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56 results for “Cluster structures”
Figure 3. Cluster Dendrogram indicating 11 in Composition and structure of plant communities in the Moist Temperate Forest Ecosystem of the Hindukush Mountains, Pakistan
Figure 3. Cluster Dendrogram indicating 11 plant association types in the Lalkoo Valley.
Original Data for Publication: Exceptionally Stable Dimers and Trimers of Au25 Clusters Linked with a Bidentate Dithiol: Synthesis, Structure and Chirality Study.
<p>Original Data for Publication: Exceptionally Stable Dimers and Trimers of Au25 Clusters Linked with a Bidentate Dithiol: Synthesis, Structure and Chirality Study. Angewandte Chemie, 2023</p>
Assessing changes in clusters of wildlife road mortalities after the construction wildlife mitigation structures
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Data from: On the spatial clustering of behavioural phenotypes: Matching movement tactics with landscape structure in a large herbivore
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Data from: Population clustering and clonal structure evidence the relict state of Ulmus minor Mill. in the Balearic Islands
Field elm (Ulmus minor) is a riparian tree that grows in rare, small populations scattered along temporary watercourses in the Balearic Islands, nowadays mostly covered with Mediterranean vegetation. Agriculture and farming on the fertile land along the periodically flooded plains have reduced the elm populations to sparse tree lines along the creek beds. The presence of field elm in this very anthropic landscape has led some authors to consider it as an introduced species in the Balearics. However, pollen data suggest these elms may be the remains of larger populations experiencing continuous population shrinkage during the Holocene, and hence be native to the isles. In this paper, we apply genetic markers to assess whether field elm is or is not indigenous to the Balearic Islands. We compare the genetic variation in nine nuclear microsatellites of six Balearic populations (three in each of the largest islands, Majorca and Minorca) with that of three natural Iberian populations located in two regions, one geologically (Baetic mountains, SE Iberia) and another historically (Catalonia, NE Iberia) related to the islands. Principal coordinates analysis and Bayesian clustering methods reveal a strong genetic differentiation of the Balearic populations from the Iberian ones, and even among islands, which support their native origin. Genotypic variation in the islands is very low and clonal reproduction is very high compared with the mainland, as it is frequently observed in populations of clonal species where sexual reproduction is limited. We discuss the practical implications of these findings for the conservation of elm genetic resources of these findings.
AFM data of ice clusters on Cu(111) and Au(111) in paper "Structure discovery in Atomic Force Microscopy imaging of ice"
<p>Frequency shift CO-tip atomic force microscopy data of small ice clusters on Cu(111) and Au(111) surfaces as they appear in the paper "Structure discovery in Atomic Force Microscopy imaging of ice".</p><p>The data are saved in a compressed .tar.gz archive. The unpacked archive contains each experiment as a Numpy .npz file. Each file contains the measurement data as a 3D array in the key 'data' and the physical extent of the scan region in the x and y directions in Ånströms in the keys 'lengthX' and 'lengthY'.</p>
Hartree potentials and geometries of relaxed on-surface ice clusters in "Structure discovery in Atomic Force Microscopy imaging of ice"
<p>Hartree potentials and geometries of on-surface DFT-relaxed ice clusters used in the paper "Structure discovery in Atomic Force Microscopy imaging of ice".</p><p>The data are saved in a compressed .tar.gz archive. The unpacked archive contains the data for each ice cluster in the .xsf format. The density functional theory (DFT) calculations were done using the Vienna Ab-initio Simulation Package with the optB86b-vdW density functional.</p>
Structural files of algorithmically generated molybdenum oxide clusters
<p>Structural files of algorithmically generated molybdenum oxide clusters. The new clusters were generated to fit experimental pair distribution functions of molybdenum oxide surface layers supported on Al<sub>2</sub>O<sub>3 </sub>and zeolites. Results are published in article XXX</p>
Fig. 3 in From clustering to overdispersion: a north to south gradient in the patterns of phylogenetic structure in North American hummingbird assemblages
Fig. 3 Boxplots of MPD, MNTD, pMPD, and pMNTD between breeding and winter seasons by biogeographic region
Fig. 2 in From clustering to overdispersion: a north to south gradient in the patterns of phylogenetic structure in North American hummingbird assemblages
Fig. 2 Geographic patterns of phylogenetic and phenotypic MPDs and MNTDs across North America according to seasons considered (breeding and winter)
Fig. 1 in From clustering to overdispersion: a north to south gradient in the patterns of phylogenetic structure in North American hummingbird assemblages
Fig. 1 Phylogenetic heatmap of the pruned phylogenetic tree (see Methods) based on McGuire et al. (2014) for North American hummingbird species and the matrix of the PC from phylogenetic PCA scores. Colors indicate standard deviation (SD) values for each PC axis by species
Data from: The association between a nurse cushion plant and a cluster-root bearing tree species alters the plant community structure
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Data from: Population clustering and clonal structure evidence the relict state of Ulmus minor Mill. in the Balearic Islands
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Data from: Sequence clustering threshold has little effect on the recovery of microbial community structure
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SVXplorer: three-tier approach to identification of structural variants via sequential recombination of discordant cluster signatures
