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236 results for “Modeling Methods”
Data from: Quantifying demographic uncertainty: Bayesian methods for integral projection models (IPMs)
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Quantitative and qualitative methods complementing: Bridging modelling and policy-making efforts to realise the European bioeconomy
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Study on a quantitative method for determining mixing proportion of transparent cemented soil for visual geotechnical model tests
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Data from: A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods
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LeWoS: A universal leaf‐wood classification method to facilitate the 3D modelling of large tropical trees using terrestrial LiDAR
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Data from: A comparison of regression methods for model selection in individual-based landscape genetic analysis
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Data from: Penalized likelihood methods improve parameter estimates in occupancy models
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Simulations scripts for: Strain localization patterns and thrust propagation in 3-D discrete element method (DEM) models of accretionary wedges
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A new method for integrating ecological niche modeling with phylogenetics to estimate ancestral distributions
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Data for exploring topography-based methods for downscaling subgrid precipitation for use in Earth System Models
<p>Topography exerts major control on land surface processes. To improve representation of topographic impacts on land surface processes, a new topography-based subgrid structure has been introduced to the Energy Exascale Earth System Model representing the subgrid heterogeneity of surface elevation. Four topography-based methods of downscaling grid precipitation to the subgrids have been explored. The data utilized for the study include precipitation, surface elevation, and height rise data derived from wind speed and Brunt Vaisala parameter and outputs of downscaled precipitation and statistical metrics calculated in this study. Results show that utilizing hypsometric elevation of the subgrid landscape within the model grid cell improves downscaling of precipitation in mountainous areas. Furthermore, accounting for blocking of airflow further improves precipitation downscaling slightly in mountainous regions consistently across multiple grid sizes.</p> <p>The data files include:</p> <ol> <li><a href="https://zenodo.org/api/files/12bc9f1c-be98-4721-8c92-6e23845be441/daily_prism_precip.zip?versionId=be97ca8d-182a-4f1e-9ae3-9da3f2b87e24">daily_prism_precip.zip</a>: high resolution precipitation data (4 km) obtained from PRISM [Daly et al. 1994, Daly et al. 2008].</li> <li> <a href="https://zenodo.org/api/files/12bc9f1c-be98-4721-8c92-6e23845be441/dem_4km4.nc">dem_4km4.nc</a>: 4 km surface elevation data derived from high resolution surface elevation data (90 m) obtained from HydroSHEDS [Lehner et al. 2008, Lehner and Grill 2013]</li> <li><a href="https://zenodo.org/api/files/12bc9f1c-be98-4721-8c92-6e23845be441/fr_number.zip?versionId=eacb5b60-9561-47f9-97c6-cd91e96afa1f">fr_number.zip</a>: Height rise of airflow calculated from wind speed and Brunt Vaisala parameter derived from the North American Regional Reanalysis data.</li> <li><a href="https://zenodo.org/api/files/12bc9f1c-be98-4721-8c92-6e23845be441/output_from_dwnscaling_methods_at_128km.zip?versionId=5f64ec8c-4018-4d97-ae1d-eb6f15ccc564">output_from_dwnscaling_methods_at_128km.zip</a>: Output data of the downscaling methods at 128 km spatial resolution.</li> <li><a href="https://zenodo.org/api/files/12bc9f1c-be98-4721-8c92-6e23845be441/output_from_dwnscaling_methods_at_96km.zip?versionId=b2c67f80-9794-41cb-9986-a4c7259ccf1c">output_from_dwnscaling_methods_at_96km.zip</a>: Output data of the downscaling methods at 96 km spatial resolution. </li> <li><a href="https://zenodo.org/api/files/12bc9f1c-be98-4721-8c92-6e23845be441/output_from_dwnscaling_methods_at_64km.zip?versionId=b83230a0-308e-4f90-971b-6636a5add796">output_from_dwnscaling_methods_at_64km.zip</a>: Output data of the downscaling methods at 64 km spatial resolution.