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12 results for “bipartite network”
Fig.1. Bipartite graph depicting a plant-animal mutualistic network involving 10 in The Role Of Macaca Spp. (Primates: Cercopithecidae) In Seed Dispersal Networks
Fig.1. Bipartite graph depicting a plant-animal mutualistic network involving 10 frugivores (left) and 170 of the plant species (right) they disperse at Khao Yai National Park, Thailand. The list of plant species is based on Kitamura et al. (2002), then the list of frugivores dispersing each species has been completed thanks to data from bin Kassim (1987), Kitamura et al. (2005), Datta & Rawat (2008), Brockelman (2009), McConkey & Brockelman (2011), Albert et al. (2013), Ngoprasert (2012), Khamcha (pers. comm.), Latinne (pers. comm.), Martmoon (pers. comm.).
Bipartite plant-pollinator diurnal and nocturnal networks for three mountain systems of the Iberian Peninsula.
<p>Dataset generated for the article "Addition of nocturnal pollinators modifies the structure of pollination" networks" (DOI:10.1038/s41598-023-49944-y). </p> <p>Diurnal and nocturnal plant-flower visitor networks (hereafter, plant-pollinator networks) were built for each site during the flowering season of 2010 (Picos de Europa) and 2011 (Sierra de Guadarrama and Sierra Nevada). To build the diurnal networks, interactions between plants and floral visitors were recorded along diurnal transects at each site, where all insects contacting the reproductive structures of the flowers were recorded. The sampled area differed between sites from 500 × 250 m in Picos de Europa to 150 × 100 m in Sierra Nevada and 100 × 60 m in Sierra de Guadarrama. These differences were dependent on the small-scale heterogeneity of vegetation. The transects were evenly distributed throughout the study area. The length of the transects varied depending on the size of the study area. Diurnal transects were performed from 10 to 18 h on sunny days with mild wind conditions for pollinator activity. Nocturnal plant-pollinator networks were built for each site by trapping moths using light traps and analysing their pollen loads. Light traps consisted of a UV light surrounded by three white triangular sheets. Moths landing on the sheets were immediately trapped and stored in individual vials with a small piece of tissue and some drops of ethyl acetate.</p> <p>For more details on the methodology see original publication.</p>
A patch-dynamic metacommunity perspective on the persistence of mutualistic and antagonistic bipartite networks
<p>The structure of interactions between species within a community plays a key role in maintaining biodiversity. Previous studies have found that the effects of these structures might substantially differ depending on interaction type, for example, a highly connected and nested architecture stabilizes mutualistic communities, while the stability of antagonistic communities is enhanced in modular and weakly connected structures. Here we show that, when network dynamics are modelled using a patch-dynamic metacommunity framework, the qualitative differences between antagonistic and mutualistic systems disappear, with nestedness and modularity interacting to promote metacommunity persistence. However, the interactive effects are significantly weaker in antagonistic metacommunities. Our model also predicts an increase in connectance, nestedness and modularity over time in both types of interaction, except in antagonistic networks where nestedness declines. At steady state, we find a strong negative correlation between nestedness and modularity in both mutualistic and antagonistic metacommunities. These predictions are consistent with the structural trends found in a large dataset of real-world antagonistic and mutualistic communities.</p>
data for Newbury et al Short term fitness effects of bipartite interactions shape network structure of mutualistic and antagonistic communities
<p>speciescountdata.csv contains colony couts and plasmid detection from the main experiment.</p> <p>evonet.csv conatins colony counts of bacteria with and without plasmid pkjk5 from commuities where donors were o/ p ancestral/evolved. </p> <p>AOPV.csv contains optical density data for species a,o,p and v. column 1 is time in hours. Then columns alternate between a, o, p, s, v, a+,o+,p+,s+,v+,s+,v+ (where + denotes plasmid carriage) until column 49. After which the same patten continues, but these were grown with tetracycline. s did not grow at all in the 96-well plate this data was taken from. This is likely due to experimental error, so an additional well plate was used just for s (S.scv).</p> <p>S.csv contains optical density data for species s. column 1 is time in hours. then there are 6 colulmns of s and 6 columns of s+ until column 49. After this the same pattern continues but bacteria were grown with tetracycline.</p>
A patch-dynamic metacommunity perspective on the persistence of mutualistic and antagonistic bipartite networks
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European Procurement Markets as Bipartite Networks
