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1,049 results for “robustness”
Plasma metabolite indices are robust to extrinsic variation and useful indicators of foraging habitat quality in Lesser Scaup (Aythya affinis)
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Tibial apophysis of palp, viewed laterally, large and robust, the tip reflexed dorsally through 90o (L1) in An of Zelotibia (Araneae, Gnaphosidae), a spider genus with a species swarm in the Albertine Rift
Tibial apophysis of palp, viewed laterally, large and robust, the tip reflexed dorsally through 90o (L1)
Investigating Distributional Robustness: Semantic Perturbations Using Generative Models (ImageNet Examples)
<p>This dataset contains examples of semantically-perturbed images, for NeurIPS 2020 submission #4915.</p> <p>There are four top-level folders, each containing results for semantic perturbations restricted to adjust the activation values at only certain layers of the BigGAN generative network: the first six layers, the middle six layers, the last six layers, and all layers.</p> <p>Within each top-level folder, there are a further four folders, each corresponding to a classifier neural network whose evaluation is being evaluated. These are EfficientNet-B4 with NoisyStudent training [1], the standard ResNet50 [2], a pixel-perturbation-robust ResNet50 trained by Engstrom et al. [3] and another trained by Wong et al. [4], using their "Fast is better than free" technique.</p> <p>Within each of these, there are many folders, named 'version_$N'. Each one of these contains three images: the unperturbed generated image, named unpert_generated_x_grid_0.png; the semantically-perturbed generated image, named generated_x_grid_0.png; and an image named semantic_pert_diffs_grid_0.png showing the pixel-space effect of the semantic perturbation, that is, the diff between the perturbed and unperturbed images. Note that if the perturbed and unperturbed images are identical, and the classifier misclassifies the unperturbed images, and so we skip this example.</p> <p>Along with the 'version_$N' folders containing the images, there exists a file for each classifier named results.json. Each top-level item in this JSON file corresponds to one 'version_$N' example. There are 5 attributes: 'label', indicating the target label of the unperturbed image; 'magnitude', which gives the magnitude of the semantic perturbation found; 'skipped_cla', which is 1 if the example is skipped because the classifier did not correctly classify the unperturbed image; 'skipped_judge', which is 1 if the human judged that the unperturbed image did not match its label, so this example is skipped; and 'pert_judgement', which is 1 if the semantically-perturbed image is judged by the human to be of the same class as the unperturbed image. These judgements on these images were used to construct the main graphs in the paper.</p> <p> </p> <p>[1] Qizhe Xie, Eduard H. Hovy, Minh-Thang Luong, and Quoc V. Le. Self-training with Noisy Student improves ImageNet classification. CoRR, abs/1911.04252, 2019. URL http://arxiv.org/abs/1911.04252.</p> <p>[2] Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, June 27-30, 2016, pages 770–778. IEEE Computer Society, 2016. doi: 10.1109/CVPR.2016.90. URL https://doi.org/10.1109/CVPR.2016.90.</p> <p>[3] Logan Engstrom, Andrew Ilyas, Shibani Santurkar, and Dimitris Tsipras. Robustness (Python library), 2019. URL ttps://github.com/MadryLab/robustness.</p> <p>[4] Eric Wong, Leslie Rice, and J. Zico Kolter. Fast is better than free: Revisiting adversarial training. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net, 2020. URL<br> https://openreview.net/forum?id=BJx040EFvH.</p>
Problem instances for robust spotter scheduling problem
<p>We randomly generated problem instances for the robust spotter scheduling problem (RSSP) which are proposed in the article "Tadumadze, G., Boysen, and N., Emde, S. (2020): Robust spotter scheduling in trailer yards. <em>OR Spectrum</em>, <a href="https://doi.org/10.1007/s00291-020-00599-5">https://doi.org/10.1007/s00291-020-00599-5</a>". For a detailed instance generation scheme see Section 4.1 of the aforementioned work.