone des populations panmictiques, où chaque individu peut être récombiné avec tout autre individu dans la population. Déjà dans les année '90, Spiessens et Manderick, Sarma et De Jong, et Gorges-Schleuter ont observé que, si une population possède une structure régulière mono- ou bi-dimensionnelle, le processus évolutionnaire montre une dynamique différente de celle d'une population panmictique. En particulier, Sarma et De Jong ont étudié la pression de sélection (c-à-d la diffusion d'un individu optimal quand seul l'opérateur de sélection est actif) induite par une structure régulière bi-dimensionnelle de la population, proposant une modélisation logistique des courbes de pression de sélection. Ce modèle suppose que la diffusion d'un individu optimal suit une loi exponentielle. On montre que ce modèle est inadéquat pour décrire ce phénomène, étant donné que la vitesse de croissance doit obéir à une loi quadratique ou sous-quadratique dans le cas d'une structure régulière bi-dimensionnelle. De nouveaux modèles linéaires et sous-quadratique sont proposés pour des structures mono- et bi-dimensionnelles. Ces modèles sont étendus pour décrire des processus évolutionnaires asynchrones. Différentes dynamiques de la population impliquent strategies différentes de recherche de l'algorithme résultant lorsque le processus évolutionnaire est utilisé pour résoudre des problèmes d'optimisation. Un ensemble de problèmes discrets et continus est utilisé pour étudier les charactéristiques de recherche des différentes topologies et mises à jour des populations. Ces dernières années, les études de Watts et Strogatz ont montré que beaucoup de réseaux, aussi bien dans les mondes biologiques et sociologiques que dans les structures produites par l'homme, ont des propriétés mathématiques qui les séparent à la fois des structures régulières et des structures aléatoires. En particulier, ils ont introduit la notion de graphe sm,all-world et ont montré que cette nouvelle famille de structures possède des intéressantes propriétés dynamiques. Des populations ayant ces nouvelles topologies sont proposés, et leurs dynamiques évolutionnaires sont étudiées et modélisées. Pour des populations ayant ces structures, des méthodes d'évolution asynchrone sont proposées, et la dynamique résultante est étudiée. Beaucoup de réseaux produits par l'homme se sont formés d'une façon incrémentale, et des explications pour leur forme actuelle ont été proposées, comme le preferential attachment de Albert et Barabàsi. Toutefois, beaucoup de réseaux existants doivent être le produit d'un processus de variation et sélection darwiniennes. Ainsi, la façon dont ces structures ont pu être sélectionnées est une question intéressante restée sans réponse. Dans la dernière partie de ce travail, on montre comment un simple processus évolutif artificiel permet à ce type de topologies d'émerger dans le cas de deux problèmes prototypiques des réseaux d'automates, les tâches de densité et de synchronisation.

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This thesis presents a topological approach to studying fuzzy setsby means of modifier operators. Modifier operators are mathematical models, e.g., for hedges, and we present briefly different approaches to studying modifier operators. We are interested in compositional modifier operators, modifiers for short, and these modifiers depend on binary relations. We show that if a modifier depends on a reflexive and transitive binary relation on U, then there exists a unique topology on U such that this modifier is the closure operator in that topology. Also, if U is finite then there exists a lattice isomorphism between the class of all reflexive and transitive relations and the class of all topologies on U. We define topological similarity relation "≈" between L-fuzzy sets in an universe U, and show that the class LU/ ≈ is isomorphic with the class of all topologies on U, if U is finite and L is suitable. We consider finite bitopological spaces as approximation spaces, and we show that lower and upper approximations can be computed by means of α-level sets also in the case of equivalence relations. This means that approximations in the sense of Rough Set Theory can be computed by means of α-level sets. Finally, we present and application to data analysis: we study an approach to detecting dependencies of attributes in data base-like systems, called information systems.