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171 results for “performance prediction”
Data from: Mite load predicts the quality of sexual color and locomotor performance in a sexually dichromatic lizard
Since Darwin, the maintenance of bright sexual colors has recurrently been linked to mate preference. However, the mechanisms underpinning such preferences for bright colors would not be resolved for another century. Likely, the idea of selection for colors that could decrease the chances of survival (e.g. flashy colors that can inadvertently attract predators) was perceived as counterintuitive. It is now widely-accepted that these extreme colors often communicate to mates the ability to survive despite a 'handicap' and act as honest signals of individual quality when they are correlated with the quality of other traits that are directly linked to individual fitness. Sexual colors in males are frequently perceived as indicators of infection resistance, in particular. Still, there remains considerable discord among studies attempting to parse the relationships between the variables associating sexual color and infection resistance, such as habitat type and body size. This discord may arise from complex interactions between these variables. Here, we ask if sexual color in male Florida scrub lizards (Sceloporus woodi) is an honest signal of resistance to chigger mite infection. To this end, we use linear modeling to explore relationships between mite load, different components of sexual color, ecological performance, body size, and habitat type. Our data show that that the brightness of sexual color in scrub lizards is negatively associated with the interaction between mite load and body size, and scrub lizards suffer decreased endurance capacity with increases in mite load. Our data also indicate that mite load, performance, and sexual color in male scrub lizards can vary between habitat types. Collectively these results suggest that sexual color in scrub lizards is an honest indicator of individual quality and further underscore the importance of considering multiple factors when testing hypotheses related to the maintenance of sexual color.
Data from: Behavioural hypervolumes of spider communities predict community performance and disbandment
Trait-based ecology argues that an understanding of the traits of interactors can enhance the predictability of ecological outcomes. We examine here whether the multidimensional behavioural-trait diversity of communities influences community performance and stability in situ. We created experimental communities of web-building spiders, each with an identical species composition. Communities contained one individual of each of five different species. Prior to establishing these communities in the field, we examined three behavioural traits for each individual spider. These behavioural measures allowed us to estimate community-wide behavioural diversity, as inferred by the multidimensional behavioural volume occupied by the entire community. Communities that occupied a larger region of behavioural-trait space (i.e. where spiders differed more from each other behaviourally) gained more mass and were less likely to disband. Thus, there is a community-wide benefit to multidimensional behavioural diversity in this system that might translate to other multispecies assemblages.
Integrating QSAR models predicting acute contact toxicity and mode of action profiling in honey bees (A. mellifera): Data curation using open source databases, performance testing and validation
<p>This excel file (DOI: <a href="https://doi.org/10.5281/zenodo.3755675">https://doi.org/10.5281/zenodo.3755675</a>) provides the collection of raw data used for developing the first integrative Quantitative Structure-Activity Relationship (QSAR) model using EFSA's OpenFoodTox, US-EPA ECOTOX and Pesticide Properties DataBase i) to predict acute contact toxicity (LD<sub>50</sub>) and ii) to profile the Mode of Action (MoA) of pesticides active substances in honey bees (<em>Apis mellifera</em>)<em>. </em>Chemical identifiers (e.g. SMILES, CAS n., InChI) and acute contact toxicity data (LD<sub>50</sub>) on honey bees were used to develop and validate i) a two-category QSAR model (toxic/non-toxic; n=411) (sensitivity =0.93), specificity =0.85), balanced accuracy =0.90), Matthews correlation coefficient MCC=0.78), and ii) a regression-based model (n=113) (R2=0.74; MAE=0.52). Similarly, current study proposes the first MoA profiling for 113 pesticides active substances and the first harmonised MoA classification scheme for acute contact toxicity in honey bees, including LD<sub>50s</sub> data points from three different databases such as EFSA's OpenFoodTox, US-EPA ECOTOX and Pesticide Properties DataBase. Such classification allows to further define MoAs and the target site of Plant Protection Products (PPPs) active substances, thus enabling regulators and scientists to refine chemical grouping and toxicity extrapolations for single chemicals and component-based mixture risk assessment of multiple chemicals.</p> <p>The full data collection and analysis of QSAR models, toxicity data (LD<sub>50</sub>) and Mode of Action (Moa) data are described in Carnesecchi et al., 2020 (DOI: doi.org/10.1016/j.scitotenv.2020.139243).</p> <p>This work was supported by the European Food Safety Authority (EFSA) [contract number: OC/EFSA/SCER/2018/01 and NP/EFSA/AFSCO/2016/02 (Edoardo Carnesecchi)].</p>
Data from: Contemporary evolution of sea urchin gamete-recognition proteins: experimental evidence of density-dependent gamete performance predicts shifts in allele frequencies over time
Species whose reproductive strategies evolved at one density regime might be poorly adapted to other regimes. Field and laboratory experiments on the sea urchin Strongylocentrotus franciscanus examined the influences of the two most common sperm bindin alleles, which differ at two amino acid sites, on fertilization success. In the field experiment, the Arginine/Glycine (RG) genotype performed best at low densities and the Glycine/Arginine (GR) genotype at high densities. In the lab experiment, the RG genotype had a higher affinity with available eggs, whereas the GR genotype was less likely to induce polyspermy. These sea urchins can reach 200 years of age. The RG allele dominates in old sea urchins, whereas younger sea urchins have near equal RG and GR allele frequencies. A latitudinal cline in RG and GR genotypes is consistent with longer survival of sea urchins in the north and with predominance of RG genotypes in older individuals. The oldest sea urchins were likely conceived at low densities, before sea-urchin predators, like sea otters, were overharvested and sea urchin densities exploded off the west coast. Contemporary evolution of gamete-recognition proteins might allow species to adapt to shifts in abundances and reduces the risk of reproductive failure in altered populations.
