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295 results for “Approximation”
Data from: Assessing the dynamics of natural populations by fitting individual based models with approximate Bayesian computation
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Data from: Using a continuum model to decipher the mechanics of embryonic tissue spreading from time-lapse image sequences: an approximate Bayesian computation approach
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Data from: Population genetic structure and approximate Bayesian computation analyses reveal the southern origin and northward dispersal of the oriental fruit moth Grapholita molesta (Lepidoptera: Tortricidae) in its native range
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Estimating on the fly: the approximate number system in rufous hummingbirds (Selasphorus rufus)
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VCF files of loci in approximate linkage equilibrium for two common spruce budworm larval parasitoids: Apanteles fumiferanae (Hymenoptera: Braconidae) and Glypta fumiferanae (Hymenoptera: Ichneumonidae)
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Data from: Elucidating the spatio-temporal dynamics of an emerging wildlife pathogen using approximate Bayesian computation
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Inferring macroevolutionary parameters from on a model of adaptive radiation by Approximate Bayesian Computation - ABC Simulations
<p>Recent advances in DNA sequencing are providing increasingly accurate phylogenetic trees to study, but understanding the evolutionary forces at play in different contexts remains a huge challenge. To tackle this issue, we applied an Bayesian approach to an existing model of phenotypic and species diversification [1] in order to retrieve 11 underlying parameters (such as basal speciation and extinction rates, but also competition strength) from phylogenetic trees with known traits values at the tips.</p> <p>This dataset corresponds to the Approximate Bayesian Computation simulations realized for the inference.</p>
Dataset for Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice
<p>The dataset consists of</p> <p>(1) Benchmark files<br> (2) the logfile (outputs) generated by ApproxMC4 and ApproxMC5 respectively</p> <p>(3) A summary of the results for the files where at least one of ApproxMC4 or ApproxMC5 did not time out and took more than 1 second. </p> <p>The corresponding paper titled "Scalable Approximate Model Counting via Concentrated Hashing]{Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice" will appear in the Proceedings of Logic in Computer science(LICS), 2020.</p>
All figures and tables for "Optimized approximate inverse Laplace transform for geo-deformation computation in viscoelastic earth model"
<p>It is the data set of all figures and tables in the paper with title "Optimized approximate inverse Laplace transform for geo-deformation computation in viscoelastic earth model".</p>
Supplementary material for "Numerical approximation of port-Hamiltonian systems for hyperbolic or parabolic PDEs with boundary control"
<p>This archive contains supplementary Python codes and Jupyter notebooks for the manuscript "Numerical approximation of port-Hamiltonian systems for hyperbolic or parabolic PDEs with boundary control" by A. Brugnoli, G. Haine, A. Serhani and X. Vasseur (ISAE-SUPAERO, University of Toulouse, France). This manuscript is available on ArXiv:</p> <p>https://arxiv.org/abs/2007.08326</p> <p>Provided notebooks:<br> -------------------</p> <p>1) Wave equation: tutorial_wave_ode.ipynb [Section 5.1 of the manuscript]<br> 2) Wave equation with mixed boundary conditions: tutorial_wave_dae.ipynb<br> 3) Mindlin plate problem: tutorial_mindlin.ipynb [Section 5.2 of the manuscript]<br> 4) Heat equation: tutorial_heat_dae.ipynb [Section 5.3 of the manuscript]</p> <p>The codes and notebooks rely on a working installation of the FEniCS software and the assimulo package, all available in the public domain:<br> - FEniCS: www.fenicsproject.org, version 2019.1.0<br> - assimulo: https://jmodelica.org/assimulo/ version 3.1</p> <p>A README file is provided for the installation of the dependencies.</p> <p>This research is supported by the project ANR-16-CE92-0028, entitled "Interconnected Infinite-Dimensional systems for Heterogeneous Media", INFIDHEM, financed by the French National Research Agency (ANR) and the Deutsche Forschungsgemeinschaft (DFG).</p>
Data from: Approximate Bayesian computation reveals the crucial role of oceanic islands for the assembly of continental biodiversity
The perceived low levels of genetic diversity, poor interspecific competitive and defensive ability, and loss of dispersal capacities of insular lineages have driven the view that oceanic islands are evolutionary dead ends. Focusing on the Atlantic bryophyte flora distributed across the archipelagos of the Azores, Madeira, the Canary Islands, Western Europe, and northwestern Africa, we used an integrative approach with species distribution modeling and population genetic analyses based on approximate Bayesian computation to determine whether this view applies to organisms with inherent high dispersal capacities. Genetic diversity was found to be higher in island than in continental populations, contributing to mounting evidence that, contrary to theoretical expectations, island populations are not necessarily genetically depauperate. Patterns of genetic variation among island and continental populations consistently fitted those simulated under a scenario of de novo foundation of continental populations from insular ancestors better than those expected if islands would represent a sink or a refugium of continental biodiversity. We, suggest that the northeastern Atlantic archipelagos have played a key role as a stepping stone for transoceanic migrants. Our results challenge the traditional notion that oceanic islands are the end of the colonization road and illustrate the significant role of oceanic islands as reservoirs of novel biodiversity for the assembly of continental floras.