</li> <li><a href="https://zenodo.org/api/files/12bc9f1c-be98-4721-8c92-6e23845be441/output_from_dwnscaling_methods_at_32km.zip?versionId=cc9021cc-c3b4-4c04-a558-752c151c49ba">output_from_dwnscaling_methods_at_32km.zip</a>: Output data of the downscaling methods at 32 km spatial resolution. </li> <li>ppt_spatial_downscaling_daily_data_flatten_withFr_test_filt0_v3rev_64.py: Python code used to calculate downscaled precipitation data from aggregated grid precipitation data.</li> <li><a href="https://zenodo.org/api/files/12bc9f1c-be98-4721-8c92-6e23845be441/stns_precip_2015.csv">stns_precip_2015.csv</a>: Precipitation data at rain gauge stations in the Conterminous US extracted from the Daymet station-level input datasets are used for evaluation of the downscaled results </li> </ol> <p>Other datasets used to calculate wind speed and Brunt Vaisala parameter were extracted from the North American Regional Reanalysis (NARR) including wind speed, temperature, surface pressure, specific humidity and relative humidity [Mesinger et al. 2006].</p> <p> </p> <p><strong>References:</strong></p> <p>Daly, C., et al. (1994). "A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain." Journal of Applied Meteorology <strong>33</strong>(2): 140-158. </p> <p>Daly, C., et al. (2008). "Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States." International Journal of Climatology <strong>28</strong>(15): 2031-2064.</p> <p>Lehner, B., et al. (2008). "New Global Hydrography Derived From Spaceborne Elevation Data." Eos, Transactions American Geophysical Union <strong>89</strong>(10): 93-94.</p> <p>Lehner, B. and G. Grill (2013). "Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems." Hydrological Processes <strong>27</strong>(15): 2171-2186.</p> <p>Mesinger, F., et al. (2006). "NORTH AMERICAN REGIONAL REANALYSIS." Bulletin of the American Meteorological Society <strong>87</strong>(3): 343-360.</p>
3D Models from Morales, J. I., et al. (2015). "Measuring Retouch Intensity in Lithic Tools: A New Proposal Using 3D Scan Data." Journal of Archaeological Method and Theory 22(2): 543-558.
<p>This document compiles the complete set of 3D models and the measurements used for the experimental work of the paper:</p> <p>Morales, J. I., et al. (2015). "Measuring Retouch Intensity in Lithic Tools: A New Proposal Using 3D Scan Data." Journal of Archaeological Method and Theory 22(2): 543-558.<br> <br> It includes 3D scans from both unmodified and modified flakes (X & Xb). All the flakes produced in this experiment were produced by freehand hard hammer percussion and no specific flaking method was followed. Diferents types of tertiary evaporitic flint described in Soto, M., et al. (2017). "The chert abundance ratio (CAR): a new parameter for interpreting Palaeolithic raw material procurement." J. Archaeol Anthropol Sci. (https://doi.org/10.1007/s12520-017-0516-3) were used.</p> <p> </p>
Model parameters trained using the Component Contribution method
<p>A Numpy (.npz) file containing all model parameters needed for applying the component contribution method to estimate the standard Gibbs energies of biochemical reactions.</p> <p> </p> <p>This model is identical to the one stored on <a href="https://legacy.quiltdata.com/package/equilibrator/component_contribution/revisions">Quilt</a> with the following parameters:</p> <ul> <li>date: May 15, 2020, 8:04 PM</li> <li>hash: fd23b10c939089ffe0409eac32e36f36ab2fa3d3e486f008acde963ffd5a2ad8</li> <li>author: equilibrator</li> <li>tags: versions 0.3.0</li> </ul>
Model trees and associated simulated nucleotide sequences for testing phylogenetic inference methods
<p>This repository contains 142 tar.gz archive files, each containing nucleotide sequence data that have been simulated using <a href="http://abacus.gene.ucl.ac.uk/software/indelible/"><em>INDELible</em></a> for testing alignment-free phylogenetic inference methods. These datasets were generated by using the results (trees and model parameters) of 142 phylogenomic analyses of real-case data as model (available <a href="https://zenodo.org/record/4034261">here</a>). Initial sequence length was 5 Mbs, and an indel rate of 0.01 was set with indel length drawn from [1, 50000] according to a Zipf distribution with parameter 1.5 (see <em>INDELible</em> <a href="http://abacus.gene.ucl.ac.uk/software/indelible/manual/model.shtml">manual</a>).