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2,326 results for “clusters”
Pulsation-driven Mass Loss from Massive Stars behind Stellar Mergers in Metal-poor Dense Clusters
<p>MESA inlists, run_star_extras, and data associated with Nakauchi, Inayoshi, Omukai 2020. MESA version</p> <p>12115.</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>
Dataset for "Validation of the Astro dataset clustering solutions with external data"
<p><strong>Validation data for the <em>Astro</em> scientific publication clustering benchmark dataset</strong></p> <p>This is the dataset used in the publication Donner, P. "Validation of the Astro dataset clustering solutions with external data", Scientometrics, DOI 10.1007/s11192-020-03780-3</p> <p>Certain data included herein are derived from Clarivate Web of Science. © Copyright Clarivate 2020. All rights reserved.</p> <p>Published with permission from Clarivate.</p> <p>The original <em>Astro</em> dataset is not contained in this data. It can be obtained from http://topic-challenge.info/ and requires permission from Clarivate Analytics for use.</p> <p> </p> <p>This dataset collection consists of four files. Each file contains an independent dataset that relates to the Astro dataset via Web of Science (WoS) record identifiers. These identifiers are called UTs. All files are tabular data in CSV format. In each, at least one column contains UT data. This should be used to link to the <em>Astro </em>dataset or other WoS data. The datasets are discussed in detail in the journal publication.</p> <p> </p>
Clusterization of the normalized gene expression data
<p>Clusterization of the normalized gene expression data</p>
Data from: Cholesterol and ORP1L dependent clustering of dynein on endolysosmes in cells 2 revealed by super resolution microscopy
<p>The sub-cellular positioning of endolysosomes is crucial for regulating their function. Particularly, the positioning of endolysosomes between the cell periphery versus the peri-nuclear region impacts autophagy, mTOR (mechanistic target of rapamycin) signaling and other processes. The mechanisms that regulate the positioning of endolysosomes at these two locations are still being uncovered. Here, using quantitative super-resolution microscopy in intact cells, we show that the retrograde motor dynein forms nano-clusters on endolysosomal membranes containing 1-2 dyneins, with an average of ~3 nanoclusters per endolysosome. These data suggest that a very small number of dynein motors (1-6) drive endolysosome motility inside cells. Surprisingly, dynein nano-clusters are slightly larger on peripheral endolysosomes having higher cholesterol levels compared to peri-nuclear ones. By perturbing endolysosomal membrane cholesterol levels, we show that dynein copy number within nano-clusters is influenced by the amount of endolysosomal cholesterol while the total number of nano-clusters per endolysosome is independent of cholesterol. Finally, we show that the dynein adapter protein ORP1L (Oxysterol Binding Protein Homologue) regulates the number of dynein motors within nano-clusters in response to cholesterol levels. We propose a new model by which endolysosomal transport and positioning is influenced by the cholesterol sensing adapter protein ORP1L, which influences dynein's copy number within nano-clusters.</p>
Diversity of biosynthetic gene clusters in gut bacteria of turtle ants
<p class="Standard"><span>In insect-microbe nutritional symbioses the gut symbionts supplement the host diet with nutrients by producing amino acids and vitamins or by degrading lignin or polysaccharides macromolecules. In multipartite mutualisms composed of multiple symbionts from different taxonomical orders, it has been suggested that beside the genes involved in the nutritional symbiosis the symbionts maintain genes responsible for the production of metabolites putatively playing a role in the maintenance and interaction of the bacterial communities living in close proximity. To test this hypothesis, we investigated the diversity of biosynthetic gene clusters (BGCs) producing different non-primary metabolites in the genomes and metagenomes of the conserved gut symbionts associated with the herbivorous turtle ants (genus: <i>Cephalotes</i>). We studied 17 <i>Cephalotes</i> species collected across several geographical areas to reveal that (i) mining metagenomes and genomes show complementary results demonstrating the robustness of this approach to retrieve BGCs, (ii) the conserved gut symbionts involved in the nutritional symbiosis have a high diversity of BGCs of different chemical families, (iii) the phylogenetic analysis of BGCs encoding the production of arylpolyenes, non-ribosomal peptides (NRP), polyketides (PK), and siderophores shows high similarity between BGCs of a single symbiont across different ant host species, and between BGCs originated from different bacterial orders within a single host species. These findings together suggest multiple mechanisms of bacterial genome conservation and evolution of BGCs. We document the occurrence, diversity, and similarity of BGCs in the genome of obligate gut bacteria involved in multipartite mutualisms across the phylogeny of turtle ants.</span></p>
Data from: Effectiveness of continence promotion for older women via community organisations: a cluster randomised trial