Data from: Towards a predictive framework for biocrust mediation of plant performance: a meta-analysis
Understanding the importance of biotic interactions in driving the distribution and abundance of species is a central goal of plant ecology. Early vascular plants likely colonized land occupied by biocrusts — photoautotrophic, surface-dwelling soil communities comprised of cyanobacteria, bryophytes, lichens, and fungi — suggesting biotic interactions between biocrusts and plants may have been at play for some 2,000 million years. Today, biocrusts coexist with plants in dryland ecosystems worldwide, and have been shown to both facilitate or inhibit plant species performance depending on ecological context. Yet, the factors that drive the direction and magnitude of these effects remain largely unknown. We conducted a meta-analysis of plant responses to biocrusts using a global dataset encompassing 1,004 studies from six continents. Our meta-analysis revealed there is no simple positive or negative effect of biocrusts on plants. Rather, plant responses differ by biocrust composition and plant species traits and vary across plant ontogeny. Moss-dominated biocrusts facilitated, while lichen-dominated biocrusts inhibited overall plant performance. Plant responses also varied among plant functional groups: C4 grasses received greater benefits from biocrusts compared to C3 grasses, and plants without N-fixing symbionts responded more positively to biocrusts than plants with N-fixing symbionts. Biocrusts decreased germination but facilitated growth of non-native plant species. Our results suggest that interspecific variation in plant responses to biocrusts, contingent on biocrust type, plant traits, and ontogeny can have strong impacts on plant species performance. These findings have important implications for understanding plant community assembly processes and ecosystem responses to global change.
Supplemental Materials - Performance Figures for "A Model for Predicting the (re)-occurrence of a ≥40% eGFR Decline in a large Population-based cohort of Persons with or At-Risk of Chronic Kidney Disease " paper
<p>The zip file contains performance metrics figures for each dynamic Bayesian Network (DBN) model, stratified by comorbidities, race, CKD stages, and ethnicity.</p> <p>Contains:</p> <ul> <li>Stratified: Bootstrapping of 1000 iterations and 1000 samples with stratified proportions (as in the original population of the test set) of rapid eGFR decliners and non-decliners.</li> </ul> <p> </p> <p>Second zip contains DBN structures as matrices for 2 periods study entry to entry period and entry period to year 1 for all sites in 2 excel files.</p>
Predictive Design of Ultrastretchable Electrodes with Strain-Insensitive Performance via Robotics- and Machine Learning-Integrated Workflow
Open the record for dataset details and reuse information.
Predicted HHV values for woody biomass samples from USDA-AFRI project using the best performing models.
<p>Predicted HHV values for samples from the USDA-AFRI project using the best-performing models from the cross-validation process.</p>
Results from "The Effects of Nonlinear Signal on Expression-Based Prediction Performance"
<p>This zipped archive contains the result files from running the pipeline described in the manuscript "The Effects of Nonlinear Signal on Expression-Based Prediction Performance".</p>
Input data from "The Effects of Nonlinear Signal on Expression-Based Prediction Performance"
<p>These files are a 1GB fragments of a compressed archive containing the data used in the manuscript "The Effects of Nonlinear Signal on Expression-Based Prediction Performance".</p> <p>To simplify the uploading process, the file was split into chunks using the `split` utility in Linux. They can be joined back together with the command `cat input_data* > input_data.tar.gz`</p> <p>All data used is either publicly available or generated by this project. The subsets of the Recount3 and GTEx that we used are not owned by us, so putting them in this creative commons repository should not be construed as re-licensing them. </p> <p> </p>
Model weights from "The Effects of Nonlinear Signal on Expression-Based Prediction Performance"
<p>This file stores a representative set of saved models from the manuscript "The Effects of Nonlinear Signal on Expression-Based Prediction Performance". </p> <p>To simplify the uploading process, the file was split into chunks using the `split` utility in Linux. They can be joined back together with the command `cat model_weights* > model_weights.tar.gz`</p> <p>These saved files correspond to the weights and optimizer state of models trained on various biological tasks. They can be "rehydrated" using the `load_model` function of the associated model class from this repo: https://github.com/greenelab/linear_signal</p>
Data Set of Publication on Accurate Performance Predictions with Component-based Models of Data Streaming Applications
<p>This is the data set for the article "Accurate Performance Predictions with Component-based Models of Data Streaming Applications" by Dominik Werle, Stephan Seifermann and Anne Koziolek which appears in the proceedings of the 16th European Conference on Software Architecture (ECSA).</p> <p>The data set contains measurements of the evaluation system, models of the system, simulation results, derived analysis results and code for running the simulation.</p> <p>This work was supported by KASTEL Security Research Labs and by the German Research Foundation (DFG) under project number 432576552, HE8596/1-1 (FluidTrust).</p>
