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Dataset results
230 results for “Data Aggregation”
uncropped western blots for analysis of RPN13 ubiquitylation and NRF1 activation by protein aggregates, as well as source data for qPCR plots and flow cytometry gating and FCS files for agDD-GFP in HeLa or HEK cells
<p>This entry contains uncropped blots for Fig 4D and Fig S4C, Fig. 5B, Fig S5 and Fig S6, and the raw FCS files for Flow Cytometry data in doi.org/10.1101/2024.08.30.610524.</p>
Data set. Optical properties. J-aggregate:PVA polaritonic films.
<p>Optical properties (real and imaginary part of permittivity) of J-aggregate:PVA materials analysed in manuscript entitled "Bio-inspired building blocks for all-organic metamaterials from visible to near-infrared". </p> <p>arXiv preprint arXiv:2210.02315</p> <p> </p> <p> </p> <p> </p>
M100 dataset: time-aggregated data for anomaly detection
<p>This entry is a part of a larger data set collected from the most recent Tier-0 supercomputer hosted at CINECA (Marconi100, <a href="https://www.hpc.cineca.it/hardware/marconi100">https://www.hpc.cineca.it/hardware/marconi100</a>). The data covers the entirety of the system, ranging from the computing nodes (980+ computing nodes) internal information such as core loads, temperatures, frequencies, memory write/read operations, CPU power consumption, fan speed, GPU usage details, etc., to the system-wide information, including the liquid cooling infrastructure, the air conditioning system, the power supply units, workload manager statistics, and job-related information, system status alerts, and weather forecast. <br> It comprises hundreds of metrics measured on each computing node, in addition to hundreds of other metrics gathered from sensors monitored along all system components.</p> <p>This particular dataset is made for anomaly detection purposes, it contains the same data as the main dataset but aggregated over time, with one Parquet file for each node. The data is distributed in tarballs, each one including all the files relative to the nodes contained in a given rack. For each file, the rows represent periods of 15 minutes, with the columns being aggregated values (average, standard deviation, min, max) over all the IPMI metrics that are available for the node; an additional column contains anomaly labels from Nagios.</p> <p>More details can be found in the companion repository: <a href="https://gitlab.com/ecs-lab/exadata">https://gitlab.com/ecs-lab/exadata</a>, including the spatial distribution of the nodes in the room.</p>
Aggregated data issued from the JOBIM 2021 'Gender equality observational study'
<p>JOBIM 2021 Gender analysis</p> <p>This repository contains data and script related to our observation study of gender impact on asking behavior during JOBIM 2021. In agreement with our <a href="https://research.pasteur.fr/en/project/jobim-2021-pilot-project-gender-speaking-differences-in-academia/">data policy and RGPD regulations</a>, only aggregated, anonymous and/or publicly available information are posted in this repository. Zoom exports, registration survey and observation files containing names of askers and their accompanying scripts remains private.</p> <p>Citation</p> <p>If you wish to use our data please cite our manuscript: .https://www.biorxiv.org/content/10.1101/2022.03.07.483337v3</p>
An individual-based model trained on multiple data sources estimates population connectivity and facilitates aggregation of harvest management units
Open the record for dataset details and reuse information.
Code and data from: Measuring the overall functional diversity by aggregating its multiple facets: functional richness, biomass evenness, trait evenness, and dispersion
Open the record for dataset details and reuse information.
Sediment accumulation rate data aggregated from publications describing research conducted in South Florida on coastal wetlands prior to 2022
Wetland sediment accumulation rate data were harvested from publications describing research conducted in the Southeast Saline Everglades, Northeast Florida Bay, the Lower Florida Keys, Southwest Everglades National Park, Ten Thousand Island National Wildlife Refuge, and Rookery Bay National Estuarine Research Reserve. The data were organized into three categories based on the method by which they were calculated: lump sum, core section interval, Sediment Elevation Table Marker Horizon. The data were assembled by Dr. Randall W. Parkinson as part of his research on the resiliency of coastal wetlands to accelerating sea-level rise.