Objectives: The primary objective of this cluster randomised controlled trial was to compare the effectiveness of the three experimental continence promotion interventions against a control intervention on urinary symptom improvement in older women with untreated incontinence recruited from community organisations. Setting: 71 community organisations across the United Kingdom Participants: 259 women aged 60 years and older with untreated incontinence entered the trial; 88% completed the 3-month follow-up. Interventions: The three active interventions consisted of a single 60-minute group workshop on 1) continence education (20 clusters, 64 women); 2) evidence-based self-management (17 clusters, 70 women); or 3) combined education and self-management (17 clusters, 61 women). The control intervention was a single 60-minute educational group workshop on memory loss, polypharmacy and osteoporosis (17 clusters, 64 women). Primary and secondary outcome measures: The primary outcome was self-reported improvement in incontinence 3 months post-intervention at the level of the individual. The secondary outcome was change in the International Consultation on Incontinence Questionnaire (ICIQ). Changes in incontinence-related knowledge and behaviours were also assessed. Results: The highest rate of urinary symptom improvement occurred in the combined intervention group (66% vs 11% of the control group, prevalence difference 55%, 95% CI 43%-67%, intracluster correlation 0). Thirty percent versus 6% of participants reported significant improvement respectively (prevalence difference 23%, 95% CI 10%-36%, intracluster correlation 0). The number-needed-to-treat was 2 to achieve any improvement in incontinence symptoms, and 5 to attain significant improvement. Compared to controls, the combined group reported an adjusted mean 2.05 point (95% CI 0.87-3.24) greater improvement on the ICIQ. Changes in knowledge and self-reported risk-reduction behaviours paralleled rates of improvement in all intervention arms. Conclusion: Continence education combined with evidence-based self-management improves symptoms of incontinence among untreated older women. Community organisations represent an untapped vector for delivering effective continence promotion interventions.
Data from: Clustered or scattered? The impact of habitat quality clustering on establishment and early spread
The match between the environmental conditions of an introduction area and the preferences of an introduced species is the first prerequisite for establishment. Yet, introduction areas are usually landscapes, i.e. heterogeneous sets of habitats that are more or less favourable to the introduced species. Because individuals are able to disperse after their introduction, the quality of the habitat surrounding the introduction site is as critical to the persistence of introduced populations as the quality of the introduction site itself. Moreover, demographic mechanisms such as Allee effects or dispersal mortality can hamper dispersal and affect spread across the landscape, in interaction with the spatial distribution of favourable habitat patches. In this study, we investigate the impact of the spatial distribution of heterogeneous quality habitats on establishment and early spread. First, we simulated introductions in one-dimensional landscapes for different dispersal rates and either dispersal mortality or Allee effects. The landscapes differed by the distribution of favourable and less favourable habitats, which were either clustered into few large aggregates of the same quality or scattered into multiple smaller ones. Second, we tested the predictions of simulations by performing experimental introductions of hymenopteran parasitoids (Trichogramma chilonis) in "clustered" and "scattered" microcosm landscapes. Results highlighted two impacts of the clustering of favourable habitat: by decreasing the risks of dispersal from the introduction site to unfavourable habitat early during the invasion, it increased establishment success. However, by increasing the distance between favourable habitat patches, it also hindered the subsequent spread of introduced species over larger areas.
Data from: Islands and streams: clusters and gene flow in wild barley populations from the Levant
The domestication of plants frequently results in a high level of genetic differentiation between domesticated plants and their wild progenitors. This process is counteracted by gene flow between wild and domesticated plants because they are usually able to inter-mate and to exchange genes. We investigated the extent of gene flow between wild barley Hordeum spontaneum and cultivated barley Hordeum vulgare, and its effect on population structure in wild barley by analyzing a collection of 896 wild barley accessions (Barley1K) from Israel and all available Israeli H. vulgare accessions from the Israeli gene bank. We compared the performance of simple sequence repeats (SSR) and single nucleotide polymorphisms (SNP) marker data genotyped over a core collection in estimating population parameters. Estimates of gene flow rates with SSR markers indicated a high level of introgression from cultivated barley into wild barley. After removing accessions from the wild barley sample that were recently admixed with cultivated barley, the inference of population structure improved significantly. Both SSR and SNP markers showed that the genetic population structure of wild barley in Israel corresponds to the three major ecogeographic regions: the coast, the Mediterranean north, and the deserts in the Jordan valley and the South. Gene flow rates were estimated to be higher from north to south than in the opposite direction. As has been observed in other crop species, there is a significant exchange of alleles between the wild species and domesticated varieties that needs to be accounted for in the population genetic analysis of domestication.