</p> <p>We generate RSSP instances for the following three different sized trailer terminals which differ in the number of dock doors <span class="math-tex">\(|D|\)</span> of the terminal and the parking positions<span class="math-tex">\(|\Pi|\)</span> in the parking lot:</p> <ul> <li>S: <span class="math-tex">\(|D| = 20\)</span>; <span class="math-tex">\(|\Pi| \in \{40,60,80,100\}\)</span></li> <li>M: <span class="math-tex">\(|D| = 50\)</span>; <span class="math-tex">\(|\Pi| \in \{100,150,200,250\}\)</span></li> <li>L: <span class="math-tex">\(|D| = 200\)</span>; <span class="math-tex">\(|\Pi| \in \{400,600,800,1000\}\)</span></li> </ul> <p>The dataset contains 450 RSSP instances each of which is described in a text-file (labeled as “<ID>.txt” where ID is a running index of instance (from 0001 to 0450)). In particular, each file contains information about the number of transport requests (i.e., jobs) <span class="math-tex">\(n\)</span>, the spotter fleet size <span class="math-tex">\(m\)</span> , the processing time of transport request <span class="math-tex">\(j\)</span> (<span class="math-tex">\(j=1,…,n\)</span>) <span class="math-tex">\(p_j\)</span> , the completion time of transport request <span class="math-tex">\(j\)</span> (<span class="math-tex">\(j=1,…,n\)</span>) <span class="math-tex">\(C_j\)</span> and the deadheading time it takes a spotter to move from the target position of job <span class="math-tex">\(j\)</span> to the start position of job <span class="math-tex">\(j'\)</span> (<span class="math-tex">\(j,j'=1,…,n\)</span>) <span class="math-tex">\(\delta_{jj'}\)</span> (i.e., sequence-dependent setup times). Further, each file consists of additional information that describes the direction of each transport request (i.e., whether it describes a transport request of a semitrailer from the parking lot to terminal or vice versa) and the index of the corresponding truck (i.e., semitrailer).</p> <p>Each text-file is structured as follows:</p> <p>count_jobs =</p> <p><integer number that describes the number of transport requests (i.e., <span class="math-tex">\(n\)</span>)>.</p> <p>Count_spotters =</p> <p><integer number that describes the number of spotters (i.e., <span class="math-tex">\(m\)</span>)>.</p> <p>processing_times =</p> <p><vector with <span class="math-tex">\(n\)</span> integer numbers: the <span class="math-tex">\(j\)</span>-th element of the vector describes the processing time of for transport request <span class="math-tex">\(j\)</span> (i.e., <span class="math-tex">\(p_j\)</span>)>.</p> <p>completion_times =</p> <p><vector with <span class="math-tex">\(n\)</span> integer numbers: the <span class="math-tex">\(j\)</span>-th element of the vector describes the completion time of <span class="math-tex">\(j\)</span>-th transport request (i.e., <span class="math-tex">\(C_j\)</span>)>.</p> <p>weights =</p> <p><vector with <span class="math-tex">\(n\)</span> integer numbers: the <span class="math-tex">\(j\)</span>-th element of the vector describes the relative importance of transport request <span class="math-tex">\(j\)</span> (i.e., <span class="math-tex">\(w_j\)</span>)>.</p> <p>driving_times =</p> <p><matrix with <span class="math-tex">\(n*n\)</span> integers: each entry in <span class="math-tex">\(j\)</span>-th column and <span class="math-tex">\(j'\)</span>-th row describes the sequence-dependent setup times between jobs <span class="math-tex">\(j\)</span> and <span class="math-tex">\(j'\)</span> (<span class="math-tex">\(\delta_{jj'}\)</span>)>.</p> <p> </p> <p>*********************job_truck_relation*********************</p> <p> </p> <p>to_terminal =</p> <p><vector with n boolean values: the <span class="math-tex">\(j\)</span>-th element of vector has a value “<span class="math-tex">\(True\)</span>”, if the <span class="math-tex">\(j\)</span>-th job stands for transport request of a semitrailer from the parking lot to the terminal; “<span class="math-tex">\(False\)</span>” -- otherwise>.</p> <p>trucks_index =</p> <p><vector with n integer numbers: the <span class="math-tex">\(j\)</span>-th element of vector describes the index of the semitrailer of transport request <span class="math-tex">\(j\)</span>>.</p> <p>The first 360 RSSP instances (i.e., 0001-0360) are generated for the computational performance test (Section 4.2) and the next 90 instances (i.e., 0361-0450) -- for the simulation study (Section 4.4).</p>
From leaf to label: A robust automated workflow for stomata detection: Light microscope images of stomata.
<p>All light microscope images used for training and testing of the deep learning model developed in the study: Meeus S., Van den Bulcke J., wyffels F. (2020) From leaf to label: A robust automated workflow for stomata detection. Ecol. Evol. <a href="https://doi.org/10.1002/ece3.6571">https://doi.org/10.1002/ece3.6571</a>.</p>
Data from: Robust DNA isolation and high-throughput sequencing library construction for herbarium specimens
Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 hours, with only 8 hours of active hands-on time with minimal modifications.
