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57 results for “network topology”
Experimental evidence that network topology can accelerate the spread of beneficial mutations
<p>Whether and how the spatial arrangement of a population influences adaptive evolution has puzzled evolutionary biologists. Theoretical models make conflicting predictions about the probability a beneficial mutation will become fixed in a population for certain topologies like stars, in which "leaf" populations are connected through a central "hub." To date, these predictions have not been evaluated under realistic experimental conditions. Here, we test the prediction that topology can change the dynamics of fixation both in vitro and in silico by tracking the frequency of a beneficial mutant under positive selection as it spreads through networks of different topologies. Our results provide empirical support that metapopulation topology can increase the likelihood that a beneficial mutation spreads, broadens the conditions under which this phenomenon is thought to occur, and points the way towards using network topology to amplify the effects of weakly favored mutations under directed evolution in industrial applications. </p>
Experimental evidence that network topology can accelerate the spread of beneficial mutations
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Supporting information for: Accounting for the topology of road networks to better explain human-mediated dispersal in terrestrial landscapes
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Data from: From structure to function in mutualistic interaction networks: topologically important frugivores have greater potential as seed dispersers
1. Networks of mutualistic interactions between animals and plants are considered a pivotal part of ecological communities. However, mutualistic networks are rarely studied from the perspective of species-specific roles, and it remains to be established whether those animal species more relevant for network structure also contribute more to the ecological functions derived from interactions. 2. Here, we relate the contribution to seed dispersal of vertebrate species with their topological role in frugivore-plant interaction networks. For one year in two localities with remnant patches of Colombian tropical dry forest, we sampled abundance, morphology, behavior, and fruit consumption from fleshy-fruited plants of various frugivore species. 3. We assessed the network topological role of each frugivore species by integrating their degree of generalization in interactions with plants with their contributions to network nestedness and modularity. We estimated the potential contribution of each frugivore species to community-wide seed dispersal, on the basis of a set of frugivore ecological, morphological and behavioral characteristics important for seed dispersal, together with frugivore abundance and frugivory degree. 4. The various frugivore species showed strong differences in their network structural roles, with generalist species contributing the most to network modularity and nestedness. Frugivores also showed strong variability in terms of potential contribution to seed dispersal, depending on the specific combinations of frugivore abundance, frugivory degree and the different traits and behaviors. 5. For both localities, the seed dispersal potential of a frugivore species responded positively to its contribution to network structure, evidencing that the most important frugivore species in the network topology were also those making the strongest contribution as seed dispersers. Contribution to network structure was correlated with frugivore abundance, diet, and behavioral characteristics. This suggests that the species-level link between structure and function is due to the fact that the occurrence of frugivore-plant interactions depends largely on the characteristics of the frugivore involved, which also condition its ultimate role in seed dispersal. 22-May-2020
Effects of Network Topology On the Performance of Consensus and Distributed Learning of SVMs Using ADMM
<p>The Alternating Direction Method Of Multipliers (ADMM) is a popular and promising distributed framework for solving large-scale machine learning problems. We consider decentralized consensus-based ADMM in which nodes may only communicate with one-hop neighbors. This may cause slow convergence. We investigate the impact of network topology on the performance of an ADMM-based learning of Support Vector Machine (SVM) using expander, and mean-degree graphs, and additionally some of the common modern network topologies. In particular, we investigate to which degree the expansion property of the network influences the convergence in terms of iterations, training and communication time. We furthermore suggest which topology is preferable. Additionally, we provide an implementation that makes these theoretical advances easily available. The results show that the performance of decentralized ADMM-based learning of SVMs in terms of convergence is improved using graphs with large spectral gaps, higher and homogeneous degrees.</p>