Data from: EdAl-2 (Educació en Alimentació) programme: reproducibility of a cluster randomised, interventional, primary-school-based study to induce healthier lifestyle activities in children
Objectives: To assess the reproducibility of an educational intervention EdAl-2 (Educació en Alimentació) programme in 'Terres de l'Ebre' (Spain), over 22 months, to improve lifestyles, including diet and physical activity (PA). Design: Reproduction of a cluster randomised controlled trial. Setting: Two semi-rural town-group primary-school clusters were randomly assigned to the intervention or control group. Participants: Pupils (n=690) of whom 320 constituted the intervention group (1 cluster) and 370 constituted the control group (1 cluster). Ethnicity was 78% Western European. The mean age (±SD) was 8.04±0.6 years (47.7% females) at baseline. Inclusion criteria for clusters were towns from the southern part of Catalonia having a minimum of 500 children aged 7–8 year; complete data for participants, including name, gender, date and place of birth, and written informed consent from parents or guardians. Intervention: The intervention focused on eight lifestyle topics covered in 12 activities (1 h/activity/session) implemented by health promoting agents in the primary school over three academic years. Primary and secondary outcomes: The primary outcome was obesity (OB) prevalence and the secondary outcomes were body mass index (BMI) collected every year and dietary habits and lifestyles collected by questionnaires filled in by parents at baseline and end-of-study. Results: At 22 months, the OB prevalence and BMI values were similar in intervention and control groups. Relative to children in control schools, the percentage of boys in the intervention group who performed ≥4 after-school PA h/week was 15% higher (p=0.027), whereas the percentage of girls in both groups remained similar. Also, 16.6% more boys in the intervention group watched ≤2 television (TV) h/day (p=0.009), compared to controls; and no changes were observed in girls in both groups. Conclusions: Our school-based intervention is feasible and reproducible by increasing after-school PA (to ≥4 h/week) in boys. Despite this improvement, there was no change in BMI and prevalence of OB.
Data from: Beech roots are simultaneously colonized by multiple genets of the ectomycorrhizal fungus Laccaria amethystina clustered in two genetic groups
In this study we characterize and compare the genetic structure of aboveground and belowground populations of the ectomycorrhizal fungus Laccaria amethystina in an unmanaged mixed beech forest. Fruiting bodies and mycorrhizas of L. amethystina were mapped and collected in four plots in the Świętokrzyskie Mountains (Poland). A total of 563 fruiting bodies and 394 mycorrhizas were successfully genotyped using the rDNA IGS1 (intergenic spacer) and seven SSR (simple sequence repeat) markers. We identified two different genetic clusters of L. amethystina in all of the plots, suggesting that a process of sympatric isolation may be occurring at a local scale. The proportion of individuals belonging to each cluster was similar among plots aboveground while it significantly differed belowground. Predominance of a given cluster could be explained by distinct host preferences or by priority effects and competition among genets. Both aboveground and belowground populations consisted of many intermingling small genets. Consequently, host trees were simultaneously colonized by many L. amethystina genets that may show different ecophysiological abilities. Our data showed that several genets may last for at least one year belowground and sustain into the next season. Ectomycorrhizal species reproducing by means of spores can form highly diverse and persistent belowground genets that may provide the host tree with higher resilience in a changing environment and enhance ecosystem performance.
