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2,326 results for “clusters”
Dynamical friction and measurements of the splashback radius in galaxy clusters (Data)
<p>Data from O'Shea et al. (2024). Dynamical friction and measurements of the splashback radius in galaxy clusters.</p>
MoSn_n clusters
<p>XYZ files containing the structures of MoSn_n clusters computed using the PBE and TPSSh functionals in combination with the Def2-TZVP basis sets. </p>
Role of net charges and charge clustering in a dynamic disordered complex between an IDP and a folded domain.
<p>Simulation input files and trajectories for the paper "Role of net charges and charge clustering in a dynamic disordered complex between an IDP and a folded domain". </p> <p>Files here:</p> <p>cg_prota_multigd.tgz -- coarse-grained simulations of prothymosin alpha with multiple globular domains</p> <p>gd_prota_cg_umbrella.tgz -- coarse grained umbrella sampling simulations of prothymosin alpha associating with a single globular domain</p> <p>prota_aa.tgz -- all-atom simulations in explicit water of prothymosin alpha alone, with several force fields</p> <p>gd_amber03ws.tgz -- all-atom simulations in explicit water of globular domain alone, with amber ff03ws force field</p> <p>gd_des-amber.tgz-- all-atom simulations in explicit water of globular domain alone, with des-amber force field</p> <p>prota+gd_des-amber-SF1.0.tgz -- all-atom simulations in explicit water of prothymosin alpha + single globular domain, des-amber-SF1.0 force field</p> <p>prota+gd_des-amber.tgz-- all-atom simulations in explicit water of prothymosin alpha + single globular domain, des-amber force field</p> <p>prota+gd_amber_ff99sbws.tgz -- all-atom simulations in explicit water of prothymosin alpha + single globular domain, amber ff99sbws force field</p> <p>prota+gd_amber_ff99sb-disp.tgz -- all-atom simulations in explicit water of prothymosin alpha + single globular domain, amber ff99sb-disp force field</p> <p>prota+gd_amber_ff03ws.tgz -- all-atom simulations in explicit water of prothymosin alpha + single globular domain, amber ff03ws force field</p> <p> </p>
MESA Inlists for: Barium Surface Abundances of Blue Straggler Stars in the Open Clusters NGC 7789 and M67
<p>These are the MESA v15140 inlists and Python script associated with the models presented in Nine et al. (2024). The files are as follows:</p> <p>inlist, inlist_start_header, inlist_to_end_core_h_burn_header, inlist_to_start_he_core_flash_header, inlist_to_end_core_he_burn_header, inlist_to_end_agb_header, inlist_to_wd_header: Pointer files to tell MESA which inlists to read for control, kappa, and PGStar commands.</p> <p>inlist_start, inlist_to_end_core_h_burn, inlist_to_start_he_core_flash, inlist_to_end_core_he_burn, inlist_to_end_agb, inlist_to_wd: MESA inlist files with control, kappa, and PGStar commands for each stage.</p> <p>turnoff_masses.py: a Python script that takes in the file inlist_start_base and rewrites it to create a starting model with the mass of a turnoff star in NGC 7789 (1.8 solar masses), NGC 6819 (1.5 solar masses), M67 (1.3 solar masses), and NGC 188 (1.1 solar masses). This starting model is then used in the following inlists to create AGB star models with these masses.</p> <p>inlist_start_base: The base starting inlist that turnoff_masses.py reads in and alters to create inlist_start.</p>
The clustering of Lyman Alpha Emitting galaxies at z=2-3
<p>Contains supporting data from the clustering analysis of LAEs within the COSMOS field.</p>
The valence electron affinity of uracil determined by anion cluster photoelectron spectroscopy
<p>Connor J. Clarke, E. Michi Burrow, Jan R. R. Verlet</p> <p> </p>
Atom-by-atom design of Cu/ZrOx clusters on MgO for CO2 hydrogenation using liquid-phase atomic layer deposition
<p>Source data for the following publication: </p> <p><strong>Atom-by-atom design of Cu/ZrOx cluster on MgO for CO2 hydrogenation using liquid-phase atomic layer deposition,<em> Nature Catalysis</em>, 2024.</strong></p>
Deep Clustering Representation for Spatially Resolved Transcriptomics Data via Multi-view Variational Graph Auto-Encoders with Consensus Clustering
Open the record for dataset details and reuse information.