Data and Code for Inequality is rising where social network segregation interacts with urban topology
<p>This folder contains data and code to reproduce results of the paper "Inequality is rising where social network segregation interacts with urban topology". arXiv version: https://arxiv.org/abs/1909.11414.</p>
Learning topological states from randomized measurements using variational tensor network tomography
<p>Dataset for paper <strong>Learning topological states from randomized measurements using variational tensor network tomography.</strong><br>The numerical code can be found at the repo: https://github.com/teng10/tn-shadow-qst</p>
Data of decomposition, topology, and the corresponding graphs of Random Woody Crown Networks with size from 10 to 248 nodes
<p>Data of decomposition, topology and the corresponding graphs of Random Woody Crown Networks with size from 10 to 248 nodes</p>
The topology of spatial networks affects stability in experimental metacommunities
<p><span>Understanding the drivers of community stability has been a central goal in ecology. Traditionally the emphasis has been placed on studying the effects of biotic interactions on community variability, and less is understood about how the spatial configuration of habitats promotes or hinders metacommunity stability. To test the effects of contrasting spatial configurations on metacommunity stability, I designed metacommunities with patches connected as random or scale-free networks. In these microcosms, two prey and one protist predator dispersed, and I evaluated community persistence, tracked biomass variations, and measured synchrony between local communities and their neighbors. After 30 generations, scale-free metacommunities had lower global biomass variability and higher persistence, suggesting higher stability. At the local scale, patches in scale-free metacommunities showed a positive relationship between variability and patch connectivity, indicating higher stability in isolated communities. No clear relationship was observed in random networks. These results suggest the increased heterogeneity in connectivity of scale-free networks favors the prevalence of isolated patches in the metacommunity, which likely act as refugia against competition—the most dominant interaction in this system—resulting in higher global stability. These results highlight the importance of accounting for network topology in the study of spatial dynamics.</span></p>
Morph_CNeT: A new GIS tool to extract morphometric attributes characterising channel network topology of Indian catchments
<p><span>Morph_CNeT” (Morphometric Channel Network Extraction Tool) can facilitate extraction of the topology based new morphometric attributes by processing DEM datasets within GIS framework. Morph_CNeT tool is used to create a repository named as Morph_CNeT-India of topological catchment attributes for 1749 gauging stations maintained by the Central Water Commission (CWC) across 22 River basin Systems of India.</span></p>
TEFNET24: Reference Packet Optical Network Topology for Edge to Core Transport [Invited]
<p>In this paper, we introduce TEFNET24, a reference multi-layer hierarchical network topology that spans from access to core networks, specifically designed to meet the demands of beyond-5G and and prepared for next-generation 6G communication systems. This topology, inspired by the actual network deployments of Telefónica in medium-sized countries in Europe and America, integrates both IP and optical (DWDM) layers to provide a comprehensive framework for network design, optimization, and analysis. Our primary contribution is the development of an open-source benchmarking network, accessible to both researchers and industry professionals. This resource aims to facilitate the study and advancement of integrated IP and optical networks, allowing researchers to address key challenges such as traffic aggregation, latency reduction, cost efficiency, and support for advanced applications. We provide guidelines for utilizing this benchmark network, enabling users to evaluate and enhance their solutions for AI-driven network management, ultra-reliable low-latency communication, enhanced mobile broadband, and massive machine-type communication. By sharing this detailed and practical benchmarking network, we seek to foster innovation and collaboration within the optical network community, driving forward the capabilities and performance of future communication networks. </p>
Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN Performance
<p>Dataset of the synthetic networks used in the paper "Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN Performance".</p>
Dataset for: Multivascular networks and functional intravascular topologies within biocompatible hydrogels
