Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
103
datasets available to search
ShareScore release 0.9.0
Dataset results
103 results for “bootstrap”
indicate branches. above MrBayes numbers by inferred The . supports Ixodes of probability subgenera 22 posterior the of Inference 16 from Bayesian ticks of indicate genomes mitochondrial branches below 40 numbers of The sequences. RAxML nucleotide by the inferred from support inferred bootstrap Phylogenies Likelihood . 2 FIGURE Maximum in A new subgenus, Australixodes n. subgen. (Acari: Ixodidae), for the kiwi tick, Ixodes anatis Chilton, 1904, and validation of the subgenus Coxixodes Schulze, 1941 with a phylogeny of 16 of the 22 subgenera of Ixodes Latreille, 1795 from entire mitochondrial genome sequences
indicate branches. above MrBayes numbers by inferred The . supports Ixodes of probability subgenera 22 posterior the of Inference 16 from Bayesian ticks of indicate genomes mitochondrial branches below 40 numbers of The sequences. RAxML nucleotide by the inferred from support inferred bootstrap Phylogenies Likelihood . 2 FIGURE Maximum
FIGURE4. Maximum-likelihood tree inferred from 694 bp of COI using a HKY+G substitution model implemented in MEGAX (Kumar et al. 2018). Bootstrap values are indicated on the nodes. in --Molecular--and--acoustic--evidence--support--the--species--status--of--Anthus rubescens rubescens and--Anthus [rubescens] japonicus--(Passeriformes:--Motacillidae)
FIGURE4. Maximum-likelihood tree inferred from 694 bp of COI using a HKY+G substitution model implemented in MEGAX (Kumar et al. 2018). Bootstrap values are indicated on the nodes.
FIGURE3. Maximum-likelihood tree inferred from 998 bp of CR using a HKY+G substitution model implemented in MEGAX (Kumar et al. 2018). Bootstrap values are indicated on the nodes. in --Molecular--and--acoustic--evidence--support--the--species--status--of--Anthus rubescens rubescens and--Anthus [rubescens] japonicus--(Passeriformes:--Motacillidae)
FIGURE3. Maximum-likelihood tree inferred from 998 bp of CR using a HKY+G substitution model implemented in MEGAX (Kumar et al. 2018). Bootstrap values are indicated on the nodes.
The asymptotic behavior of bootstrap support values in molecular phylogenetics
Open the record for dataset details and reuse information.
Hamlet aggressive mimicry: permanovas and bootstraps results on dS, dL
Open the record for dataset details and reuse information.
Improving Phylogenies Based on Average Nucleotide Identity, Incorporating Saturation Correction and Non-Parametric Bootstrap Support
Open the record for dataset details and reuse information.
Figure 4. Optimal maximum-likelihood tree resulting from the RAxML analysis. Bootstrap support values greater than 50 in Taxonomy of Micronesian monitors (Reptilia: Squamata: Varanus): endemic status of new species argues for caution in pursuing eradication plans
Figure 4. Optimal maximum-likelihood tree resulting from the RAxML analysis. Bootstrap support values greater than 50% are shown on the nodes. Scale bar corresponds to the mean number of nucleotide substitutions per site.