Data from: The demographic history of Atlantic salmon (Salmo salar) across its distribution range reconstructed from approximate Bayesian computations
Understanding the dual roles of demographic and selective processes in the buildup of population divergence is one of the most challenging tasks in evolutionary biology. Here, we investigated the demographic history of Atlantic Salmon across the entire species range using 2035 anadromous individuals from North America and Eurasia. By combining results from admixture graphs, geo-genetic maps and an Approximate Bayesian Computation (ABC) framework, we validated previous hypotheses pertaining to secondary contact between European and Northern American populations, but also identified secondary contacts in European populations from different glacial refugia. We further identified the major sources of admixture from the southern range of North America into more northern populations along with a strong signal of secondary gene flow between genetic regional groups. We hypothesize that these patterns reflects the spatial redistribution of ancestral variation across the entire North American range. Results also support a role for linked selection and differential introgression that likely played an under-appreciated role in shaping the genomic landscape of species in the Northern hemisphere. We conclude that studies between partially isolated populations should systematically include heterogeneity in selective and introgressive effects among loci to perform more rigorous demographic inferences of the divergence process.
Data from: Robustness of the approximate likelihood of the protracted speciation model
The protracted speciation model presents a realistic and parsimonious explanation for the observed slowdown in lineage accumulation through time, by accounting for the fact that speciation takes time. A method to compute the likelihood for this model given a phylogeny is available and allows estimation of its parameters (rate of initiation of speciation, rate of completion of speciation, and extinction rate) and statistical comparison of this model to other proposed models of diversification. However this likelihood computation method makes an approximation of the protracted speciation model to be mathematically tractable: it sometimes counts fewer species than one would do from a biological perspective. This approximation may have large consequences for likelihood-based inferences: it may render any conclusions based on this method completely irrelevant. Here we study to what extent this approximation affects parameter estimations. We simulated phylogenies from which we reconstructed the tree of extant species according to the original, biologically meaningful protracted speciation model and according to the approximation. We then compared the resulting parameter estimates. We found that the differences were larger for high values of extinction rates and small values of speciation-completion rates. Indeed, a long speciation-completion time and a high extinction rate promote the appearance of cases to which the approximation applies. However, surprisingly, the deviation introduced is largely negligible over the parameter space explored, suggesting that this approximate likelihood can be applied reliably in practice to estimate biologically relevant parameters under the original protracted speciation model.
Data from: Dynamics of pre-choice and post-choice behaviour: rats approximate optimal strategy in a discrete-trial decision task
We simulate two types of environments to investigate how closely rats approximate optimal foraging. Rats initiated a trial where they chose between two spouts for sucrose, which was delivered at distinct probabilities. The discrete trial procedure used allowed us to observe the relationship between choice proportions, response latencies and obtained rewards. Our results show that rats approximate the optimal strategy across a range of environments that differ in the average probability of reward as well as the dynamics of the depletion-renewal cycle. We found that the constituent components of a single choice differentially reflect environmental contingencies. Post-choice behaviour, measured as the duration of time rats spent licking at the spouts on unrewarded trials, was the most sensitive index of environmental variables, adjusting most rapidly to changes in the environment. These findings have implications for the role of confidence in choice outcomes for guiding future choices.
Data from: PHRAPL: phylogeographic inference using approximate likelihoods
The demographic history of most species is complex, with multiple evolutionary processes combining to shape the observed patterns of genetic diversity. To infer this history, the discipline of phylogeography has (to date) used models that simplify the historical demography of the focal organism, for example by assuming or ignoring ongoing gene flow between populations or by requiring a priori specification of divergence history. Since no single model incorporates every possible evolutionary process, researchers rely on intuition to choose the models that they use to analyze their data. Here, we describe an approximate likelihood approach that reduces this reliance on intuition. PHRAPL allows users to calculate the probability of a large number of complex demographic histories given a set of gene trees, enabling them to identify the most likely underlying model and estimate parameters for a given system. Available model parameters include coalescence time among populations or species, gene flow, and population size. We describe the method and test its performance in model selection and parameter estimation using simulated data. We also compare model probabilities estimated using our approximate likelihood method to those obtained using standard analytical likelihood. The method performs well under a wide range of scenarios, although this is sometimes contingent on sampling many loci. In most scenarios, as long as there are enough loci and if divergence among populations is sufficiently deep, PHRAPL can return the true model in nearly all simulated replicates. Parameter estimates from the method are also generally accurate in most cases. PHRAPL is a valuable new method for phylogeographic model selection and will be particularly useful as a tool to more extensively explore demographic model space than is typically done or to estimate parameters for complex models that are not readily implemented using current methods. Estimating relevant parameters using the most appropriate demographic model can help to sharpen our understanding of the evolutionary processes giving rise to phylogeographic patterns.