<p>This repository contains the bgzipped variants calls in VCF format for CHM1, NA12878 and AJ trio dataset that are used in the SVXplorer manuscript. The names of the files contain the name of the sample (CHM1/NA12878/HG002/HG003/HG004), the name of the method (SVXplorer/DELLY/LUMPY/TIDDIT/TARDIS/MANTA) used to call the variants. There are three separate files for the DELLY calls which have the deletions, duplications and the inversion calls made by DELLY for each of the samples. For NA12878, there are two sets of calls, one for each of the libraries (ERR194147/SRR505885)</p> <p> </p>
Data for "A Stepwise Clustered Hydrological Model for Addressing the Autocorrelation Structure of Streamflow in Irrigated Watersheds"
<p>This data set contains hydrological input (goundwater depth, streamflow and irrigation) for the study of "<strong>A Stepwise Clustered Hydrological Model for Addressing the Autocorrelation Structure of Streamflow in Irrigated Watersheds</strong>"</p> <p>For more information please contact the author.</p>
Data from: STRUCTURE is more robust than other clustering methods in simulated mixed-ploidy populations
Analyses of population genetic structure has become a standard approach in population genetics. In polyploid complexes, clustering analyses can elucidate the origin of polyploid populations and patterns of admixture between different cytotypes. However, combining diploid and polyploid data can theoretically lead to biased inference with (artefactual) clustering by ploidy. We used simulated mixed-ploidy (diploid-autotetraploid) data to systematically compare the performance of k-means clustering and the model-based clustering methods implemented in STRUCTURE, ADMIXTURE, FASTSTRUCTURE and INSTRUCT under different scenarios of differentiation and with different marker types. Under scenarios of strong population differentiation, the tested applications performed equally well. However, when population differentiation was weak, STRUCTURE was the only method that allowed unbiased inference with markers with limited genotypic information (co-dominant markers with unknown do sage or dominant markers). Still, since STRUCTURE was comparably slow the much faster but less powerful FASTSTRUCTURE provides a reasonable alternative for large datasets. Finally, although bias makes k-means clustering unsuitable for markers with incomplete genotype information, given large numbers of loci (>1000) with known dosage k-means clustering was superior to FASTSTRUCTURE in terms of power and speed. We conclude that STRUCTURE is the most robust method for the analysis of genetic structure in mixed-ploidy populations, although alternative methods should be considered under some specific conditions.
Data from: The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis
The inference of population genetic structures is essential in many research areas in population genetics, conservation biology and evolutionary biology. Recently, unsupervised Bayesian clustering algorithms have been developed to detect a hidden population structure from genotypic data, assuming among others that individuals taken from the population are unrelated. Because of this hypothesis, markers in a sample taken from a subpopulation can be considered to be in Hardy-Weinberg and linkage equilibrium. However, close relatives might be sampled from the same subpopulation, and consequently, might cause Hardy-Weinberg and linkage disequilibrium and thus bias a population genetic structure analysis. In this study, we used simulated and real data to investigate the impact of close relatives in a sample on Bayesian population structure analysis. We also showed that, when close relatives were identified by a pedigree reconstruction approach and removed, the accuracy of a population genetic structure analysis can be greatly improved. The results indicate that unsupervised Bayesian clustering algorithms cannot be used blindly to detect genetic structure in a sample with closely related individuals. Rather, when closely related individuals are suspected to be frequent in a sample, these individuals should be first identified and removed before conducting a population structure analysis.
The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical datasets
<p class="CxSpFirst">The software program STRUCTURE is one of the most cited tools for determining population structure. To infer the optimal number of clusters from STRUCTURE output, the Δ<i>K</i> method is often applied. However, a recent study relying on simulated microsatellite data suggested that this method has a downward bias in its estimation of <i>K</i> and is sensitive to uneven sampling. If this finding holds for empirical datasets, conclusions about the scale of gene flow may have to be revised for a large number of studies. To determine the impact of method choice, we applied recently described estimators of <i>K</i> to re-estimate genetic structure in 41 empirical microsatellite datasets; 15 from a broad range of taxa and 26 focused on a diverse phylogenetic group, coral. We compared alternative estimates of <i>K</i> (Puechmaille statistics) with traditional (Δ<i>K</i> and posterior probability) estimates and found widespread disagreement of estimators across datasets. Thus, one estimator alone is insufficient for determining the optimal number of clusters regardless of study organism or evenness of sampling scheme. Subsequent analysis of molecular variance (AMOVA) between clustering solutions did not necessarily clarify which solution was best. To better infer population structure, we suggest a combination of visual inspection of STRUCTURE plots and calculation of the alternative estimators at various thresholds in addition to Δ<i>K</i>. Differences between estimators could reveal patterns with important biological implications, such as the potential for more population structure than previously estimated, as was the case for many studies reanalyzed here.</p>
Supplementary Materials for article on entitled 'Structure and usage do not explain each other: An analysis of German word-initial clusters', published in Linguistics
<p>See the article for a description of the data</p>
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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.