DATA SET FOR PUBLICATION: Structure Determination of Hen Egg-White Lysozyme Aggregates Adsorbed to Lipid/Water and Air/Water Interfaces
<p>The data set collected for the publication: "Structure Determination of Hen Egg-White Lysozyme Aggregates Adsorbed to Lipid/Water and Air/Water Interfaces" (<a href="https://doi.org/10.1021/acs.langmuir.9b03826">https://doi.org/10.1021/acs.langmuir.9b03826</a>).</p>
Data from: Attack and aggregation of a major squash pest: parsing the role of plant chemistry and beetle pheromones across spatial scales
<p>1. Successful management of insect crop pests requires an understanding of the cues and spatial scales at which they function to affect rates of attack of preferred and non-preferred host plants. A long-standing conceptual framework in insect-plant ecology posits that there is hierarchical structure spanning host location, acceptance, and attack that could be exploited for integrated pest management.</p> <p>2. We investigated how plant- and insect-derived chemical cues affect successive decisions of host choice in aggregating insects, and tested predictions in the Cucurbita pepo - Acalymma vittatum system. Acalymma vittatum is an aggregating specialist beetle pest that strongly prefers zucchini (C. p. pepo) to summer squash (C. p. ovifera), two independent domesticates of C. pepo. We hypothesized that subspecies-specific plant traits, especially volatile cues, interact with the male-produced aggregation pheromone to amplify beetle preference for C. p. pepo.</p> <p>3. Differential beetle attack of C. pepo subspecies in the field is not determined by plant traits that affect host finding or differential aggregation due to pheromones: across two years, beetles had strong density-dependent attraction to both subspecies when male beetles were feeding, and no interactions between plant volatiles and the male-produced pheromone were detected. In absence of male pheromone emission, beetles were equally unattracted to plants with or without beetle feeding.</p> <p>4. In contrast, plant traits that mediate insect acceptance appear to underlie differences in preference. At a local scale, beetles did not accept and emigrated from C. p. ovifera compared to C. p. pepo. Distinct volatile emissions were observed between subspecies, but further work is needed to identify if these volatiles promote emigration.</p> <p>5. Synthesis and applications: By dissecting pest preference during successive host choice decisions, we isolated a trait with implications for pest management. Beetles on cucurbits can be managed by employing cultivars with differential susceptibility (e.g. trap cropping), and the mechanistic knowledge presented here informs best practices and limitations for on-farm applications. More broadly, pest management in diversified cropping systems can be enhanced through understanding how plant preference gradients affect herbivore movement and behavior, and plant breeders can target traits to reduce herbivory in such systems.</p>
Anonymized and aggregated temporal data on the number of research papers coauthored by Slovenian researchers
<p>The dataset includes: raw aggregated Slovenian researcher network data (available at http:((www.sicris.si), Benford law distribution conformity tests. Scripts for handling the data and Benford conformity tests.</p>
Monthly aggregated climate projections of IPSL-CM5A-LR ISIMIP2a fasttrack data for the BES SIM study
<p>Climate projections used in the BES SIM study (Pereira et al. Science 2024). Netcdf files with average air surface temperature (tas) projections, minimum air surface temperature (tasmin), maximum air surface temperature (tasmax), total precipitation (pr), short wave downwelling radiation (rsds) and number of days with a precipitation above 1.0mm/day (wetday) bias corrected following Hempel et al. (2013), from ISIMIP2a fasttrack, for the model IPSL-CM5A-LR for each RCP scenario, with each file being named after the respective scenario (RCP2.6, RCP6.0, RCP8.5). Monthly means (monmean) or sums (monsum) are provided in a 0.5-degree horizontal resolution from the year 1901 to 2099.</p>