</p> <p>Each archive contains the following files/directories:</p> <ul> <li><code>GTR.params.trees.tsv </code> a tab-delimited file summarizing the real-case GTR+Γ model parameters and the phylogenetic tree used to simulate the sequence dataset (gathered from <a href="https://zenodo.org/record/4034261">https://zenodo.org/record/4034261</a>)</li> <li><code>tax.tsv </code> a tab-delimited file containing the initial (col 1) and simplified (col 2) taxon names</li> <li><code>model.nwk </code> a <a href="https://evolution.genetics.washington.edu/phylip/newicktree.html">Newick</a>-formatted file containing the initial model tree (gathered from <code>GTR.params.trees.tsv</code>) with simplified leaf names (following <code>tax.tsv</code>)</li> <li><code>control.txt </code> the <em>INDELible</em> input file used to simulate the evolution of a sequence along the tree in <code>model.nwk</code></li> <li><code>seq/ </code> a directory containing the simulated sequences (one FASTA file per leaf in the tree in <code>model.nwk</code>)</li> </ul> <p>___</p> <p>Criscuolo A (2020) <em>On the transformation of MinHash-based uncorrected distances into proper evolutionary distances for phylogenetic inference</em>. F1000Research, 9:1309. <a href="https://doi.org/10.12688/f1000research.26930.1">doi:10.12688/f1000research.26930.1</a></p>
Model parameters trained using the Component Contribution method (legacy version)
<p>A Numpy (.npz) file containing all model parameters needed for applying the component contribution method to estimate the standard Gibbs energies of biochemical reactions.</p> <p>This is a <strong>legacy version</strong>, and should only be used for consistency testing. Otherwise, please use the newer version (<a href="https://zenodo.org/record/4013789">10.5281/zenodo.4013789</a>).</p> <p>This model is identical to the one stored on <a href="https://legacy.quiltdata.com/package/equilibrator/component_contribution/revisions">Quilt</a> with the following parameters:</p> <ul> <li>date: April 9, 2020, 3:03 PM</li> <li>hash: 2c14d76366ba17dc876f2fc10612db41cae65c0411d8a654b762faa2beb3b055</li> <li>author: equilibrator</li> <li>tags: versions 0.2.18</li> </ul>
Raw in vitro screening data and R scripts for: A Bayesian method for population-wide cardiotoxicity hazard and risk characterization using an in vitro human model
<p>Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes are an established model for testing potential chemical hazards. Inter-individual variability in toxicodynamic sensitivity has also been demonstrated <i>in vitro</i>; however, quantitative characterization of the population-wide variability has not been fully explored. We sought to develop a method to address this gap by combining a population-based iPSC-derived cardiomyocyte model with Bayesian concentration-response modeling. A total of 136 compounds, including 44 pharmaceuticals and 82 environmental chemicals, were tested in iPSC-derived cardiomyocytes from 43 non-diseased humans. Hierarchical Bayesian population concentration-response modeling was conducted for five phenotypes reflecting cardiomyocyte function or viability. Toxicodynamic variability was quantified through the derivation of chemical- and phenotype-specific variability factors (TDVF). Toxicokinetic modeling was used for probabilistic <i>in vitro</i>-to-<i>in vivo </i>extrapolation in order to derive population-wide margins of safety (MOS) for pharmaceuticals and margins of exposure (MOE) for environmental chemicals. Pharmaceuticals were found to be active across all phenotypes. Over half of tested environmental chemicals showed activity in at least one phenotype, most commonly positive chronotropy. TDVF estimates for the functional phenotypes were greater than those for cell viability, usually exceeding the generally-assumed default of ~3. Population variability-based MOS for pharmaceuticals were correctly predicted to be relatively narrow, between 10-100; however, MOE for environmental chemicals, based on population exposure estimates, generally exceeded 1000, suggesting they pose little risk at general population exposures even to sensitive sub populations. This study represents a first of its kind human <i>in vitro</i> model that can be used to characterize toxicodynamic population variability in cardiotoxic risk.</p>
Using predictive models to evaluate the quality of a test suite at class and method level.