Morphological heart age from CTA: Predictions, Performance and Saliency Maps
<p>This data distribution contains regression results for age prediction from computed tomography angiography images from the SCAPIS dataset, as well as proof-of-concept experiments concerning the prediction of known volumetric features estimated through segmentation of the images.</p> <p>Each sub-folder represents one experiment.</p> <p>For each experiment (sex-stratified), there is a csv file '0.csv'<br>with the following structure</p> <p>Row 1: subject id1, subject id2, subject id3, ...<br>Row 2: reference value1, reference value2, reference value3, ...<br>Row 3: predicted value1, predicted value2, predicted value3, ...</p> <p>There is also a file 'results_summary.txt' which provides a text output of the quality measures corresponding to each experiment:<br>Mean Absolute Error (MAE)<br>R^2 (R2)<br>Pearson correlation (r_p)<br>Spearman correlation (r_s)<br>Intraclass Correlation Coefficient (ICC)</p> <p>The following sub-folders/experiments contain saliency maps:<br>- main (the main experiment with PCA from the whole heart)<br>- main_linear (the main experiment without PCA from the whole heart)<br>- poc_lvv (proof-of-concept: left ventricle volume)<br>- poc_rvv (proof-of-concept: right ventricle volume)<br>- poc_lav (proof-of-concept: left atrium volume)<br>- poc_rav (proof-of-concept: right atrium volume)<br>- poc_myov (proof-of-concept: myocardium volume)<br>- poc_av (proof-of-concept: aorta volume)</p> <p>The feature subsets use the following encoding (for the feature subset experiments, the path contains the numbers representing the included features):<br>1: Median Density<br>2: Median Volume<br>3: Stddev Density<br>4: Stddev Volume</p> <p>Ethics:<br>The subjects/images are all anonymized, with a chronological age rounded to whole months.</p> <p>Ethics approval was obtained from the Swedish Ethical Review Authority (Dnr 2022-07308-01) to conduct this research study related to human subjects, with associated sex and age information. All subjects provided informed written consent for their collected data to be used for research and for that research to be published. The study adheres to the Declaration of Helsinki. SCAPIS has been approved as a multicentre trial by the ethics committee at Umea University and adheres to the Declaration of Helsinki.</p>
Data and code for manuscript: The performance and potential of deep learning for predicting species distributions
<p>This repository contains the (preprocessed) data and code for the publication titled "The performance and potential of deep learning for predicting species distributions".</p>
Supplementary Data for "Exploring structure-function relationships in engineered receptor performance using computational structure prediction"
<p>These data are supplementary data for the manuscript "<strong>Exploring structure-function relationships in engineered receptor performance using computational structure prediction</strong>", which has been submitted for consideration for publication. These data include protein structure predictions used in this study.</p>
Do the predicted suitability scores from species distribution models correlate with species performance on-ground?
<p>Species distribution models are a very popular statistical tool for inferring potential distribution range of species across space and time and are thought to be a good predictor for habitat suitability. Some studies have suggested that if these models are reliable, predicted habitat suitability (PHS) should relate to species traits visualization, growth potential, body size, abundance. We validated this hypothesis by estimating association between the PHS and species abundance for 17 avian species endemic to the Western Ghats - Sri Lanka biodiversity hotspot. Additionally, we compared the PHS of sites where species were detected in both seasons (wet and dry) against sites where they were detected in the dry season alone. As a proxy for abundance, we estimated single-season occupancy estimates (ψ) using detection/non-detection data from multiple visits to the survey sites. We report significant and positive PHS-ψ correlation, though the strength of this association varied across species and models. Half of the species showed higher suitability scores for the sites where they were detected year round. The results presented here suggest that the predictive models can be used as a proxy for habitat quality, in addition to inferring the potential distribution.</p>
Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat
<p>Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration. --</p>
The impact of the cross-docked poses on the performance of machine learning classifier for protein-ligand binding pose prediction
<p>Datasets, features, and some representative scripts utilized in the paper "The impact of the cross-docked poses on the performance of machine learning classifier for protein-ligand binding pose prediction".</p>
Mesh data for multi-impeller mixing performance prediction in stirred tanks using mean age theory approach
<p>The upload files include mesh data for all configurations studied in the research: multi-impeller mixing performance prediction in stirred tanks using mean age theory approach.</p>
Physical Performance Testing and Frailty in Prediction of Early Postoperative Course After Cardiac Surgery
ClinicalTrials.gov study NCT05166863. IPD Sharing: UNDECIDED. Countries: 1. Publications: 8.
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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)
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.