[Raw data collection] - Granular skeleton optimisation and influence of the cement paste content in bio-based oyster shell mortar with 100% aggregate replacement
<h1>Raw data collection</h1> <h2>Associated paper information</h2> <p>- Year: 2024 <br>- Journal: Sustainability <br>- DOI/link: https://doi.org/10.3390/su16062297 <br>- Title: Granular skeleton optimisation and influence of the cement paste content in bio-based oyster shell mortar with 100% aggregate replacement <br>- Authors: Ana Cláudia Pinto Dabés Guimarães (1,2), Olivier Nouailletas (3), Céline Perlot (2,3,4) and David Grégoire (1,3,4,*) <br>- Affiliation: <br> (1) Universite de Pau et des Pays de l’Adour, E2S UPPA, CNRS, LFCR, Anglet, France, <br> (2) Universite de Pau et des Pays de l’Adour, E2S UPPA, SIAME, Anglet, France, <br> (3) Universite de Pau et des Pays de l’Adour, E2S UPPA, ISA BTP, Anglet, France, <br> (4) Institut Universitaire de France, Paris, France, <br> * Correspondence: david.gregoire@univ-pau.fr</p>
Data for the research article "High-Temperature Deformation of Enstatite-Olivine Aggregates" published in JGR Solid Earth
<p>The data available in this repository is the original data presented in the research article: Bystricky, M., Lawlis, J., Mackwell, S., & Heidelbach, F. (2024). High-temperature deformation of enstatite-olivine aggregates, Journal of Geophysical Research: Solid Earth, 129, e2023JB027699. https://doi.org/10.1029/2023JB027699.</p> <p>Version v1: data at time of original submission (2023)</p> <p>Version v2: data at time of publication (2024)</p>
Source data for Chen et al (2024) entitled "Motor Cortical Neuronal Hyperexcitability Associated with α-Synuclein Aggregation"
<div> </div> <div>--------------------</div> <div>GENERAL INFORMATION </div> <div>--------------------</div> <div>This readme file was generated on [2024-01-15] by [Liqiang Chen].</div> <div> </div> <div>Title of Dataset:</div> <div>Description of Dataset: </div> <div>Principal Investigator: Hong-Yuan Chu, hc948@georgetown.edu, ORCID: 0000-0003-0923-683X. </div> <div>Date of Data Collection: 2023-04-01 to 2024-11-10 </div> <div>Software Dependencies: Excel and Image J.</div> <div> </div> <div>-------------</div> <div>FILE OVERVIEW </div> <div>-------------</div> <div>Directory of Files: Source data, Electrophysiology trace data, and Microscopy images.</div> <div>Relationship Between Files: Source data is used to make figures in GraphPad. Electrophysiology trace data is used to plot electrophysiology traces. Microscopy images are used for representative images. </div> <div>File Formats: Microsoft Excel Worksheet (.xlsx) and confocal images (.nd2)</div> <div>File Naming Convention: Based on file formats.</div> <div> </div> <div>----------------------------------------</div> <div>DATA SPECIFIC INFORMATION FOR [Source data]</div> <div>Date of Creation: 2024-08-13</div> <div>Description of Data: Source data is used to make figures in GraphPad.</div> <div>A. Missing data are represented n/a.</div> <div>B. Abbreviations (Primary cortex: M1; Secondary cortex: M2; α-Synulein: αSyn; intratelencephalic neurons: ITNs; corticospinal neurons: CSNs).</div> <div>C. Figure 5B data (ITN-Sholl analysis-Intersections-5 µm Radius) can not organized as tidy format because of too many data points in each group. </div> <div> </div> <div>DATA SPECIFIC INFORMATION FOR [Electrophysiology trace data]</div> <div>Date of Creation: 2024-08-13</div> <div>Description of Data: Electrophysiology trace data is used to plot electrophysiology traces.</div> <div>A. Electrophysiology traces can be plotted using Excel.</div> <div>B. Traces are plotted in Electrophysiology trace data file.</div> <div> </div> <div>DATA SPECIFIC INFORMATION FOR [Microscopy images]</div> <div>Date of Creation: 2024-08-13</div> <div>Description of Data: Microscopy images are used to make representative images. </div> <div>A. Microscopy images can be opened using Image J. </div> <div>B. Microscopy images are named based on experimental group, animal ID, and figure number in the manuscript. </div> <div> </div> <div> </div> <div>-----------</div> <div>METHODOLOGY</div> <div>-----------</div> <div>Description of methods used for data collection: Electrophysiology data is collected using MultiClamp 700B amplifier and Digidata 1550B. pClamp 11 software is used. Microscopy images are collected using an confocal microscope. </div> <div> </div> <div>Description of methods used for data processing: </div> <div>A. Electrophysiology data is processed using clampfit software, including measure the peak of EPSC, count the number of action potentials, measure the width/rise time/decay time of action potential.