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89 results for “Bayesian estimation”
Bayesian estimation of the specific shear and bulk viscosity of the quark-gluon plasma
<p>This repository contains all data necessary to reproduce Bayesian parameter estimates of a computational model of relativistic heavy-ion collisions.</p> <p>The computational collision model which generated the raw data is available at <a href="https://github.com/Duke-QCD/hic-eventgen">https://github.com/Duke-QCD/hic-eventgen</a>. The analysis code which postprocessed the raw data and performed the parameter estimation is available at <a href="https://github.com/jbernhard/hic-param-est">https://github.com/jbernhard/hic-param-est</a>.</p> <p>For more information, see the author's dissertation, <a href="https://arxiv.org/abs/1804.06469">Bayesian parameter estimation for relativistic heavy-ion collisions (arXiv:1804.06469 [nucl-th])</a>. In particular, chapter 3 describes the computational collision model, chapter 4 describes the parameter estimation method, and section 5.3 presents the results based on this dataset.</p> <p><strong>Usage</strong></p> <p>hic-param-est-cache.tar.gz is designed to be used with the analysis code (<a href="https://github.com/jbernhard/hic-param-est">https://github.com/jbernhard/hic-param-est</a>).<br> See the documentation at <a href="http://qcd.phy.duke.edu/hic-param-est">http://qcd.phy.duke.edu/hic-param-est</a>. After downloading the code, extract the data archive in the hic-param-est folder. This will create the cache directory containing the parameter design files, model calculations, and experimental data. Note that this data archive includes Python pickle files created by <a href="https://joblib.readthedocs.io/en/latest/persistence.html">joblib</a>, which is included with <a href="https://scikit-learn.org">scikit-learn</a>, a dependency of the analysis code.</p> <p>alternate-format.hdf contains the same data in HDF5 format. This is not intended for use directly with the analysis code, but may be more convenient for other purposes.</p> <p>chain.hdf contains the posterior distribution sample (the "chain") generated by MCMC sampling in HDF5 format. It may be used with the analysis code by placing it in a subfolder "mcmc" in the hic-param-est folder. It can also be regenerated by the analysis code, although this can take a long time.</p>
Data and code for simulation study and case study in "A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity"
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Data from: Bayesian methods outperform parsimony but at the expense of precision in the estimation of phylogeny from discrete morphological data
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Data from: Elevated substitution rate estimates from ancient DNA: model violation and bias of Bayesian methods
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Data from: Estimating Bayesian phylogenetic information content
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Data from: Deflating trees: improving Bayesian branch-length estimates using informed priors
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Data from: Evaluating the impact of genomic data and priors on Bayesian estimates of the angiosperm evolutionary timescale
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Data from: Wheat alleles introgress into selfing wild relatives: empirical estimates from Approximate Bayesian Computation in Aegilops triuncialis.
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Data from: Bayesian estimation of speciation and extinction from incomplete fossil occurrence data
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Data from: An evaluation of different partitioning strategies for Bayesian estimation of species divergence times
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Data from: A hierarchical Bayesian model for calibrating estimates of species divergence times
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Data from: Bayesian methods for estimating GEBVs of threshold traits
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Data from: Bayesian estimation of species divergence times using correlated quantitative characters
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Data from: Conventional analysis of trial-by-trial adaptation is biased: empirical and theoretical support using a Bayesian estimator
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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
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Improved RNA stability estimation through Bayesian modeling reveals most bacterial transcripts have sub-minute half-lives [RIF-seq]
GEO Series GSE234009. Salmonella enterica subsp. enterica serovar Typhimurium. 120 samples. Type: Expression profiling by high throughput sequencing.
Improved RNA stability estimation through Bayesian modeling reveals most bacterial transcripts have sub-minute half-lives [CLIP-seq]
GEO Series GSE234007. Salmonella enterica subsp. enterica serovar Typhimurium. 12 samples. Type: Other.