Modis and GA 7.0 Cluster Analysis Results
<p>Data output associated<strong><em> </em></strong>with Schuddeboom et al. 2018.</p>
Exploring Clustering Techniques for Effective Reinforcement Learning based Personalization for Health and Wellbeing/Database 1
<p>The first Dataset of the five runs done. If you would like to have access to any or all of the others please send an e-mail to the authors.</p>
Properties of negative initial leaders and flash size in a cluster of supercells
<p>The data is associated with the paper titled "Properties of negative initial leaders and flash size in a cluster of supercells" . The abstract is as follows:</p> <p>Properties of negative initial leaders (NILs) and flash size in a cluster of supercells with generally inverted charge structure in Oklahoma on 10−11 May 2010 are examined, primarily using Lightning Mapping Array data. A method to identify NILs from LMA source is proposed. Median values of 18.00 ms, 1.02 km, 0.65 × 10<sup>5</sup> m s<sup>−1</sup>, and 47.24° are found for NIL duration, three-dimensional (3D) displacement, 3D displacement speed, and the angle between the displacement and the vertical directions, respectively. Median NIL speeds initially decrease with increasing height, but begin increasing above 12 km, possibly related to the rapid reduction in air density. The NILs tend to decelerate during the early stage, particularly during the first 6 ms. The NILs in small-size charge regions tend to have low speeds, vice versa. The flash duration, horizontal distance, vertical distance, flash area and flash volume have median values of 0.27 s, 5.54 km, 3.67 km, 9.67 km<sup>2</sup>, and 14.37 km<sup>3</sup>, respectively. All parameters follow lognormal distributions. Most flashes (83.18%) extend primarily in the horizontal direction. Flash area shows an inverse relationship with flash density at their fast changes during storm evolution. Although large flash initiation density (FID) generally occurs in regions with small flash size, the smallest flash size is not collocated with large FID value. Flash duration changes independently of flash area in regions with large FID. A hypothesis is proposed to explain the observations in this study on the correlations among dynamic process, flash activity, flash size, and flash duration.</p>
Changes in School-day Step Counts during a Physical Activity for Lent Intervention: A Cluster Randomized Crossover Trial of the Savior's Sandals
<p>Excel data file of 187 participants in a Physical Activity for Lent program conducted in spring 2017 at 4 Catholic middle schools in San Diego, CA, USA. Includes daily physical activity step counts and questionnaire data for religiosity, physical activity enjoyment, and situational interest motivation.</p>
Unsupervised Acoustic Segmentation and Clustering using Siamese Network Embeddings
<p>The spoken term discovery system outputs and evaluations for track 2 on Zero Speech 2017. </p>
Research Data Supporting "Diagrammatic Coupled Cluster Monte Carlo"
<p>Research data supporting "Diagrammatic Coupled Cluster Monte Carlo". Includes all inputs and outputs for diagrammatic and unlinked Coupled Cluster Monte Carlo simulations on systems of noninteracting Neon and Beryllium replicas, and the separation of the Helium pentamer. This dataset also includes all code used to generate diagCCMC results and to analyse and plot all data. Unlinked CCMC calculations were performed using the open-source HANDE QMC package (http://www.hande.org.uk/).</p>
Supplementary materials for the spatial clustering of Europe
<p>This repository includes:</p> <p>- Three raster files (load density distribution, wind full-load hours, solar full-load hours) for Europe</p> <p>- Three shapefiles (results of the clustering)</p> <p>- Eight input files for the urbs model (2015 and 2050).</p> <p>To use the open-source model generator urbs, visit: https://github.com/tum-ens/urbs</p> <p>The three raster files can be used as inputs for the clustering script: https://github.com/tum-ens/geoclustering</p>
A Reportage about the Research Cluster: The Past for the Present, 2018
<p>The cluster <strong>The Past for the Present – International Research and Educational Programme</strong> has been established by the Faculty of “Artes Liberales” of the University of Warsaw, Fakultät für Sprach- und Literaturwissenschaften of the Ludwig-Maximilians-Universität München, and Dipartimento di Storia Culture Civiltà and Dipartimento di Filologia Classica e Italianistica of the Università di Bologna. We aim at developing the studies into the ancient tradition as a marker of transformations underway across the world. A collaboration with schools and dissemination of research results are very important to us. We wish to acknowledge the projects <em><strong>Our Mythical Childhood</strong></em> (ERC Consolidator Grant) and <strong><em>Chasing Mythical Beasts</em></strong> (Alexander von Humboldt Foundation Alumni Award) in the developement of our endeavours. This short reportage presents the main ideas of our work.</p> <p>Video by Krzysztof Korwin-Piotrowski, idea and scholarly supervision by Katarzyna Marciniak, English proofreading by Elżbieta Olechowska. </p> <p>The movie is available also here: <a href="https://www.youtube.com/watch?v=HfypV5PUMUc&t=1s">https://www.youtube.com/watch?v=HfypV5PUMUc&t=1s</a>. </p>
Data accompanying "An empirical pipeline for choosing the optimal clustering threshold in RADseq studies"
<p>Data files accompanying "An empirical pipeline for choosing the optimal clustering threshold in RADseq studies"</p>
Structural files of algorithmically generated molybdenum oxide clusters
<p>Structural files of algorithmically generated molybdenum oxide clusters. The new clusters were generated to fit experimental pair distribution functions of molybdenum oxide surface layers supported on Al<sub>2</sub>O<sub>3 </sub>and zeolites. Results are published in article XXX</p>
Fig. 6 in Reclustering the cluster flies (Diptera: Oestroidea, Polleniidae)
Fig. 6. Morinia tsitsikamma sp.n. (A) Sternite 5, male paratype 05390; (B) hypandrium in dorsal view, male paratype 05390; (C, D) phallic complex in lateral view, male paratype 05390 (scale, 200 μm); (E, F) phallic complex in dorsal view, male paratype 05390 (scale, 200 μm); (G) apical portion of oviscapt. ap, phallic apodeme; ep, epiphallus; hya, hypandrial arm; pdp, phallic dorsolateral process; pr, pregonite; ps, postgonite. [Colour figure can be viewed at wileyonlinelibrary.com].
Fig. 7 in Reclustering the cluster flies (Diptera: Oestroidea, Polleniidae)
Fig. 7. Alvamaja chlorometallica Rognes, female. (A) Habitus in lateral view; (B) abdomen in dorsal view; (C, D) oviscapt in dorsal view: (C) posterior tip of tergite 6, tergites 7 and 8, epiproct and cerci; (D) detail of tergite 8, epiproct and cerci; (E) tip of oviscapt in left lateral view. T, tergite. [Colour figure can be viewed at wileyonlinelibrary.com].
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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.