Data from: Insulin signaling's role in mediating tissue-specific nutritional plasticity and robustness in the horn-polyphenic beetle Onthophagus taurus
Organisms cope with nutritional variation via developmental plasticity, adjusting trait size to nutrient availability for some traits while enabling others to develop in a nutritionally robust manner. Yet, the developmental mechanisms that regulate organ-specific growth across nutritional gradients remain poorly understood. We assessed the functions of members of the insulin/insulin-like signaling pathway (IIS) in the regulation of nutrition sensitivity and robustness in males of the horn-polyphenic beetle Onthophagus taurus, as well as potential regulatory interactions between IIS and two other growth-regulating pathways: Doublesex and Hedgehog signaling. Using RNA interference (RNAi) we experimentally knocked down both insulin receptors (InR1, InR2) and Foxo, a growth inhibitor. We then performed morphometric measurements on horns, a highly nutrition-sensitive trait, and genitalia, a largely nutrition-insensitive trait. Finally, we used qRT-PCR to assess expression levels of Doublesex and the Hedgehog-signaling gene smoothened following IIS-RNAi. Our results suggest that nutrition responsiveness of both traits is regulated by different IIS components, which transduce nutritional conditions to both Doublesex and Hedgehog pathways, albeit via different IIS pathway members. Combined with previous studies our findings suggest that separate origins of trait exaggeration among insect lineages were enabled through the independent cooption of IIS, yet via reliance on different components therein.
Data from: Bayesian species delimitation can be robust to guide tree inference errors
The Bayesian method of species delimitation (Yang and Rannala, 2010) uses a so-called guide tree to reduce the number of models to be evaluated in the reversible-jump Markov chain Monte Carlo (rjMCMC) algorithm (Green, 1995). It has been pointed out that the method tends to over-split if a random population tree is used as the guide tree (Fujita and Leaché, 2011). Here we conduct a simulation study to examine the performance of the method under more realistic scenarios, that is, when the guide tree is inferred from the sequence data. We found that Bayesian species delimitation is in general robust to errors in the inferred guide tree.
Data from: Robustness to divergence time underestimation when inferring species trees from estimated gene trees
To infer species trees from gene trees estimated from phylogenomic data sets, tractable methods are needed that can handle dozens to hundreds of loci. We examine several computationally efficient approaches—MP-EST, STAR, STEAC, STELLS, and STEM—for inferring species trees from gene trees estimated using maximum likelihood (ML) and Bayesian approaches. Among the methods examined, we found that topology-based methods often performed better using ML gene trees and methods employing coalescent times typically performed better using Bayesian gene trees, with MP-EST, STAR, STEAC, and STELLS outperforming STEM under most conditions. We examine why the STEM tree (also called GLASS or Maximum Tree) is less accurate on estimated gene trees by comparing estimated and true coalescence times, performing species tree inference using simulations, and analyzing a great ape data set keeping track of false positive and false negative rates for inferred clades. We find that although true coalescence times are more ancient than speciation times under the multispecies coalescent model, estimated coalescence times are often more recent than speciation times. This underestimation can lead to increased bias and lack of resolution with increased sampling (either alleles or loci) when gene trees are estimated with ML. The problem appears to be less severe using Bayesian gene-tree estimates.
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: Robustness of the outcome of adult bumblebee infection with a trypanosome parasite after varied parasite exposures during larval development
The outcome of defence by the invertebrate immunity has recently been shown to be more complex than previously thought. In particular, the outcome is affected by biotic and abiotic environmental variation, host genotype, parasite genotype, and their interaction. Knowledge of conditions under which environmental variation affects the outcome of an infection is one important question that relates to this complexity. We here use the model system of the bumblebee, Bombus terrestris infected by the trypanosome, Crithidia bombi, combined with a split-colony design to test the influence of the parasite environment during larval rearing on adult resistance. We find that genotype-specific interactions are maintained, and adult resistance is not influenced. This demonstrates that environmental dependence of bumblebee-trypanosome interactions is not ubiquitous, and yet unknown constraints will maintain standard co-evolutionary dynamics under such environmental deviations.
Data from: A robust semi-parametric test for detecting trait-dependent diversification
Rates of species diversification vary widely across the tree of life and there is considerable interest in identifying organismal traits that correlate with rates of speciation and extinction. However, it has been challenging to develop methodological frameworks for testing hypotheses about trait-dependent diversification that are robust to phylogenetic pseudoreplication and to directionally biased rates of character change. We describe a semi-parametric test for trait-dependent diversification that explicitly requires replicated associations between character states and diversification rates in order to detect effects. To use the method, diversification rates are reconstructed across a phylogenetic tree with no consideration of character states. A test statistic is then computed to measure the association between species-level traits and the corresponding diversification rate estimates at the tips of the tree. The empirical value of the test statistic is compared to a null distribution that is generated by structured permutations of evolutionary rates across the phylogeny. The test is applicable to binary discrete characters as well as continuous-valued traits and can accommodate extremely sparse sampling of character states at the tips of the tree. We apply the test to several empirical datasets and demonstrate that the method has acceptable Type I error rates.