<p>Dataset for:</p> <p>Multivascular networks and functional intravascular topologies within biocompatible hydrogels</p> <p>Bagrat Grigoryan1,∗, Samantha J. Paulsen1,∗, Daniel C. Corbett2,∗, Daniel W. Sazer1, Chelsea L. Fortin2, Alexander J. Zaita1, Paul T. Greenfield1, Nicholas J. Calafat1, John P. Gounley3, Anderson H. Ta1, Fredrik Johansson2, Amanda Randles3, Jessica E. Rosenkrantz4, Jesse D. Louis-Rosenberg4, Peter A. Galie5, Kelly R. Stevens2,†, Jordan S. Miller1,†</p> <p>1Department of Bioengineering, Rice University, Houston, TX 77005, USA 2Department of Bioengineering, University of Washington, Seattle, WA 98195, USA 3Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA 4Nervous System, Somerville, MA 02143, USA 5Department of Biomedical Engineering, Rowan University, Glassboro, NJ 08028, USA</p> <p>∗Equal contribution. †Corresponding authors. Email: ksteve@uw.edu (K.R.S.) and jmil@rice.edu (J.S.M.).</p> <p>Solid organs transport fluids through distinct vascular networks that are biophysically and biochemically entangled, creating complex 3D transport regimes that have remained difficult to produce and study. We establish intravascular and multivascular design freedoms with photopolymerizable hydrogels using food dye additives as biocompatible yet potent photoabsorbers for projection stereolithography. We demonstrate monolithic transparent hydrogels produced in minutes comprising efficient intravascular 3D fluid mixers and functional bicuspid valves. We further elaborate entangled vascular networks from space-filling mathematical topologies and explore the oxygenation and flow of human red blood cells during tidal ventilation and distension of a proximate airway. In addition, we deployed structured biodegradable hydrogel carriers in a rodent model of hepatic disease to highlight the potential translational utility of this materials innovation.</p>
Data from: From structure to function in mutualistic interaction networks: topologically important frugivores have greater potential as seed dispersers
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The topology of spatial networks affects stability in experimental metacommunities
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Dataset for: Contingent evolution of alternative metabolic network topologies determines whether cross-feeding evolves
<p>Data generated with VirtualMicrobes (<a href="https://bitbucket.org/thocu/virtual-microbes">https://bitbucket.org/thocu/virtual-microbes</a>) supporting: </p> <p>J.Meijer, B. van Dijk, P. Hogeweg. Contingent evolution of alternative metabolic network topologies determines whether cross-feeding evolves. Nature Communication Biology (2020)</p>
Data from: Topology of tree-mycorrhizal fungus interaction networks in xeric and mesic Douglas-fir forests
1. From the phytocentric perspective, a mycorrhizal network (MN) is formed when the roots of two or more plants are colonized by the same fungal genet. MNs can be modelled as interaction networks with plants as nodes and fungal genets as links. The potential effects of MNs on facilitation or competition between plants are increasingly recognized, but their network topologies remain largely unknown. This information is needed to understand the ecological significance of MN functional traits. 2. The objectives of this study were to describe the interaction network topologies of MNs formed between two ectomycorrhizal fungal species, Rhizopogon vesiculosus and R. vinicolor, and interior Douglas-fir trees at the forest stand scale, identify factors leading to this structure and to contrast MN structures between forest plots with xeric versus mesic soil moisture regimes. 3. Tuberculate mycorrhizas were sampled in six 10 × 10 m plots with either xeric or mesic soil moisture regimes. Microsatellite DNA markers were used to identify tree and fungal genotypes isolated from mycorrhizas and for comparison with reference tree boles above-ground. 4. In all six plots, trees and fungal genets were highly interconnected. Size asymmetries between different tree cohorts led to non-random MN topologies, while differences in size and connectivity between Rhizopogon species-specific subnetwork components contributed towards MN nestedness. Large mature trees acted as network hubs with a significantly higher node degree compared to smaller trees. MNs representing trees linked by R. vinicolor genets were mostly nested within larger, more highly connected R. vesiculosus-linked MNs. 5. Attributes of network nodes showed that hub trees were more important to MN topology on xeric than mesic sites, but the emergent structures of MNs were similar in the two soil moisture regimes. 6. Synthesis. This study suggests MNs formed between interior Douglas-fir trees and R. vesiculosus and R. vinicolor genets are resilient to the random loss of participants, and to soil water stress, but may be susceptible to the loss of large trees or fungal genets. Our results regarding the topology of MNs contribute to the understanding of forest stand dynamics and the resilience of forests to stress or disturbance.