FIGURE 6. Male genitalia with crista succuli approximately 1 in Recognition of a new species of Carmenta from New Mexico supported by morphology and mitochondrial cytochrome oxidase I data (Lepidoptera: Sesiidae: Sesiinae: Synanthedonini)
FIGURE 6. Male genitalia with crista succuli approximately 1/2 the length of the right valve.
Figure 1. – FAO Statistical Area 21, ranging approximately from 35 in The fisheries of the sea around Saint-Pierre and Miquelon: from cod to sea cucumber
Figure 1. – FAO Statistical Area 21, ranging approximately from 35 to 77.5 0N, and from 42 to 77.5 0E (6,293,000 km2), and encompassing the Newfoundland-Labrador Shelf Large Marine Ecosystem (LME; dark grey; 664,700 km2) and the Southern Grand Banks- South Newfoundland Marine Ecoregion (light grey; 55,400 km2), slightly modified to fit inside the LME. The insert in the lower right corner shows the Exclusive Economic Zone of St Pierre and Miquelon (12,400 km2).
Figure 1 in A first approximation for the Herpetofauna species composition of the Taiamã Ecological Station, Pantanal of Mato Grosso, Brazil
Figure 1. (A) Distribution map of Paleosuchus palpebrosus (orange color) (based on Magnusson et al., 2019); (B) New distribution record (star) for the Pantanal floodplain at the Taiamã Ecological Station, Mato Grosso, Brazil; (C) Registered specimen of Paleosuchus palpebrosus (Photograph by Daniel L. Z. Kantek).
Data from: Self-recruitment in a Caribbean reef fish: a method for approximating dispersal kernels accounting for seascape
Characterizing patterns of larval dispersal is essential to understanding the ecological and evolutionary dynamics of marine metapopulations. Recent research has measured local dispersal within populations, but the development of marine dispersal kernels from empirical data remains a challenge. We propose a framework to move beyond point estimates of dispersal towards the approximation of a simple dispersal kernel, based on the hypothesis that the structure of the seascape is a primary predictor of realized dispersal patterns. Using the coral reef fish Elacatinus lori as a study organism, we use genetic parentage analysis to estimate self-recruitment at a small spatial scale (<1 km). Next, we determine which simple kernel explains the observed self-recruitment, given the influx of larvae from reef habitat patches in the seascape at a large spatial scale (up to 35 km). Finally, we complete parentage analyses at six additional sites to test for export from the focal site and compare these observed dispersal data within the metapopulation to the predicted dispersal kernel. We find 4.6% self-recruitment (CI95%: ±3.0%) in the focal population, which is explained by the exponential kernel y = 0.915x (CI95%: y = 0.865x, y = 0.965x), given the seascape. Additional parentage analyses showed low levels of export to nearby sites, and the best-fit line through the observed dispersal proportions also revealed a declining function y = 0.77x. This study lends direct support to the hypothesis that the probability of larval dispersal declines rapidly with distance in Atlantic gobies in continuously distributed habitat, just as it does in the Indo-Pacific damselfishes in patchily distributed habitat.
Data from: Inferring the origin of populations introduced from a genetically structured native range by approximate Bayesian computation: case study of the invasive ladybird Harmonia axyridis
Correct identification of the source population of an invasive species is a prerequisite for testing hypotheses concerning the factors responsible for biological invasions. The native area of invasive species may be large, poorly known and/or genetically structured. Because the actual source population may not have been sampled, studies based on molecular markers may generate incorrect conclusions about the origin of introduced populations. In this study, we characterized the genetic structure of the invasive ladybird Harmonia axyridis in its native area using various population genetic statistics and methods. We found that H. axyridis native area most likely consisted of two geographically distinct genetic clusters located in eastern and western Asia. We then performed approximate Bayesian computation (ABC) analyses on controlled simulated microsatellite data sets to evaluate: (i) the risk of selecting incorrect introduction scenarios, including admixture between sources, when the populations of the native area are genetically structured and sampling is incomplete, (ii) the ability of ABC analysis to minimize such risks by explicitly including unsampled populations in the scenarios compared. Finally, we performed additional ABC analyses on real microsatellite data sets to retrace the origin of biocontrol and invasive populations of H. axyridis, taking into account the possibility that the structured native area may have been incompletely sampled. We found that the invasive population in eastern North America, which has served as the bridgehead for worldwide invasion by H. axyridis, was probably formed by an admixture between the eastern and western native clusters. This admixture may have facilitated adaptation of the bridgehead population.
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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.