<p>Vídeo de apresentação para o Workshop de Teses e Dissertações do CBSoft (WTDSoft).</p>
Data from: Model sensitivity and use of the comparative finite element method in mammalian jaw mechanics: mandible performance in the Gray Wolf
Finite Element Analysis (FEA) is a powerful tool gaining use in studies of biological form and function. This method is particularly conducive to studies of extinct and fossilized organisms, as models can be assigned properties that approximate living tissues. In disciplines where model validation is difficult or impossible, the choice of model parameters and their effects on the results become increasingly important, especially in comparing outputs to infer function. To evaluate the extent to which performance measures are affected by initial model input, we tested the sensitivity of bite force, strain energy, and stress to changes in seven parameters that are required in testing craniodental function with FEA. Simulations were performed on FE models of a Gray Wolf (Canis lupus) mandible. Results showed that unilateral bite force outputs are least affected by the relative ratios of the balancing and working muscles, but only ratios above 0.5 provided balancing-working side joint reaction force relationships that are consistent with experimental data. The constraints modeled at the bite point had the greatest effect on bite force output, but the most appropriate constraint may depend on the study question. Strain energy is least affected by variation in bite point constraint, but larger variations in strain energy values are observed in models with different number of tetrahedral elements, masticatory muscle ratios and muscle subgroups present, and number of material properties. These findings indicate that performance measures are differentially affected by variation in initial model parameters. In the absence of validated input values, FE models can nevertheless provide robust comparisons if these parameters are standardized within a given study to minimize variation that arise during the model-building process. Sensitivity tests incorporated into the study design not only aid in the interpretation of simulation results, but can also provide additional insights on form and function.
Data from: Effect of detection heterogeneity in occupancy-detection models: an experimental test of time-to-first-detection methods
Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time-to-first-detection (TTD) occupancy models have been proposed as a cost-effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy-detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala (Phascolarctos cinereus) populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness-of-fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy-detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness-of-fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy-detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.
Data from: Vaccination method affects immune response and bacterial growth but not protection in the Salmonella Typhimurium animal model of typhoid
Understanding immune responses elicited by vaccines, together with immune responses required for protection, is fundamental to designing effective vaccines and immunisation programs. This study examines the effects of the route of administration of a live attenuated vaccine on its interactions with, and stimulation of, the murine immune system as well as its ability to increase survival and provide protection from colonisation by a virulent challenge strain. We assess the effect of administration method using the murine model for typhoid, where animals are infected with S. Typhimurium. Mice were vaccinated either intravenously or orally with the same live attenuated S. Typhimurium strain and data were collected on vaccine strain growth, shedding and stimulation of antibodies and cytokines. Following vaccination, mice were challenged with a virulent strain of S. Typhimurium and the protection conferred by the different vaccination routes was measured in terms of challenge suppression and animal survival. The main difference in immune stimulation found in this study was the development of a secretory IgA response in orally-vaccinated mice, which was absent in IV vaccinated mice. While both strains showed similar protection in terms of challenge suppression in systemic organs (spleen and liver) as well as survival, they differed in terms of challenge suppression of virulent pathogens in gut-associated organs. This difference in gut colonisation presents important questions around the ability of vaccines to prevent shedding and transmission. These findings demonstrate that while protection conferred by two vaccines can appear to be the same, the mechanisms controlling the protection can differ and have important implications for infection dynamics within a population.
Data from: A new method to scan genomes for introgression in a secondary contact model
Secondary contact between divergent populations or incipient species may result in the exchange and introgression of genomic material. We develop a simple DNA sequence measure, called Gmin, which is designed to identify genomic regions experiencing introgression in a secondary contact model. Gmin is defined as the ratio of the minimum between-population number of nucleotide differences in a genomic window to the average number of between-population differences. Although it is conceptually simple, one advantage of Gmin is that it is computationally inexpensive relative to model-based methods for detecting gene flow and it scales easily to the level of whole-genome analysis. We compare the sensitivity and specificity of Gmin to those of the widely used index of population differentiation, FST, and suggest a simple statistical test for identifying genomic outliers. Extensive computer simulations demonstrate that Gmin has both greater sensitivity and specificity for detecting recent introgression than does FST. Furthermore, we find that the sensitivity of Gmin is robust with respect to both the population mutation and recombination rates. Finally, a scan of Gmin across the X chromosome of Drosophila melanogaster identifies candidate regions of introgression between sub-Saharan African and cosmopolitan populations that were previously missed by other methods. These results show that Gmin is a biologically straightforward, yet powerful, alternative to FST, as well as to more computationally intensive model-based methods for detecting gene flow.
ScienceDex guides
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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.