Data from: Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution
A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade's history and subsequently slowdown in rate as niches become saturated – a so-called "Early Burst". Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst - the rate at which phenotypic evolution declines - is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows for the identification and down-weighting of convergent taxa, leading to moderate increases in method performance. We demonstrate the utility and power of these approach by investigating the evolution of body size in cetaceans. Model fitting using maximum likelihood is equivocal with regards the mode of cetacean body size evolution. However, posterior predictive simulation combined with a robust node height test return low support for Brownian motion or rate shift models, but not the early burst model. While the jury is still out on whether early bursts are actually common in nature, our approach will hopefully facilitate more robust testing of this hypothesis. We advocate the adoption of similar posterior predictive approaches to improve the fit and to assess the adequacy of macroevolutionary models in general.
Data from: The peripheral olfactory code in Drosophila larvae contains temporal information and is robust over multiple timescales
We studied the electrophysiological activity of two classes of Drosophila melanogaster larval olfactory sensory neurons (OSNs), Or24a and Or74a, in response to 1 s stimulation with butanol, octanol, 2-heptanone, and propyl acetate. Each odour/OSN combination produced unique responses in terms of spike count and temporal profile. We used a classifier algorithm to explore the information content of OSN activity, and showed that as well as spike count, the activity of these OSNs included temporal information that enabled the classifier to accurately identify odours. The responses of OSNs during continuous odour exposure (5 and 20 min) showed that both types of neuron continued to respond, with no complete adaptation, and with no change to their ability to encode temporal information. Finally, we exposed larvae to octanol for 3 days and found only minor quantitative changes in OSN response to odours, indicating that the larval peripheral code is robust when faced with long-term exposure to odours, such as would be found in a natural context.
Data from: STRUCTURE is more robust than other clustering methods in simulated mixed-ploidy populations
Analyses of population genetic structure has become a standard approach in population genetics. In polyploid complexes, clustering analyses can elucidate the origin of polyploid populations and patterns of admixture between different cytotypes. However, combining diploid and polyploid data can theoretically lead to biased inference with (artefactual) clustering by ploidy. We used simulated mixed-ploidy (diploid-autotetraploid) data to systematically compare the performance of k-means clustering and the model-based clustering methods implemented in STRUCTURE, ADMIXTURE, FASTSTRUCTURE and INSTRUCT under different scenarios of differentiation and with different marker types. Under scenarios of strong population differentiation, the tested applications performed equally well. However, when population differentiation was weak, STRUCTURE was the only method that allowed unbiased inference with markers with limited genotypic information (co-dominant markers with unknown do sage or dominant markers). Still, since STRUCTURE was comparably slow the much faster but less powerful FASTSTRUCTURE provides a reasonable alternative for large datasets. Finally, although bias makes k-means clustering unsuitable for markers with incomplete genotype information, given large numbers of loci (>1000) with known dosage k-means clustering was superior to FASTSTRUCTURE in terms of power and speed. We conclude that STRUCTURE is the most robust method for the analysis of genetic structure in mixed-ploidy populations, although alternative methods should be considered under some specific conditions.
Data from: Not all sequence tags are created equal: designing and validating sequence identification tags robust to indels
Ligating adapters with unique synthetic oligonucleotide sequences (sequence tags) onto individual DNA samples before massively parallel sequencing is a popular and efficient way to obtain sequence data from many individual samples. Tag sequences should be numerous and sufficiently different to ensure sequencing, replication, and oligonucleotide synthesis errors do not cause tags to be unrecoverable or confused. However, many design approaches only protect against substitution errors during sequencing and extant tag sets contain too few tag sequences. We developed an open-source software package to validate sequence tags for conformance to two distance metrics and design sequence tags robust to indel and substitution errors. We use this software package to evaluate several commercial and non-commercial sequence tag sets, design several large sets (maxcount=7,198) of edit metric sequence tags having different lengths and degrees of error correction, and integrate a subset of these edit metric tags to polymerase chain reaction (PCR) primers and sequencing adapters. We validate a subset of these edit metric tagged PCR primers and sequencing adapters by sequencing on several platforms and subsequent comparison to commercially available alternatives. We find that several commonly used sets of sequence tags or design methodologies used to produce sequence tags do not meet the minimum expectations of their underlying distance metric, and we find that PCR primers and sequencing adapters incorporating edit metric sequence tags designed by our software package perform as well as their commercial counterparts. We suggest that researchers evaluate sequence tags prior to use or evaluate tags that they have been using. The sequence tag sets we design improve on extant sets because they are large, valid across the set, and robust to the suite of substitution, insertion, and deletion errors affecting massively parallel sequencing workflows on all currently used platforms.
