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608
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ShareScore release 0.9.0
Dataset results
608 results for “ensembles”
Ensemble averaged signals from the light scattering signals of individual suspension droplets.
<p>The ensemble-averaged light scattering signals were constructed from 1000 individual light scattering signals published on https://doi.org/10.5281/zenodo.6614871</p> <p>The light scattering of the droplets on a Gaussian beam are measured using a commercial device SpraySpy PL100 from AOM-Systems GmbH. It has one laser source with a wavelength of 405nm along with two detectors placed around and named here as A and B. This laser source as well as the two detectors are pointed towards the droplet chain, which is created by a commercial monodisperse droplet generator from FMP Technology GmbH.</p> <p>The detectors, in the form of photo multipliers, aim to track and capture light scattered from the droplets passed through the Gaussian beam. The light scattering signal is subsequently converted into a voltage signal by a transimpedance amplifier. The measuring signal is digitized by a digital oscilloscope PicoScope 6404B. The signal consists of 32 measurement frames with an individual duration of 20ms sampled by 312.5MS/s. Each frame contains about 1000 individual light scattering signals. Since there are two independent detectors with one signal generated by each, there are also two active channels in the measurement on the oscilloscope named correspondingly Channel A and Channel B.</p> <p>In total, measurements are conducted for a concentration range of 0 to 100%. From 0 to 25% a measurement step amounts to 1\% (1%, 2%...,25%) while from 25 to 100\% a measurement step amounts to 2.5%, rounded up to 3% (25%, 28%, 30%...100%).</p>
Computer-Aided diagnostic for classifying Chest X-Ray Images Using Deep Ensemble Learning
<p>Both healthy and tuberculosis images are from "Tuberculosis (TB) Chest X-Ray Database'' collected by researchers from Qatar and Dhaka University, Doha, Qatar, and collaboration with doctors from Hamad Medical Corporation and Bangladesh. All the images are CRX in PNG format and a size 512x512. </p> <p>The COVID and Pneumonia images are also from a Kaggle dataset: "COVID-19 Radiography Database'' , which collects images from different sources. This dataset was collected by the same researchers as the "Tuberculosis (TB) Chest X-Ray Database''. All the images in this database are CRX in PNG format and a size 256X256.</p>
Dataset The MLL1 trimeric catalytic complex is a dynamic conformational ensemble stabilized by multiple weak interactions and is susceptible to pharmacological disruption
<p>This dataset is related to <strong>"</strong>MLL1 minimal catalytic complex is a dynamic conformational ensemble susceptible to pharmacological allosteric disruption<strong>" </strong>(Lilia Kaustov, Alexander Lemak, Hong Wu, Marco Faini, Lixin Fan, Xianyang Fang, Hong Zeng, Shili Duan, Abdellah Allali-Hassani, Yong Wei, Masoud Vedadi, Ruedi Aebersold, Yunxing Wang, Scott Houliston, Cheryl H. Arrowsmith) . </p> <p>The repository contains the data used in the modeling of WDR5-RbBP5-MLL1 trimeric complex, the optimal ensemble of models, and the representative models for major and minor populations. The modeling is performed based on saxs and cross-link MS data, crystallographic structures, and comparative models using coarse-grained MD simulations and Sparse Ensemble Selection method (SES) for optimal ensemble selection.</p>
Disconnected vector loop g-2 HISQ coarse physical ensemble
<ul> <li>Disconnecected vector loop operators for the g-2 project.</li> <li>The symmetric and isospin broken correlators can be computed from this data set.</li> <li>They were generated on HPC resources at Cambridge and Durham using a modified version of the MILC code.</li> <li>The is coarse physical ensemble. l4864f211b600m001907m05252m6382</li> <li>The file Coarse_g-2ttim.pdf contains some information about the conventions</li> </ul> <p>WARNING</p> <ul> <li>The second set of loops for the noise sources 128 to 256 were the same as 1 to 128 were identical for streams e and f.</li> </ul>
Direct RNA sequencing and signal alignment reveal RNA structure ensembles in a eukaryotic cell [RNA004]
GEO Series GSE304703. synthetic construct. 4 samples. Type: Other.
Direct RNA sequencing and signal alignment reveal RNA structure ensembles in a eukaryotic cell [nanopore_DRS]
GEO Series GSE304702. Candida albicans; synthetic construct. 35 samples. Type: Other.
Direct RNA sequencing and signal alignment reveal RNA structure ensembles in a eukaryotic cell
GEO Series GSE309111. synthetic construct. 8 samples. Type: Other.