Data from: Linking topological structure and dynamics in ecological networks
Interaction networks are basic descriptions of ecological communities and are at the core of community dynamics models. Knowledge of their structure should enable us to understand dynamical properties of ecological communities. However, the relationships between dynamical properties of communities and qualitative descriptors of network structure remain unclear. To improve our understanding of such relationships, we develop a framework based on the concept of strongly connected components, which are key structural components of networks necessary to explain stability properties such as persistence and robustness. We illustrate this framework for the analysis of qualitative empirical food webs and plant-plant interaction networks. Both types of networks exhibit high persistence (on average, 99% and 80% of species, respectively, are expected to persist) and robustness (only 0.2% and 2% of species are expected to disappear following the extinction of a species). Each of the networks is structured as a large group of interconnected species accompanied by much smaller groups that most often consist of a single species. This low-modularity configuration can be explained by a negative modularity-stability relationship. Our results suggest that ecological communities are not typically structured in multispecies compartments and that compartmentalization decreases robustness.
Data from: The topological differences between visitation and pollen transport networks: a comparison in species rich communities of the Himalaya-Hengduan Mountains
Pollination networks are usually constructed and assessed by direct field observations which commonly assume that all flower visitors are true pollinators. However, this assumption is often invalid and the use of data based on mere visitors to flowers may lead to a misunderstanding of intrinsic pollination networks. Here, using a large dataset by both sampling floral visitors and analyzing their pollen loads, we constructed 32 networks pairs (visitation vs. pollen transport) across one flowering season at four elevation sites in the Himalaya-Hengduan Mountains region. Pollen analysis was conducted to determine which flower visitors acted as potential pollinators (pollen vectors) or as cheaters (those not carrying pollen of the visited plants). We tested whether there were topological differences between visitation and pollen transport networks and whether different taxonomic groups of insect visitors differed in their ability to carry pollen of the visited plants. Our results indicated that there was a significantly higher degree of specialization at both the network and species levels in the pollen transport networks in contrast to the visitation networks. Modularity was lower but nestedness was higher in the visitation networks compared to the pollen transport networks. All the cheaters were identified as peripheral species and most of them contributed positively to the nested structure. This may explain in part the differences in modularity and nestedness between the two network types. Bees carried the highest proportion of pollen of the visited plants. This was followed by Coleoptera, other Hymenoptera and Diptera. Lepidoptera carried the lowest proportion of pollen of the visited plants. Our study shows that the construction of pollen transport networks could provide a more in-depth understanding of plant-pollinator interactions. Moreover, it suggests that detecting and removing cheater interactions when studying the topology of other mutualistic networks might be also important.
Data from: Resilience or robustness: identifying topological vulnerabilities in rail networks
Many critical infrastructure systems have network structure and are under stress. Despite their national importance, the complexity of large-scale transport networks means we do not fully understand their vulnerabilities to cascade failures. The research in this paper examines the interdependent rail networks in Greater London and surrounding commuter area. We focus on the morning commuter hours, where the system is under the most demand stress. There is increasing evidence that the topological shape of the network plays an important role in dynamic cascades. Here, we examine whether the different topological measures of resilience (stability) or robustness (failure) are more appropriate for understanding poor railway performance. The results show that resilience and not robustness has a strong correlation to the consumer experience statistics. Our results are a way of describing the complexity of cascade dynamics on networks without the involvement of detailed agent-based-models, showing that cascade effects are more responsible for poor performance than failures. The network science analysis hints at pathways towards making the network structure more resilient by reducing feedback loops.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.