Raw data and results for the paper "Conditional non-parametric bootstrap for non-linear mixed effect models"
<p>*Data* (comets_condBoot_data.zip)</p> <p>Data was simulated according to an Emax model (scenarios 1 and 2) or a Hill model (scenarios 3 and 4). The archive contains 4 folders with the data simulated in the first 4 scenarios (N=200 simulated datasets in each folder):<br> - scenario 1 - pdemax.rich<br> - scenario 2 - pdemax.sparse<br> - scenario 3 - pdhillhigh.rich<br> - scenario 4 - pdhillhigh.sparse<br> The data used in scenarios 5 and 6 was a subset of the datasets simulated in scenarios 3 and 4 respectively. In scenario 5, 20 subjects were taken from each dataset (subjects 1-5, 26-30, 51-55, 76-80) from the datasets in folder pdhillhigh.rich. In scenario 6, the datasets were constituted by the first 20 subjects from each sampling group of the data simulated in pdhillhigh.sparse.</p> <p>*Results:* (comets_scenarioXXX_results.zip, XXX=1,.. 6)</p> <p>6 simulation scenarios were assessed in the paper. Each file corresponds to 1 of 6 folders, one for each scenario:<br> - scenario 1 - pdemax.rich/results<br> - scenario 2 - pdemax.sparse/results<br> - scenario 3 - pdhillhigh.rich/results<br> - scenario 4 - pdhillhigh.sparse/results<br> - scenario 5 - pdhillhigh.n20rich/results<br> - scenario 6 - pdhillhigh.n20sparse/results</p> <p>In each "results" subfolder, the results for each bootstrap method and each dataset are written to a separate file, eg for simulation 1 in the first scenario:<br> - case bootstrap: scenarioHill1_bootstrapCase_sim1.res <br> - non-parametric bootstrap: scenarioHill1_bootstrapNP_sim1.res<br> - conditional non-parametric bootstrap: scenarioHill1_bootstrapNPc_sim1.res<br> - parametric bootstrap: scenarioHill1_bootstrapPar_sim1.res<br> The folder also contains:<br> - the saemix estimates for the 200 simulations: scenarioHill1_fitOrig.res<br> - tables with the bias and SE for the different bootstraps over the set of simulations, used to evaluate the methods: rbiasSEboot200.res, rbiasSEboot.res, rbiasWRsampleEstimates.res</p> <p> </p>
Data from: On the variety of methods for calculating confidence intervals by bootstrapping
1. Researchers often want to place a confidence interval around estimated parameter values calculated from a sample. This is commonly implemented by bootstrapping. There are several different frequently used bootstrapping methods for this purpose. 2. Here we demonstrate that authors of recent papers frequently do not specify the method they have used and that different methods can produce markedly different confidence intervals for the same sample and parameter estimate. 3. We encourage authors to be more explicit about the method they use (and number of bootstrap resamples used). 4. We recommend the bias corrected and accelerated method as giving generally good performance; although researchers should be warned that coverage of bootstrap confidence intervals is characteristically less than the specified nominal level, and confidence interval evaluation by any method can be unreliable for small samples in some situations.
Fig. 2. Maximum Likelihood tree for genus Fusicolla with RPB2 dataset. Node numbers indicate bootstrap value above 70 in First report of seven unrecorded bambusicolous fungi in Korea
Fig. 2. Maximum Likelihood tree for genus Fusicolla with RPB2 dataset. Node numbers indicate bootstrap value above 70%. Blue colored name indicates the strains isolated in this study. Type strains are indicated by "T".
Fig. 4. Bootstrap consensus tree inferred from 1000 replicates, using the Maximum Likelihood method. The analysis involved 20 in Severe coenurosis caused by larvae of Taenia serialis in an olive baboon (Papio anubis) in Benin
Fig. 4. Bootstrap consensus tree inferred from 1000 replicates, using the Maximum Likelihood method. The analysis involved 20 sequences of 12S rDNA gene of cestodes having coenurus type larvae (Taenia serialis and T. multiceps) and one sequence of Echinococcus granulosus, as outgroup. For each sequence, the GenBank Accession number, species, developmental stage, host and geographic origin are provided. A total of 320 positions were included in the dataset. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches.
Supplementary phylogenetic trees of Babesia bigemina based on partial sequences of both genes Rap-1a and gp45, with SH-aLRT support values (%), aBayes support, and ultrafast bootstrap support (%).
Open the record for dataset details and reuse information.
Figure 5. Bootstrap 50 in Evolutionary systematics of the Indian mouse Mus famulus Bonhote, 1898: molecular (DNA/DNA hybridization and 12S rRNA sequences) and morphological evidence
Figure 5. Bootstrap 50% majority rule consensus tree from analysis of the morphological data. Bootstrap support values (100 heuristic bootstrap replicates, 10 addition replicates, random addition sequence) are shown above the branches.