Inference of nonlinear receptive field subunits with spike-triggered clustering
<p>Responses of sensory neurons are often modeled using a weighted combination of rectified linear subunits. Since these subunits often cannot be measured directly, a flexible method is needed to infer their properties from the responses of downstream neurons. We present a method for maximum likelihood estimation of subunits by soft-clustering spike-triggered stimuli, and demonstrate its effectiveness in visual neurons. Subunits estimated from parasol retinal ganglion cells (RGCs) in macaque retina partitioned the receptive field into compact regions, likely representing aggregated bipolar cell inputs. Joint clustering revealed shared subunits in neighboring RGCs, producing a parsimonious population model. Closed-loop validation, using stimuli lying in the null space of the linear receptive field, revealed stronger nonlinearities in OFF cells than ON cells. Responses to natural images, jittered to emulate fixational eye movements, were accurately predicted by the subunit model. Finally, the generality of the approach was demonstrated in macaque V1 neurons.</p>
Data from: Estimating density from presence/absence data in clustered populations
<p>1. Inventories of plant populations are fundamental in ecological research and monitoring, but such surveys are often prone to field assessment errors. Presence/absence (P/A) sampling may have advantages over plant cover assessments for reducing such errors. However, the linking between P/A data and plant density depends on model assumptions for plant spatial distributions. Previous studies have shown, for example, how that plant density can be estimated under Poisson model assumptions on the plant locations. In this study new methods are developed and evaluated for linking P/A data with plant density assuming that plants occur in clustered spatial patterns.<br> 2. New theory was derived for estimating plant density under Neyman-Scott type cluster models such as the Matérn and Thomas cluster processes. Suggested estimators, corresponding confidence intervals, and a proposed goodness-of-fit test were evaluated in a Monte-Carlo simulation study assuming a Matérn cluster process. Further, the estimators were applied to plant data from environmental monitoring in Sweden to demonstrate their empirical application.<br> 3. The simulation study showed that our methods work well for large enough sample sizes. The judgment of what is "large enough'' is often difficult, but simulations indicate that a sample size is large enough when the sampling distributions of the parameter estimators are symmetric or mildly skewed. Bootstrap may be used to check whether this is true. The empirical results suggests that the derived methodology may be useful for estimating density of plants such as <em>Leucanthemum vulgare</em> and <em>Scorzonera humilis</em>.<br> 4. By developing estimators of plant density from P/A data under realistic model assumptions about plants' spatial distributions, P/A sampling will become a more useful tool for inventories of plant populations. Our new theory is an important step in this direction.</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.
Data from: Arsenic induces members of the mmu-miR-466-669 cluster which reduces NeuroD1 expression
Chronic arsenic exposure can result in adverse development effects including decreased intellectual function, reduced birth weight, and altered locomotor activity. Previous in vitro studies have shown that arsenic inhibits stem cell differentiation. MicroRNAs (miRNAs) are small non-coding RNAs that regulate multiple cellular processes including embryonic development and cell differentiation. The purpose of this study was to examine whether altered miRNA expression was a mechanism by which arsenic inhibited cellular differentiation. The pluripotent P19 mouse embryonal carcinoma cells were exposed to 0 or 0.5 μM sodium arsenite for 9 days during cell differentiation, and changes in miRNA expression was analyzed using microarrays. We found that the expression of several miRNAs important in cellular differentiation, such as miR-9 and miR-199 were decreased by 1.9- and 1.6-fold respectively following arsenic exposure, while miR-92a, miR-291a, and miR-709 were increased by 3-, 3.7- and 1.6-fold, respectively. The members of the miR-466-669 cluster and its host gene, Scm-Like with four Mbt domains 2 (Sfmbt2), were significantly induced by arsenic from 1.5- to 4-fold in a time-dependent manner. Multiple miRNA target prediction programs revealed that several neurogenic transcription factors appear to be targets of the cluster. When consensus anti-miRNAs targeting the miR-466-669 cluster were transfected into P19 cells, arsenic-exposed cells were able to more effectively differentiate. The consensus anti-miRNAs appeared to rescue the inhibitory effects of arsenic on cell differentiation due to an increased expression of NeuroD1. Taken together, we conclude that arsenic induces the miR-466-669 cluster, and that this induction acts to inhibit cellular differentiation in part due to a repression of NeuroD1.
