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722 results for “use case”
Data from: DNA metabarcoding for diet analysis and biodiversity: A case study using the endangered Australian sea lion (Neophoca cinerea)
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Data from: Using biogeographic history to inform conservation: the case of Preble’s meadow jumping mouse
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Data from: Inferring introgression using RADseq and DFOIL: power and pitfalls revealed in a case study of spiny lizards (Sceloporus)
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Data from: Using big data to assess prescribing patterns in Greece: the case of chronic obstructive pulmonary disease
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Data from: Automated integration of trees and traits: a case study using paired fin loss across teleost fishes
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How do host-plant use and seasonal life cycle relate to insect body size: A case study on European geometrid moths (Lepidoptera: Geometridae)
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Data from: Establishing the plant component of a tallgrass prairie restoration using a remnant reference ecosystem model: A case study
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Incipient speciation and the impact on taxonomic decision: a case study using a sky island sister species pair of stag beetle (Lucanus; Lucanidae)
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Data from: Simulation-based validation of spatial capture-recapture models: a case study using mountain lions
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Five year pediatric use of a digital wearable fitness device: lessons from a pilot case study
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Data Publication accompanying the paper "How FAIR can you get? Image Retrieval as a Use Case to calculate FAIR Metrics"
<pre>This dataset is the result of a benchmark run for a use-case-centric FAIR metric. The applied tech stack uses OAI-PMH and DataCite. The use case central to this benchmark is the retrieval of temporally and spatially annotated images. The zipped archives includes the data created during the first test run in June 2018. </pre>
ASPIDE: SERMAS diffusion-weighted image processing use-case
<p>This repository contains the outputs of the diffusion-weighted image processing use-case of the ASPIDE project for a single subject. The input files were obtained from the Human Connectome Project (HCP) database. HCP is an open project and the full unprocessed dataset can be obtained from <a href="https://db.humanconnectome.org/app/template/Login.vm">https://db.humanconnectome.org/app/template/Login.vm</a>.</p>
Sample dataset for the UNICAL use case - ASPIDE
<p>This repository contains a sample of the data used for the urban computing use-case of the ASPIDE project. The dataset contains about 56,000 geotagged items published in Flickr from January 2006 to May 2016 in the center of Rome.</p> <p> </p>
Maximizing human effort for analyzing scientific images: a case study using digitized herbarium sheets
<p>This directory contains "gold standard" set of phenological annotations of herbarium specimen photographs, in Acer_Prunus_gold_standard_phenological_data.csv. The methods used to generate these data are described in Brenskelle, L., R. P. Guralnick, M. Denslow, and B. J. Stucky. 2020. Maximizing human effort for analyzing scientific images: A case study using digitized herbarium sheets. Applications in Plant Sciences 8(6): e11370.</p>
Data from MECO(n) model simulations on "Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018"
<p>This tar-files contain the results of the MECO(n) model, which are published in</p> <p>T. Klausner, M. Mertens, H. Huntrieser, M. Galkowski, G. Kuhlmann, R. Baumann, A. Fiehn, P. Jöckel, M. Pühl, and A. Roiger: Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO<sub>2</sub> and CH<sub>4</sub> in situ observations in summer 2018, Elementa: Science of the Anthropocene (Ref.: Ms. No. ELEMENTA-D-19-00074R1), 2019.</p>
Supplementary material 1 from: Crookes S, Heer T, Castañeda RA, Mandrak NE, Heath DD, Weyl OLF, MacIsaac HJ, Foxcroft LC (2020) Monitoring the silver carp invasion in Africa: a case study using environmental DNA (eDNA) in dangerous watersheds. NeoBiota 56: 31-47. https://doi.org/10.3897/neobiota.56.47475
Table 1
Supplementary material from: Ashurov S, Othman AHA, Bin Rosman R, Bin Haron R (2020) The determinants of foreign direct investment in Central Asian region: A case study of Tajikistan, Kazakhstan, Kyrgyzstan, Turkmenistan and Uzbekistan (A quantitative analysis using GMM). Russian Journal of Economics 6(2): 162-176. https://doi.org/10.32609/j.ruje.6.48556
Arellano–Bond dynamic panel-data estimation
Data from: Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation
<p class="AbstractSummary"><b>Background</b></p> <p class="AbstractSummary">Prostate cancer (PC) is the most frequently diagnosed cancer in North American men. Pathologists are in critical need of accurate biomarkers to characterize PC, particularly to confirm the presence of intraductal carcinoma of the prostate (IDC-P), an aggressive histopathological variant for which therapeutic options are now available. Our aim was to identify IDC-P with Raman micro-spectroscopy and machine learning technology following a protocol suitable for routine clinical histopathology laboratories.</p> <p class="AbstractSummary"><b>Methods and findings</b></p> <p class="AbstractSummary">We used Raman micro-spectroscopy to differentiate IDC-P from PC, as well as PC and IDC-P from benign tissue on formalin-fixed paraffin-embedded first-line radical prostatectomy specimens (embedded in tissue microarrays, TMAs) from 483 patients treated in three Canadian institutions between 1993 and 2013. The main measures were the presence or absence of IDC-P and of PC, regardless of the clinical outcomes. Most of the 483 patients were pT2 stage (44–69%), and pT3a (22–49%) was more frequent than pT3b (9–12%). After approval of the construction of the TMAs by local ethics review board, the diagnostic accuracy study was approved by the Centre hospitalier de l'Université de Montréal (CHUM) ethics review board. Briefly, two consecutive sections of each TMA block were cut. The first section was transferred onto a glass slide to perform immunohistochemistry with H&E counterstaining for cell identification. The second section was placed on an aluminum slide, dewaxed, and then used to acquire an average of 7 Raman spectra per specimen (between 4 and 24 Raman spectra, 4 acquisitions / TMA core). Raman spectra of each cell type were then analyzed to retrieve tissue-specific molecular information and to generate classification models using machine learning technology. <span>Models were trained and cross-validated using data from one institution. Accuracy, sensitivity and specificity were respectively of 87 ± 5%, 86 ± 6% and 89 ± 8% to differentiate PC from benign tissue, and of 95 ± 2%, 96 ± 4% and 94 ± 2% respectively to differentiate IDC-P from PC. The trained models were then tested on data from two independent institutions, reaching accuracies, sensitivities and specificities of 84 and 86%, 84 and 87%, and 81 and 82%, respectively</span><span> to diagnose PC, and of 85 and 91%, 85 and 88%, and 86 and 93% respectively for the identification of IDC-P.</span> IDC-P could further be differentiated from high-grade prostatic intraepithelial neoplasia (HGPIN), a pre-malignant intraductal proliferation which can be mistaken as IDC-P, with accuracies, sensitivities and specificities >95% in both training and testing cohorts. As we used stringent criteria to diagnose IDC-P, the main limitation of our study is the exclusion of borderline, difficult to classify lesions from our datasets.</p> <p class="AbstractSummary"><b>Conclusions</b></p> <p>In this study, we developed classification models for the analysis of Raman micro-spectroscopy data to differentiate IDC-P, PC and benign tissue, including HGPIN. Raman micro-spectroscopy could be a next-generation histopathological technique used to <span>reinforce the identification of high-risk PC patients and lead to more precise diagnosis of IDC-P.</span></p>
Supplementary material 8 from: Zizka VMA, Weiss M, Leese F (2020) Can metabarcoding resolve intraspecific genetic diversity changes to environmental stressors? A test case using river macrozoobenthos. Metabarcoding and Metagenomics 4: e51925. https://doi.org/10.3897/mbmg.4.51925
Table S1. Number of macroinvertebrate individuals per sample and season
First use of acoustic calls to distinguish cryptic fish species: Dascyllus aruanus complex as a case study
From a practical point of view, the determination of species in the wild is based on their phenotypes. Consequently, many species remain unknown because they are visually indistinguishable from described species. Although molecular methods and advances in bioacoustical analysis have been extensively used to uncover cryptic species, the combination of both methodologies is still rare and concerns only some terrestrial taxa such as insects, bats, frogs and birds. In this study, we aim to determine whether the sounds produced by different populations of fish can also be a tool to distinguish and identify cryptic species. The humbug damselfish complex, Dascyllus aruanus, is widely distributed across the Indo-Pacific Ocean and, since 2019, is thought to be composed of at least two species with Dascyllus aruanus in the Pacific Ocean and Dascyllus abudafur in the Indian Ocean. Recordings were made over a large geographical area with populations from Madagascar (Indian Ocean), Taiwan (Pacific Ocean) and French Polynesia (Society Islands). Two kinds of sounds were used for analysis: sounds associated with conspecific chases, and sounds produced during the "signal jump" of courtship behaviour. The sounds associated with signal jumps differ geographically. Acoustic feature differences between Taiwan and Madagascar align with the existence of genetic differences confirming specific status and supporting for the first time that sounds can help to discriminate cryptic species in Teleosts. However, differences in both acoustic features and genetic data can also be found between Taiwan and French Polynesia suggesting two clearly distinct populations. Using the same reasoning, we propose to resurrect the epithet "emamo" (Lesson 1830) for the Society Island humbug damselfish. Interestingly, sounds associated to conspecific chases are more variable than sounds related to signal jumps, suggesting that there are more constraints on sounds related to courtship since they would serve as indicators for species identity and contribute to premating isolation.
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.