Data from: Bayesian estimation of fossil phylogenies and the evolution of early to middle Paleozoic crinoids (Echinodermata)
Knowledge of phylogenetic relationships among species is fundamental to understanding basic patterns in evolution and underpins nearly all research programs in biology and paleontology. However, most methods of phylogenetic inference typically used by paleontologists do not accommodate the idiosyncrasies of fossil data and therefore do not take full advantage of the information provided by the fossil record. The advent of Bayesian 'tip-dating' approaches to phylogeny estimation is especially promising for paleosystematists because time-stamped comparative data can be combined with probabilistic models tailored to accommodate the study of fossil taxa. Under a Bayesian framework, the recently developed fossilized birth–death (FBD) process provides a more realistic tree prior model for paleontological data that accounts for macroevolutionary dynamics, preservation, and sampling when inferring phylogenetic trees containing fossils. In addition, the FBD tree prior allows for the possibility of sampling ancestral morphotaxa. Although paleontologists are increasingly embracing probabilistic phylogenetic methods, these recent developments have not previously been applied to the deep-time invertebrate fossil record. Here, I examine phylogenetic relationships among Ordovician through Devonian crinoids using a Bayesian tip-dating approach. Results support several clades recognized in previous analyses sampling only Ordovician taxa, but also reveal instances where phylogenetic affinities are more complex and extensive revisions are necessary, particularly among the Cladida. The name Porocrinoidea is proposed for a well-supported clade of Ordovician 'cyathocrine' cladids and hybocrinids. The Eucladida is proposed as a clade name for the sister group of the Flexibilia herein comprised of cladids variously considered 'cyathocrines,' 'dendrocrines,' and/or 'poteriocrines' by other authors.
Data from: Bayesian estimation of genomic clines
We developed a Bayesian genomic cline model to study the genetic architecture of adaptive divergence and reproductive isolation between hybridizing lineages. This model quantifies locus-specific patterns of introgression with two cline parameters that describe the probability of locus-specific ancestry as a function of genome-wide admixture. "Outlier" loci with extreme patterns of introgression relative to most of the genome can be identified. These loci are potentially associated with adaptive divergence or reproductive isolation. We simulated genetic data for admixed populations that included neutral introgression, as well as loci that were subject to directional, epistatic or underdominant selection, and analyzed these data using the Bayesian genomic cline model. Under many demographic conditions, underdominance or directional selection had detectable and predictable effects on cline parameters and "outlier" loci were greatly enriched for genetic regions affected by selection. We also analyzed previously published genetic data from two transects through a hybrid zone between Mus domesticus and M. musculus. We found considerable variation in rates of introgression across the genome and particularly low rates of introgression for two X-linked markers. There were similarities and differences in patterns of introgression between the two transects, which likely reflects a combination of stochastic variability due to genetic drift and geographic variation in the genetic architecture of reproductive isolation. By providing a robust framework to quantify and compare patterns of introgression among genetic regions and populations, the Bayesian genomic cline model will advance our understanding of the genetics of reproductive isolation and the speciation process.
Data from: Improved estimation of macroevolutionary rates from fossil data using a Bayesian framework
The estimation of origination and extinction rates and their temporal variation is central to understanding diversity patterns and the evolutionary history of clades. The fossil record provides the only direct evidence of extinction and biodiversity changes through time and has long been used to infer the dynamics of diversity changes in deep time. The software PyRate implements a Bayesian framework to analyze fossil occurrence data to estimate the rates of preservation, origination and extinction while incorporating several sources of uncertainty. Building upon this framework, we present a suite of methodological advances including more complex and realistic models of preservation and the first likelihood-based test to compare the fit across different models. Further, we develop a new reversible jump Markov chain Monte Carlo algorithm to estimate origination and extinction rates and their temporal variation, which provides more reliable results and includes an explicit estimation of the number and temporal placement of statistically significant rate changes. Finally, we implement a new C++ library which speeds up the analyses by orders of magnitude, therefore facilitating the application of PyRate to large datasets. We demonstrate the new functionalities through extensive simulations and with the analysis of a large dataset of Cenozoic marine mammals. We compare our analytical framework against two alternative methods to infer origination and extinction rates revealing that PyRate decisively outperforms them across a range of simulated datasets. Our analyses indicate that explicit statistical model testing, which is often neglected in fossil-based macroevolutionary analyses, is crucial to obtain accurate and robust results.
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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)
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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.