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Dataset results
15 results for “traces combination”
Fives Input dataset (Cobalt & Darshan traces, combined and preprocessed)
<p>Dataset made of aggregated and curated Cobalt and Darshan logs from the Theta HPC platform at ALCF.</p> <p>Cobalt and Darshan logs were obtained from ALCF Public Data repository (https://reports.alcf.anl.gov/data/index.html) and cover the year 2022. This data was generated from resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. In order to use the scripts contained within this archive, these datasets must be downloaded and placed in the directory '2022' at the root of the extracted archive.</p> <p>The Darshan logs used in this datasets are originillay available in an aggregated form. The levels of details are usually the following : </p> <ul> <li>job (reservation made to a resource manager for some platform resources)</li> <li>application run (application running inside the job, on the reserved resources ; there may be multiple ones, sequentially or in parallel, during a job's execution)</li> <li>I/O operation (read or write registered to a file from a process of an application)</li> </ul> <p>Darshan CSV files for Theta contain job and application runs informations, but individual I/O of each application run is aggregated into a single entry.</p> <p>This resource is organised as a single archive containing:</p> <ul> <li>YAML files with our datasets, at various granularity levels (in 'preprocessed_datastets' directory): <ul> <li>48 files containing each<strong> 1 month worth of job traces</strong> for one of <strong>3 job classes</strong> (4 files per month, one per job class and one with all job classes) </li> <li>4 files containing each the entire year worth of job traces ; 1 file per job class, 1 file with all job classes.</li> </ul> </li> <li>A Jupyter Lab notebook, which contains the necessary routines to create aformentionned datasets from raw logs files from ALCF, for the Theta system</li> <li>A requirements.txt file, describing required Python packages and their versions.</li> <li>Various empty directories meant to receive outputs from the Jupyter notebook.</li> </ul>
Combined data file for Jokinen et al. "Terrestrial organic matter input drives sedimentary trace metal sequestration in a human-impacted boreal estuary", Science of the Total Environment 717, 2020
<p>The datafile contains all the new raw data presented in the figures in the publication.</p>
Data from: Tracing horizontal Wolbachia movements among bees (Anthophila): a combined approach using multilocus sequence typing data and host phylogeny
The endosymbiotic bacterium Wolbachia enhances its spread via vertical transmission by generating reproductive effects in its hosts, most notably cytoplasmic incompatibility (CI). Additionally, frequent interspecific horizontal transfer is evident from a lack of phylogenetic congruence between Wolbachia and its hosts. The mechanisms of this lateral transfer are largely unclear. To identify potential pathways of Wolbachia movements, we performed multilocus sequence typing of Wolbachia strains from bees (Anthophila). Using a host phylogeny and ecological data, we tested various models of horizontal endosymbiont transmission. In general, Wolbachia strains seem to be randomly distributed among bee hosts. Kleptoparasite-host associations among bees as well as other ecological links could not be supported as sole basis for the spread of Wolbachia. However, cophylogenetic analyses and divergence time estimations suggest that Wolbachia may persist within a host lineage over considerable timescales and that strictly vertical transmission and subsequent random loss of infections across lineages may have had a greater impact on Wolbachia strain distribution than previously estimated. Although general conclusions about Wolbachia movements among arthropod hosts cannot be made, we present a framework by which precise assumptions about shared evolutionary histories of Wolbachia and a host taxon can be modelled and tested.
Combinational quantification of distinct neural projections from retrograde tracing
<p>This record contains the experimental cases with the following ids, used for data analysis of the paper. <br><br>SW190423-07<br>Sw190423-08<br>SW190423-09<br>SW190425-07<br>SW190425-08<br>SW190425-09<br>SW190425-10<br>SW190426-01<br>SW190426-02<br>SW190426-03<br>SW190816-01<br>SW190816-03</p>
Dataset for: Combined Ca, Sr isotope and trace element analyses of Late Cretaceous dinosaur teeth: assessing diet versus diagenesis
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Data for: Combining stable isotopes, trace elements, and distribution models to assess the geographic origins of migratory bats
<p>The expansion of industrial-scale wind-energy facilities has increased the production of low-carbon emission energy but has also resulted in mortality of wildlife, including migratory bats. Management decisions can be limited by a lack of understanding of the geographic impact of bats killed at wind-energy facilities. Several studies have leveraged stable hydrogen isotope ratios (δ<sup>2</sup>H) of bat fur to illuminate this issue but are limited in the precision of conclusion because δ<sup>2</sup>H values vary primarily across latitudinal and elevational bands. One approach to increase the precision of geographic assignment is to combine independent inferences about spatial location from additional biomarkers and other related information. To test this possibility, we assigned known-origin individuals of three bat species commonly killed at on-shore wind-energy facilities in North America (<em>Lasiurus</em> <em>borealis</em>, <em>L</em>. <em>cinereus</em>, and <em>Lasionycteris</em> <em>noctivagans</em>) to probable origin using δ<sup>2</sup>H values, trace element concentrations, and species distribution models. We used cross-validation calibrated combined model tuning to determine the degree to which assignment probabilities improved when combining datasets. We found that combining markers typically performed better than single approaches. For <em>L. borealis</em> and <em>L. cinereus</em>, combining all three data sources outperformed any single or other combined approach. With an accuracy set at 80%, an average of 39.7% and 36.0% of each species' total geographic range was considered a potential origin, respectively; stable hydrogen alone included 51.8% and 50.6% of the total geographic area. In contrast, for <em>L. noctivagans</em>, including trace elements did not increase precision, and adding distribution data to δ<sup>2</sup>H values only improved precision by 0.6%. Thus, we found that a combination of multiple biomarkers typically, but not always, outperforms single marker approaches, and optimized combinations of different markers outperform equal weighting of each marker. From a practical perspective, δ<sup>2</sup>H values performed better than trace elements alone; in cases where cost is a limiting factor, the stable hydrogen should be the single biomarker used in conjunction with species distribution models. Overall, these results highlight the importance of validating methods for each species they are applied to and show that combining information from intrinsic biomarker approaches is a useful tool to document bat movements.</p>
Data for: Combining stable isotopes, trace elements, and distribution models to assess the geographic origins of migratory bats
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Data from: Tracing horizontal Wolbachia movements among bees (Anthophila): a combined approach using multilocus sequence typing data and host phylogeny
Open the record for dataset details and reuse information.
T-47D Giredestrant + palbociclib combination TraCe-seq (NGS4327)
GEO Series GSE260703. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
Combined Lineage Tracing and scRNA-seq Reveals Unexpected First Heart Field Predominance of Human iPSC Differentiation
GEO Series GSE202398. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Combined Genetic and Genealogic Studies Uncover a Large BAP1 Cancer Syndrome Kindred Tracing Back Nine Generations to a Common Ancestor from the 1700s.
GEO Series GSE74573. Homo sapiens. 8 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
Neurotropism and Neurotoxicity Comparison among Retrograde Viral Tracers and Their Combinational Application in High-order Circuit Tracing
GEO Series GSE115865. Mus musculus. 73 samples. Type: Expression profiling by high throughput sequencing.
Tralement Versus a Fixed-dose Trace Element Combination Product to Evaluate Manganese Safety
ClinicalTrials.gov study NCT05661682. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Tralement vs. Fixed-dose Trace Element Combination Product in Patients >3 to 17 Years of Age Requiring Long-term PN
ClinicalTrials.gov study NCT05677126. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Single-cell transcriptomic phenotyping combined with lineage tracing using paired B cell receptor repertoires identified both persistent antibody-secreting cell as well as memory B cell subsets after
GEO Series GSE149133. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
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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.