</div> <div>B. Microscopy images are processed using Image J software, including measure the α-Synulein pathologic area in motor cortex, quantify the TH staining, and verify the co-localization of pS129 and biocytin. </div> <div>C. All data after processed through clampfit and Image J is put into GraphPad to make figures.</div> <div> </div> <div>-----------------------</div> <div>DATA ACCESS AND SHARING</div> <div>-----------------------</div> <div>This research was funded in part by </div> <div>1. Aligning Science Across Parkinson’s (ASAP-020572) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF).</div> <div>2. National Institute of Neurological Disorders and Stroke (R01NS121374).</div> <div>3. Congressionally Directed Medical Research Programs (W81XWH-21-1-0943).</div> <p> </p>
A data repository for the study of Alpha-synuclein aggregates trigger anti-viral immune pathways and RNA editing in human astrocytes
<p><span>This repository contains data associated with the study:</span></p> <p><span><strong>"Alpha-synuclein Aggregates Trigger Anti-Viral Immune Pathways and RNA Editing in Human Astrocytes"</strong></span></p> <p><span>Published as a <strong>bioRxiv preprint</strong>: <a href="https://doi.org/10.1101/2024.02.26.582055"><span>DOI: 10.1101/2024.02.26.582055</span></a></span></p>
Additional data repository for the study of Alpha-synuclein aggregates trigger anti-viral immune pathways and RNA editing in human astrocytes
<p>Zip file 1: astrocytes calcium data measured using Fura 2</p> <p>Zip file2: astrocytes ROS measured using DHE (Dihydroethidium)</p> <p>Zip file 3: astrocytes cell death measured using Sytox green</p>
Data used in JAMES paper "Sensitivity of the Horizontal Scale of Convective Self‐Aggregation to Sea Surface Temperature in Radiative Convective Equilibrium Experiments Using a Global Nonhydrostatic Model"
<p>Data used in JAMES paper "Sensitivity of the Horizontal Scale of Convective Self‐Aggregation to Sea Surface Temperature in Radiative Convective Equilibrium Experiments Using a Global Nonhydrostatic Model" by Shuhei Matsugishi and Masaki Satoh doi: 10.1029/2021MS002636</p>
Data and code for Host and pathogen drivers of infection-induced changes in social aggregation behavior
<p>Raw data and R code </p> <p>DistanceInds.xlsx contains pairwise distances between pairs of flies, measured within groups of 12 every 30 mins for 4 hours post-infection with one of four bacterial pathogens, at either a low or high dose. </p> <p>NND-Boyle.csv contains nearest-neighbor distances between pairs of flies, measured within groups of 12 following infections with Pseudomonas entomophila. </p>
Data for "Predicting aggregate morphology of sequence-defined macromolecules with Recurrent Neural Networks"
<p>These are the data associated with the paper, "Predicting aggregate morphology of sequence-defined macromolecules with Recurrent Neural Networks" (DOI 10.1039/D2SM00452F). Three of the directories contains subdirectories with `GSD` files dumped from HOOMD. The other contains pretrained RNN models as TorchScript binaries exported from PyTorch.</p>
A Global Gridded Municipal Water Withdrawal Estimation Method Using Aggregated Data and Artificial Neural Network
<p>Global gridded municipal water withdrawal estimations for the following WST paper.</p> <p>Jiabao Yan, Shaofeng Jia; A global gridded municipal water withdrawal estimation method using aggregated data and artificial neural network. <em>Water Science Technology</em>, 2023; 87 (1): 251–274. <a href="https://doi.org/10.2166/wst.2022.399" target="_blank" rel="noopener">https://doi.org/10.2166/wst.2022.399</a></p> <p>The representative year of the data is 2015, and the unit of the data is in millimeters (mm).</p>
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.