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Dataset results
27 results for “cost-effectiveness model”
Data from: A cost-effective blood DNA methylation-based age estimation method in domestic cats, Tsushima leopard cats (Prionailurus bengalensis euptilurus), and Panthera species, using targeted bisulfite sequencing and machine learning models
<p><span>Knowledge of individual age can help both in-situ and ex-situ conservation programs to design more efficient and suitable management plans for targeted wildlife species. DNA methylation is one of the epigenetic aging markers that has emerged as a promising tool that can estimate age with high accuracy using only a tiny amount of biological material, which can be collected in a minimally invasive way. Here, we sequenced five targeted genetic regions and used </span><span>8–23</span><span> selected CpG sites to build age estimation models with machine learning methods </span><span>with about only $3–7 per sample</span><span>, using blood samples of seven Felidae species—ranging from small to big, and domestic to endangered species: domestic cats (<em>Felis catus</em>, 139 samples), Tsushima leopard cats (<em>Prionailurus bengalensis euptilurus</em>, 84 samples), and five<em> Panthera </em>species (96 samples). </span><span>The models built achieved satisfactory accuracy—the mean absolute error of the best models was 1.966, 1.348, and 1.552 years in domestic cats, Tsushima leopard cats, and <em>Panthera</em> spp., respectively.</span><span> Our models in domestic cats and Tsushima leopard cats were applicable to individuals regardless of health conditions, indicating the high applicability of our models to samples collected from diverse situations, e.g., rescued individuals in the context of conservation. We also showed the possibility of developing universal age estimation models for the five<em> Panthera</em> spp. using two of the five genetic regions, suggesting an even lower cost to use our models for future applications.</span></p>
Data from: A cost-effective blood DNA methylation-based age estimation method in domestic cats, Tsushima leopard cats (Prionailurus bengalensis euptilurus), and Panthera species, using targeted bisulfite sequencing and machine learning models
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Performance Measurement Dataset of the HPC Benchmarks FASTEST, Kripke, and RELeARN for Cost-Effective Modeling Analysis with Extra-P
<p>Performance Measurement Dataset of the HPC Benchmarks FASTEST, Kripke, RELeARN for Scalability Studies with Extra-P. This data was used to analyze cost-effective modeling approaches presented in the IPDPS 2020 paper "Learning Cost-Effective Sampling Strategies for Empirical Performance Modeling".</p>
Data and codes for "The impact, costs, and cost-effectiveness of tuberculosis outbreak investigations in the United States: a model-based analysis"
<p>Data and codes for the manuscript entitled:</p> <p>"<strong>The impact, costs, and cost-effectiveness of tuberculosis outbreak investigations in the United States: a model-based analysis"</strong></p> <p> </p> <p><strong>Please see Readme.txt for details</strong></p>
Simulation results for "COVID-19 vaccination in Sindh Province, Pakistan: a modelling study of health impact and cost-effectiveness"
<p>The high-performance computing results for raw epidemiological simulations and quantiled scenarios associated with https://doi.org/10.1101/2021.02.24.21252338.</p> <p>All results stored as compressed rds files of data.table objects (use-able as data.frame objects) for use with R programming language.</p>
Data from: Cost-effectiveness of leveraging existing HIV primary health systems and community health workers for hypertension screening and treatment in Africa: An individual-based modelling study
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Supplementary material 6 from: Lommen STE, Jongejans E, Leitsch-Vitalos M, Tokarska-Guzik B, Zalai M, Müller-Schärer H, Karrer G (2018) Time to cut: population models reveal how to mow invasive common ragweed cost-effectively. NeoBiota 39: 53-78. https://doi.org/10.3897/neobiota.39.23398
Stochastic population growth for alternative seed bank scenarios (graphic results, population dynamics) :
Supplementary material 8 from: Lommen STE, Jongejans E, Leitsch-Vitalos M, Tokarska-Guzik B, Zalai M, Müller-Schärer H, Karrer G (2018) Time to cut: population models reveal how to mow invasive common ragweed cost-effectively. NeoBiota 39: 53-78. https://doi.org/10.3897/neobiota.39.23398
r-cost curves for different seed survival scenarios and reference data sets (graphic results, population dynamics) :
3D printed models are an accurate, cost-effective, and reproducible tool for quantifying terrestrial thermal environments
<p>Dataset used in Alujević et al. 2023. 3D printed models are an accurate, cost-effective, and reproducible tool for quantifying terrestrial thermal environments. </p>
Effectiveness and Cost-effectiveness of the New Orleans Intervention Model for Infant Mental Health
ClinicalTrials.gov study NCT02653716. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Which Model of Care is the Most Cost-effective in the Treatment of Musculoskeletal Disorders?
