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1,066 results for “bayesian”
Data for: Reintroduced Oriental stork bayesian hierarchical model data
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Spatial confounding in Bayesian species distribution modeling
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Prior choice and data requirements of Bayesian multivariate mixed effects models fit to tag-recovery data: The need for power analyses
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Resources for: Spatio-temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts
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Data and Scripts from: Bayesian prediction of multivariate ecology from phenotypic data yields novel insights into the diets of extant and extinct taxa
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Biomass production at 2085 horizon for the Maurienne valley (French Alps) estimated using a Bayesian Belief Network
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Inferring human immunodeficiency virus 1 proviral integration dates with Bayesian Inference
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Anatomical partitioning has little influence in topologies from Bayesian phylogenetic analyses of morphological data
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Revisiting the historical scenario of a disease dissemination using genetic data and Approximate Bayesian Computation methodology: the case of Pseudocercospora fijiensis invasion in Africa
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Code and data for Bayesian joint species distribution model selection for community-level prediction
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Data and scripts for: Bayesian Phylogenetic Analysis on multi-core Compute Architectures: Implementation and evaluation of BEAGLE in RevBayes with MPI
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Impacts of taxon-sampling schemes on Bayesian tip dating under the fossilized birth-death process
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Data of Bayesian inference of non-linear multiscale model parameters accelerated by a Deep Neural Network
<pre>Data from title = "Bayesian inference of non-linear multiscale model parameters accelerated by a Deep Neural Network", journal = "Computer Methods in Applied Mechanics and Engineering", pages = "112693", year = "2020", issn = "0045-7825", doi = "https://doi.org/10.1016/j.cma.2019.112693", author = "Wu, Ling and Zulueta, Kepa and Major, Zoltan and Arriaga, Aitor and Noels, Ludovic" </pre>
A Bayesian Phylogenetic Hidden Markov Model for B Cell Receptor Sequence Analysis
<p>simulation and PC64/VRC01 input/output data files</p>
The reasonable application of Bayesian multi-model averaging to produce gross primary production with high quality in China
<p>To reduce the uncertainties of output data from the Multi-scale Terrestrial Model Intercomparison Project (MsTMIP), Bayesian Model Averaging (BMA) was trained by observed GPP from ChinaFLUX and a set of monthly 0.5° by 0.5° GPP data from 1948 to 2010 for China was produced.</p>
CO2 Reduction Tafel Dataset for Bayesian Data Analysis
<p>This dataset contains 344 different digitized and tagged Tafel slope datasets from the CO2 reduction literature. We re-analyze this data with a Bayesian data analysis procedure that estimates a Tafel slope and yields distributional uncertainty information about its value. We are releasing this dataset along with our study to facilitate re-analyzing and refitting our data using different models and approaches.</p>
Molecular dating for phylogenies containing a mix of populations and species by using Bayesian and RelTime approaches
<p><span><span><span><span><span><span><span><span><span><span><span>Simultaneous molecular dating of population and species divergences is essential in many biological investigations, including phylogeography, phylodynamics, and species delimitation studies. In these investigations, multiple sequence alignments consist of both intra- and inter-species samples (mixed samples). As a result, the phylogenetic trees contain inter-species, inter-population, and within-population divergences. Bayesian relaxed clock methods are often employed in these analyses, but they assume the same tree prior for both inter- and intra-species branching processes and require specification of a clock model for branch rates (independent vs. autocorrelated rates models). We evaluated the impact of a single tree prior onBayesian divergence time estimates by analyzing computer-simulated datasets. We also examined the effectof the assumption of independence of evolutionary rate variation among branches when the branch rates are autocorrelated. Bayesian approach with coalescent tree priors generally produced excellent molecular dates and highest posterior densities with high coverage probabilities. We also evaluated the performance of a non-Bayesian method, RelTime, which does not require the specification of a tree prior or a clock model. RelTime's performance was similar to that of the Bayesian approach, suggesting that it is also suitable to analyze datasets containing both populations and species variation when its computational-efficiency is needed.</span></span></span></span></span></span></span></span></span></span></span></p>
Molecular dynamics simulations data for "Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes".
<p>Molecular dynamics simulation data created and used in "Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes".</p> <p> </p>
Bayesian diagnostic meta-analysis dataset of pelvic examination in pelvic inflammatory disease
<p><span><span><span><span><span><span><span><span><span><span><span>Pelvic inflammatory disease (PID) is not merely a transient sexually transmitted disease. It can lead to chronic pain, ectopic pregnancy, and infertility. Although the Centers for Disease Control and Prevention have established minimum diagnostic criteria, including pelvic examination, the diagnostic value of pelvic tenderness has recently garnered controversy. Our meta-analysis aimed to confirm whether pelvic examination can help diagnose PID among at-risk women.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Design</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>A Bayesian meta-analysis of studies reporting diagnostic data of patients at risk for PID.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Setting</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>We searched MEDLINE, EMBASE, CENTRAL, CINAHL, Google, and Google Scholar for eligible articles. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Participants</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Female patients at risk for PID.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Main results</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>The literature search produced 5,395 articles. After quality assessment, 16 studies and their 4,083 participants were eligible for synthesis on pelvic tenderness.</span></span></span></span></span></span></span></span></span></span></span></p>
Data for "Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics"
<p>Experimental and precomputed data for the paper "Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics" by Oesterle et al. 2020 (DOI: <a href="https://doi.org/10.7554/eLife.54997">10.7554/eLife.54997</a>).</p> <p>The cone bipolar cell data has been described and published in the paper "Inhibition decorrelates visual feature representations in the inner retina" by Franke et al. 2017 (DOI: <a href="https://doi.org/10.1038/nature21394">10.1038/nature21394</a>). </p> <p>This data is both a supplement to the Oesterle et al. paper and the code for this paper.</p> <p>The code is available in this <a href="http://github.com/berenslab/CBC_inference">GitHub repository</a>.</p> <p>We recommend downloading the GitHub repository and to follow the instructions there.</p>
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.