Data from: Generalized bootstrap supports for phylogenetic analyses of protein sequences incorporating alignment uncertainty
Open the record for dataset details and reuse information.
Data from: On the variety of methods for calculating confidence intervals by bootstrapping
Open the record for dataset details and reuse information.
Fig. Sa/b: (a) Strict consensus of 2 most parsimonious trees generated by exact analysis of sequence data. Numbers on branches represent bootstrap node confidence values from 100 replications. (b) Jac support tree. Numbers on branches represent confidence frequencies in nodes as quantified by parsimony jacknifing with Jac (Farris 1995). in Morphological and mitochondrial-DNA variation in Rhinolophus rouxii (Chiroptera)
Fig. Sa/b: (a) Strict consensus of 2 most parsimonious trees generated by exact analysis of sequence data. Numbers on branches represent bootstrap node confidence values from 100 replications. (b) Jac support tree. Numbers on branches represent confidence frequencies in nodes as quantified by parsimony jacknifing with Jac (Farris 1995).
FIGURE 31. Bootstrap consensus tree from W in Mitochondrial sequence data clarify species concepts in the Cyclocephala mafaffa species complex (Coleoptera: Scarabaeidae: Dynastinae: Cyclocephalini)
FIGURE 31. Bootstrap consensus tree from W-IQ-TREE analysis. Node support values from left to right are maximum likelihood bootstrap, parsimony bootstrap, and Bayesian posterior probability. Support values labeled with a "*" have 100% bootstrap support or 1.0 posterior probability. Support values labeled with a "-" have bootstrap supports lower than 50% or posterior probability lower than 0.95. Nodes labeled "--" indicates that node was not recovered by an analysis. Colored branches highlight taxa of the C. mafaffa species complex (green = C. deceptor; red = C. mafaffa mafaffa; blue = C. mafaffa grandis).
Fig. 5 Cluster analysis with multiscale bootstrap values for a in Coupling impoverishment analysis and partitioning of beta diversity allows a comprehensive description of Odonata biogeography in the Western Mediterranean
Fig. 5 Cluster analysis with multiscale bootstrap values for a the Sørensen index and b the Simpson index. The number of IndVal significant species is also reported for each cluster
FIGURE. Phylogram of Tolypocladium generated from Maximum likelihood analysis of ITS, SSU and LSU sequence data. Purpureocillium lilacinum (CBS 284.36) was selected as an outgroup taxon. The tree topology of the ML analysis was similar to the BI. Maximum likelihood bootstrap values greater than 75 and Bayesian posterior probabilities over 0.90 were indicated above the nodes. The scale bar indicates 0.006 changes. The new species was in blue. in Yunnan-Guizhou Plateau: a mycological hotspot
FIGURE. Phylogram of Tolypocladium generated from Maximum likelihood analysis of ITS, SSU and LSU sequence data. Purpureocillium lilacinum (CBS 284.36) was selected as an outgroup taxon. The tree topology of the ML analysis was similar to the BI. Maximum likelihood bootstrap values greater than 75 and Bayesian posterior probabilities over 0.90 were indicated above the nodes. The scale bar indicates 0.006 changes. The new species was in blue.
Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS V004
This sea ice concentration data set was derived using measurements from the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite and from the Special Sensor Microwave/Imager (SSM/I) sensors on the Defense Meteorological Satellite Program's (DMSP) -F8, -F11, and -F13 satellites. Measurements from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard DMSP-F17 are also included. The data set has been generated using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) Bootstrap Algorithm with daily varying tie-points. Daily (every other day prior to July 1987) and monthly data are available for both the north and south polar regions. Data are gridded on the SSM/I polar stereographic grid (25 x 25 km) and provided in two-byte integer format. Data coverage began on 01 November 1978 and is ongoing through the most current processing, with updated data processed several times annually.
ScienceDex guides
Understand access before you commit
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.