Data from: Robust and accurate prediction of residue-residue interactions across protein interfaces using evolutionary information
Do the amino acid sequence identities of residues that make contact across protein interfaces covary during evolution? If so, such covariance could be used to predict contacts across interfaces and assemble models of biological complexes. We find that residue pairs identified using a pseudo-likelihood based method to covary across protein-protein interfaces in the 50S ribosomal unit and 28 additional bacterial protein complexes with known structure are almost always in contact in the complex provided that the number of aligned sequences is greater than the average of the lengths of the two proteins. We use this method to make subunit contact predictions for an additional 36 protein complexes with unknown structures, and present models based on these predictions for the tripartite ATP-independent periplasmic (TRAP) transporter, the tripartite efflux system, the pyruvate formate lyase-activating enzyme complex, and the methionine ABC transporter.
Data from: Resilience or robustness: identifying topological vulnerabilities in rail networks
Many critical infrastructure systems have network structure and are under stress. Despite their national importance, the complexity of large-scale transport networks means we do not fully understand their vulnerabilities to cascade failures. The research in this paper examines the interdependent rail networks in Greater London and surrounding commuter area. We focus on the morning commuter hours, where the system is under the most demand stress. There is increasing evidence that the topological shape of the network plays an important role in dynamic cascades. Here, we examine whether the different topological measures of resilience (stability) or robustness (failure) are more appropriate for understanding poor railway performance. The results show that resilience and not robustness has a strong correlation to the consumer experience statistics. Our results are a way of describing the complexity of cascade dynamics on networks without the involvement of detailed agent-based-models, showing that cascade effects are more responsible for poor performance than failures. The network science analysis hints at pathways towards making the network structure more resilient by reducing feedback loops.
Data from: Convergence analysis of a finite element skull model of Herpestes javanicus (Carnivora, Mammalia): implications for robust comparative inferences of biomechanical function
Predictions of skull biomechanical capability based on virtual models constitute a valuable data source for testing hypotheses about craniodental form and feeding behavior. Such comparative analyses also inform dietary reconstruction in extinct species. 3D modeling using Finite Element (FE) methods is a common technique applied to the comparative analysis of craniodental function in extinct and extant vertebrates. However, taxonomically diverse skull models in the literature often are not directly comparable to each other, in part because of distinctions in how boundary conditions are defined, but also because of substantial differences in the number of FEs composing the models. In this study, we test whether a conventional convergence test is adequate in identifying the minimum number of FEs needed to achieve internally stable results for a single species. We constructed a series of skull models of Herpestes javanicus, and simulated unilateral biting across the dentition; the models differed in the number of FEs, degrees of freedom at the joint and bite point constraints, and type of tetrahedral FEs used. We found that convergence patterns differed across constraint types, FE quantities, and bite position simulated. Four-noded tetrahedral (tet-4) FE models with relaxed constraints produced the most stable measurements compared to over-constrained tet-4 models and to relaxed tet-10 models. In absence of an optimal FE quantity from convergence testing, we propose a broadly applicable sub-sampling protocol, whereby average measurement values across multiple models per specimen are used for among-species comparisons. A regime of sampling three low FE quantity models produced the closest estimates of mean measurement values relative to larger model sets, being within the 95% bootstrap estimated confidence intervals. Future studies should focus on identifying sources of variation associated with other FE modeling protocols, so that they can be accounted for before biomechanical attributes from these simulations are used to infer form–function linkage.
Data from: Robust extraction of quantitative structural information from high-variance histological images of livers from necropsied Soay sheep
Quantitative information is essential to the empirical analysis of biological systems. In many such systems, spatial relations between anatomical structures is of interest, making imaging a valuable data acquisition tool. However, image data can be difficult to analyse quantitatively. Many image processing algorithms are highly sensitive to variations in the image, limiting their current application to fields where sample and image quality may be very high. Here, we develop robust image processing algorithms for extracting structural information from a dataset of high-variance histological images of inflamed liver tissue obtained during necropsies of wild Soay sheep. We demonstrate that features of the data can be measured in a fully automated manner, providing quantitative information which can be readily used in statistical analysis. We show that these methods provide measures that correlate well with a manual, expert operator-led analysis of the same images, that they provide advantages in terms of sampling a wider range of information and that information can be extracted far more quickly than in manual analysis.
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.