ClinicalTrials.gov study NCT06832852. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Data from: Sequence Capture using PCR-generated Probes (SCPP): a cost-effective method of targeted high-throughput sequencing for non-model organisms
Recent advances in high-throughput sequencing library preparation and subgenomic enrichment methods have opened new avenues for population genetics and phylogenetics of non-model organisms. To multiplex large numbers of indexed samples while sequencing predominantly orthologous, targeted regions of the genome, we propose modifications to an existing, in-solution capture that utilizes PCR products as target probes to enrich library pools for the genomic subset of interest. The sequence capture using PCR-generated probes (SCPP) protocol requires no specialized equipment, is highly flexible, and significantly reduces experimental costs for projects where a modest scale of genetic data is optimal (25-100 genomic loci). Our alterations enable application of this method across a wider phylogenetic range of taxa and result in higher capture efficiencies and coverage at each locus. Efficient and consistent capture over multiple SCPP experiments and at various phylogenetic distances is demonstrated, extending the utility of this method to both phylogeographic and phylogenomic studies.
Supplementary material 7 from: Lommen STE, Jongejans E, Leitsch-Vitalos M, Tokarska-Guzik B, Zalai M, Müller-Schärer H, Karrer G (2018) Time to cut: population models reveal how to mow invasive common ragweed cost-effectively. NeoBiota 39: 53-78. https://doi.org/10.3897/neobiota.39.23398
Deterministic population models per reference data set (graphic results, population dynamics) :
Supplementary material 3 from: Lommen STE, Jongejans E, Leitsch-Vitalos M, Tokarska-Guzik B, Zalai M, Müller-Schärer H, Karrer G (2018) Time to cut: population models reveal how to mow invasive common ragweed cost-effectively. NeoBiota 39: 53-78. https://doi.org/10.3897/neobiota.39.23398
Burial experiments (location table, methods, graphic results) :
Supplementary material 5 from: Lommen STE, Jongejans E, Leitsch-Vitalos M, Tokarska-Guzik B, Zalai M, Müller-Schärer H, Karrer G (2018) Time to cut: population models reveal how to mow invasive common ragweed cost-effectively. NeoBiota 39: 53-78. https://doi.org/10.3897/neobiota.39.23398
Parametrisation of population models of experimental mowing treatments (model parameterisation) :
Supplementary material 4 from: Lommen STE, Jongejans E, Leitsch-Vitalos M, Tokarska-Guzik B, Zalai M, Müller-Schärer H, Karrer G (2018) Time to cut: population models reveal how to mow invasive common ragweed cost-effectively. NeoBiota 39: 53-78. https://doi.org/10.3897/neobiota.39.23398
Parametrisation of population models of unmanaged references (model parameterisation) :
Supplementary material 2 from: Lommen STE, Jongejans E, Leitsch-Vitalos M, Tokarska-Guzik B, Zalai M, Müller-Schärer H, Karrer G (2018) Time to cut: population models reveal how to mow invasive common ragweed cost-effectively. NeoBiota 39: 53-78. https://doi.org/10.3897/neobiota.39.23398
Demographic survey of reference populations (location table, methods) :
Supplementary material 1 from: Lommen STE, Jongejans E, Leitsch-Vitalos M, Tokarska-Guzik B, Zalai M, Müller-Schärer H, Karrer G (2018) Time to cut: population models reveal how to mow invasive common ragweed cost-effectively. NeoBiota 39: 53-78. https://doi.org/10.3897/neobiota.39.23398
Analysis of mowing experiment data (statistical analysis of empirical data) :
A Cost-Effective Semi-Ab Initio Approach to Model Relaxation in Rare-Earth Single-Molecule Magnets. Open data set
<p>Data supporting the original figures 2 and 3 of the related publication.</p>
Data from: Sequence Capture using PCR-generated Probes (SCPP): a cost-effective method of targeted high-throughput sequencing for non-model organisms
Open the record for dataset details and reuse information.
ScienceDex guides
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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)
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.