<p><strong>EU Procurement Market Network Data</strong></p> <p>Johannes Wachs<br> January 2020<br> <strong>*In case you use this data, please reference:</strong> </p> <ul> <li>Wachs, J., Fazekas, M. & Kertész, J. Corruption risk in contracting markets: a network science perspective. Int J Data Sci Anal (2020). 10.1007/s41060-019-00204-1</li> <li>Available open access at: <a href="https://link.springer.com/article/10.1007%2Fs41060-019-00204-1">https://link.springer.com/article/10.1007%2Fs41060-019-00204-1</a></li> </ul> <p>These 234 networks represent the annual national public procurement markets of 26 European countries from 2008-2016, inclusive. Data is sourced from Tenders Electronic Daily (TED), the official procurement portal of the European Union.</p> <p>Nodes with the suffix "_i" are issuers (sometimes referred to as buyers) of public contracts, for instance public hospitals, ministries, local governments. Nodes with the suffix "_w" are winners (sometimes called suppliers) of public contracts, generally private-sector firms. Identities have been statistically deduplicated, as described in the paper. </p> <p>Each network is bipartite: edges only exist between issuers and winners. Edges represent contracting relationships and have two attributes: </p> <ul> <li>``count'' measures the volume of contracts between the issuer and winner in the given year. This attribute can be interpreted as a weight or strength of the relationship.</li> <li>``pctSingleBid'' describes the share of contracts between the issuer and winner awarded without competition, i.e. with the winner as single bidder or sole-supplier. Note: missing data on single-bidding is imputed. This is an elementary indicator of corruption risk of the contract. For more information consult the paper referenced above.</li> </ul> <p>Ids of issuers and winners are consistent across time and within countries. Node ids have been randomly generated and do not correspond to any official statistics.</p> <p>The networks are stored in the GML format. For example: they can be read in directly by Gephi or by the Python NetworkX library with the following commands (using the 2010 Portuguese market as an example):</p> <blockquote> <p> import networkx as nx<br> G=nx.read_gml('country_year_networks/PT_2010.gml')</p> </blockquote>
Data for paper: Comparing Measures of Centrality in Bipartite Social Networks: A Study of Drug Seeking for Opioid Analgesics
<p>Data and code for paper: Comparing Measures of Centrality in Bipartite Social Networks: A Study of Drug Seeking for Opioid Analgesics</p>
Replication data for: Sensitivity of bipartite network analyses to incomplete sampling and taxonomic uncertainty
<p>Simulated host-parasite communities in Llopis‐Belenguer, C., J. A. Balbuena, I. Blasco‐Costa, A. Karvonen, V. Sarabeev, and J. Jokela. 2022. Sensitivity of bipartite network analyses to incomplete sampling and taxonomic uncertainty. Ecology</p> <ul> <li>Full communities</li> </ul> <p>01_full_communities.RDS</p> <ul> <li>Resampled communities affected by host sampling completeness. From 90% to 10% of host sampling completeness every 10% steps</li> </ul> <p>02_resampled_sampling_completeness_90.RDS, </p> <p>03_resampled_sampling_completeness_80.RDS, </p> <p>04_resampled_sampling_completeness_70.RDS, </p> <p>05_resampled_sampling_completeness_60.RDS, </p> <p>06_resampled_sampling_completeness_50.RDS, </p> <p>07_resampled_sampling_completeness_40.RDS, </p> <p>08_resampled_sampling_completeness_30.RDS, </p> <p>09_resampled_sampling_completeness_20.RDS, </p> <p>10_resampled_sampling_completeness_10.RDS</p> <ul> <li>Resampled communities affected by parasite taxonomic resolution at all levels of host sampling completeness. From 90% to 10% of parasite taxonomic resolution and from 100% to 10% of host sampling completeness every 10% steps</li> </ul> <p>11_resampled_taxonomic_resolution_90_sampling_completeness_100-10.RDS, </p> <p>12_resampled_taxonomic_resolution_80_sampling_completeness_100-10.RDS, </p> <p>13_resampled_taxonomic_resolution_70_sampling_completeness_100-10.RDS, </p> <p>14_resampled_taxonomic_resolution_60_sampling_completeness_100-10.RDS, </p> <p>15_resampled_taxonomic_resolution_50_sampling_completeness_100-10.RDS, </p> <p>16_resampled_taxonomic_resolution_40_sampling_completeness_100-10.RDS, </p> <p>17_resampled_taxonomic_resolution_30_sampling_completeness_100-10.RDS, </p> <p>18_resampled_taxonomic_resolution_20_sampling_completeness_100-10.RDS, </p> <p>19_resampled_taxonomic_resolution_10_sampling_completeness_100-10.RDS</p> <p> </p>
Bipartite network datasets for Permian host-plant--insect herbivory
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Data from: Trophic niche similarities of sympatric Turdus thrushes determined by fecal contents, stable isotopes, and bipartite networks approaches
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Data from: Division of labor as a bipartite network
Bipartite ecological networks are increasingly used to described and model relationships between interacting species (e.g. plant-pollinator or host parasite). Here, we apply network methods developed in community ecology to quantify division of labor in insect societies. We consider two quantitative indices (H2' and d') derived from information theory that inform on how much the actual patterns of task performance deviates from the null expectation that workers perform tasks randomly. In addition, we computed network modularity to identify clusters of specialized individuals that are preferentially engaged in the completion of subset of available tasks. We analyzed both simple synthetic networks, varying in size and degree of specialization, and published datasets to introduce the metrics and to show that a bipartite approach provides useful insights into task allocation. Considering division of labor as a bipartite network offers a conceptual framework that could substantially increase our understanding of division of labor in animal societies.
Data from: Division of labor as a bipartite network
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.