Supporting data case study, ensemble climate-impact modelling
<p>Data supporting the case study in 'Ensemble climate-impact modelling: extreme impacts from moderate meteorological conditions', publication under review.</p>
Replication Package for the Paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions"
<p>This is the replication package for the paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions". It contains the source code and dataset of our experiment for the replication by other researchers. In the meanwhile, we provide brief description of the files in the replication package in the following.</p> <p><strong>1. code folder</strong></p> <ul> <li><em>experiment.py </em>contains the source code for our experiment, which is conducted on Windows 10 and Python 3.7.0. <strong>Note that you may get slightly</strong> <strong>different experiment results when conducting the experiments on different environment configurations.</strong></li> <li><em>requirements.txt</em> records all the installation packages and their version numbers needed for the current program to run. You can use "<em>pip install -r requirements.txt</em>" to rebuild the project and install all dependencies. <strong>Note that you may get slightly different experiment results when using different packages or versions. </strong></li> </ul> <p><strong>2. dataset folder</strong></p> <ul> <li><em>decisions.xlsx </em>contains 848 labelled sentence-level decisions from the Hibernate developer mailing list.</li> </ul>
Replication Package for the Paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List"
<p>This is the replication package for the paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List". It contains the source code and dataset of our experiment for the replication by other researchers. In the meanwhile, we provide brief description of the files in the replication package below.</p> <p><strong>1. code folder</strong></p> <ul> <li><em>experiment.py </em>contains the source code for our experiment, which is conducted on Windows 10 and Python 3.7.0. <strong>Note that you may get slightly</strong> <strong>different experiment results when conducting the experiments on different environment configurations.</strong></li> <li><em>requirement.txt</em> records all the installation packages and their version numbers needed for the current program to run. You can use "<em>pip install -r requirement.txt</em>" to rebuild the project and install all dependencies. <strong>Note that you may get slightly different experiment results when using different packages or versions. </strong></li> </ul> <p><strong>2. dataset folder</strong></p> <ul> <li><em>decisions.xlsx </em>contains 844 labelled sentence-level decisions from the Hibernate developer mailing list.</li> </ul>
Causal Modeling Using Network Ensemble Simulations Predicts Novel Lipid Metabolism Genes
GEO Series GSE15226. Mus musculus. 120 samples. Type: Expression profiling by array.
MeteoSwiss ensemble weather forcing data (2019)
<p>MeteoSwiss CosmoE weather ensemble predictions for 2019, which were used for the calibration of the hydrodynamic model of Lake Geneva. The original dataset was modified to only contain the relevant pixels over the lake to reduce the total size of the dataset.</p>
High-resolution (3-km) ensemble WRF/WRF-Hydro simulation results for HRB, 2008-2011.
<p>The dataset stores the model results from the published paper of <a href="https://doi.org/10.1007/s00382-021-06044-9">https://doi.org/10.1007/s00382-021-06044-9</a>.</p> <p>It is used for personal archive of the simulation results.</p> <p>WRF and WRF-Hydro simulation with PBL schemes: YSU, MYJ, ACM2. </p> <p>With Tagging result, with 3D atmosphere variable for summer time.</p> <p>Calculated Water budgets in CSV. </p>
Data for the bachelor thesis "Investigating Tuning Parameters in ECHAM-HAM with a Perturbed Parameter Ensemble"
<p>This repository contains the data for the bachelor thesis:<br> <br> Author: Melina Abeling<br> Title: Investigating Tuning Parameters in ECHAM-HAM with a Perturbed Parameter Ensemble<br> Date: July 2022</p> <p><br> The scripts are to be found in the accompanying package (https://doi.org/10.5281/zenodo.6866140).</p>
Trained Artificial Neural Network for Detecting Cut-off low related Vb-Cyclones in a large single-model ensemble
<p>Trained network data accompanying the research letter "Detecting Climate Change Effects on Vb-Cyclones in a 50-Member Single-Model Ensemble Using Machine Learning" submitted to Geophysical Research Letters.</p> <p>Licence: Creative Commons Attribution-NonCommercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0)</p>
Hourly aerosol assimilation of Himawari-8 AOT using the four-dimensional local ensemble transform Kalman filter
<p>These data are simulated results used in the manuscript titled "Hourly aerosol assimilation of Himawari-8 AOT using the four-dimensional local ensemble transform Kalman filter" to Journal of Advances in Modeling Earth Systems. </p>
Phytochemicals from AYUSH-64 screened against main protease and spike protein of Omicron variant of SARS-CoV-2 using ensemble docking and molecular dynamics approach
<p>Data for "Phytochemicals from AYUSH-64 screened against main protease and spike protein of Omicron variant of SARS-CoV-2 using ensemble docking and molecular dynamics approach" </p>
Ensembl r88 Saccharomyces Cerevisia LinkSets v0.91
<p>Ensembl Saccharomyces Cerevisia LinkSets</p> <p> Gene - Transcript - Protein</p>
Ensembl Sus Scrofa Linkset
<p>Ensembl Sus Scrofa Linkset</p> <p> Gene - Transcript - Protein</p>
Ensembl r88 Saccharomyces Cerevisia LinkSets v0.90
<p>Ensembl Saccharomyces Cerevisia LinkSets</p> <p> Gene - Transcript - Protein</p>
ScienceDex guides
Understand access before you commit
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.