Data from: An evolutionary history of the selectin gene cluster in humans
Molecules involved in leukocyte trafficking have a central role in the development of inflammatory and immune responses. We performed FST analysis of the selectin cluster, as well as of SELPLG, ICAM1 and VCAM1. Peaks of significantly high population genetic differentiation were restricted to two regions in SELP and one in SELPLG. Resequencing data indicated that the region covering SELP exons 11–13 displays high nucleotide diversity in Africans and Europeans (CEU), and a high level of within-species diversity compared with inter-specific divergence. Analysis of inferred haplotypes revealed a complex phylogeny with two deeply separated clades that coalesce at ~3.5 million years (MY) plus a minor clade with a TMRCA (time to the most recent common ancestor) of ~2.2 MY. A splicing assay indicated no haplotype-specific effect on SELP exon 14 inclusion. These data are consistent with a model of multiallelic balancing selection; single-nucleotide polymorphism analysis indicated that the Val640Leu variant represents a likely selection target. In populations of Asian ancestry a distinct haplotype, possibly carrying regulatory variants, has been driven to high frequency by positive selection. No deviation from neutrality was observed for the SELPLG region. Resequencing of SELP in chimpanzees revealed a haplotype phylogeny with extremely deep basal branches, suggesting either long-standing balancing selection or ancestral population structure. Thus, SELP has experienced a complex selective history, possibly as a result of local adaptation. Variants in the gene have been associated with autoimmune and cardiovascular diseases. Association studies would benefit from both taking the complex SELP haplotype structure into account and from analysis of possible regulatory variants in the gene.
Data from: Evolutionary ecology of beta-lactam gene clusters in animals
Beta-lactam biosynthesis was thought to occur only in fungi and bacteria, but we recently reported the presence of isopenicillin N synthase in a soil-dwelling animal, Folsomia candida. However, it has remained unclear whether this gene is part of a larger beta-lactam biosynthesis pathway and how widespread the occurrence of penicillin biosynthesis is among animals. Here, we analyzed the distribution of beta-lactam biosynthesis genes throughout the animal kingdom and identified a beta-lactam gene cluster in the genome of F. candida (Collembola), consisting of isopenicillin N synthase (IPNS), δ-(L-α-aminoadipoyl)-L-cysteinyl-D-valine synthetase (ACVS), and two cephamycin C genes (cmcI and cmcJ) on a genomic scaffold of 0.76 Mb. All genes are transcriptionally active and are inducible by stress (heat shock). A beta-lactam compound was detected in vivo using an ELISA beta-lactam assay. The gene cluster also contains an ABC transporter which is co-regulated with IPNS and ACVS after heat shock. Furthermore, we show that different combinations of beta-lactam biosynthesis genes are present in over 60% of springtail families but they are absent from genome- and transcript libraries of other animals including close relatives of springtails (Protura, Diplura, and insects). The presence of beta-lactam genes is strongly correlated with an eudaphic (soil-living) lifestyle. Beta-lactam genes IPNS and ACVS each form a phylogenetic clade in between bacteria and fungi, while cmcI and cmcJ genes cluster within bacteria. This suggests a single horizontal gene transfer event most probably from a bacterial host, followed by differential loss in more recently evolving species.
Data from: Defector clustering is linked to cooperation in a pathogenic bacterium
Spatial clustering is thought to favour the evolution of cooperation because it puts cooperators in a position to help each other. However, clustering also increases competition. The fate of cooperation may depend on how much cooperators cluster relative to defectors, but these clustering differences have not been the focus of previous models and experiments. By competing siderophore-producing cooperator and defector strains of the opportunistic pathogen Pseudomonas aeruginosa in experimental microhabitats, we found that at the spatial scale of individual interactions, cooperator clustering lowers cooperation, but defector clustering favours cooperation. A theoretical model and individual-based simulations show these counterintuitive effects can arise when competition and cooperation occur at a single resource-determined scale, with population dynamics crucially allowing cooperators and defectors to cluster differently. The results suggest that cooperation relies on the regulation of sufficient defector clustering relative to cooperator clustering, which may be important in bacteria, social amoeba, and cancer inhibition.
Data from "Linked Coupled Cluster Monte Carlo"
<p>We consider a new formulation of the stochastic coupled cluster method in terms of the similarity transformed Hamiltonian. We show that improvement in the granularity with which the wavefunction is represented results in a reduction in the critical population required to correctly sample the wavefunction for a range of systems and excitation levels and hence leads to a substantial reduction in the computational cost. This development has the potential to substantially extend the range of the method, enabling it to be used to treat larger systems with excitation levels not easily accessible with conventional deterministic methods.</p>
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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.