Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
29,897
datasets available to search
ShareScore release 0.9.0
Dataset results
29,897 results for “activism”
Quantitative Assessments of the Liquefaction Hazard of Soils considering Possible Strong Earthquakes in Seismically Active Regions of Russia
<p>Initial data for RESEARCH ARTICLE "Quantitative Assessments of the Liquefaction Hazard of Soils considering Possible Strong Earthquakes in Seismically Active Regions of Russia "</p>
Data for the publication "Measurement report: The ice-nucleating activity of lichen sampled in a northern European boreal forest"
<p>This repository contains the data and plotting scripts for the paper:</p> <p>Authors: Ulrike Proske, Michael P. Adams, Grace C. E. Porter, Mark Holden, Jaana Bäck, and Benjamin J. Murray</p> <p>Titel: Measurement report: The ice-nucleating activity of lichen sampled in a northern European boreal forest</p> <p>Date: 2024</p>
Phytochemical Screening and Microbial Activity of Essential Oil from Aerial Parts of Murraya paniculata (L.) Orange Jasmine
<p>Phytochemical Screening and Microbial Activity of Essential Oil from <br>Aerial Parts of Murraya paniculata (L.) Orange Jasmine </p>
scRNA-seq dataset from "Glucose deprivation and identification of TXNIP as an immunometabolic modulator of T cell activation in cancer"
<p>Gene expression profiling analysis of single cell RNA-seq data from MLR, anti-CD3/anti-CD28 treated and paired untreated CD4+ T cells samples under high glucose (11 mM) and low glucose (1 mM) conditions.</p> <p>For each sample, cells suspensions in culture medium were recovered, washed once with 0.04% BSA in 1X PBS and processed through 10x Cell Multiplexing Oligo Labeling protocol (10x Genomics, USA) according to the manufacturer’s instructions. ~1,600 cells/µl pooled cell suspensions were prepared with equal number of cells per sample: one for MLR samples, one for non-stimulated T cells samples, and one for anti-CD3/anti-CD28-stimulated T cells samples. Libraries were prepared using the 10x Chromium Single-Cell 3’ v3.1 protocol with Feature Barcode (10x Genomics, USA), according to the manufacturer’s instructions. Sequencing was performed on a NovaSeq 6000 sequencer (Illumina, USA).</p> <p>Cell Ranger (v6.0.1, 10x Genomics Inc) was applied for demultiplexing, reads mapping against the GRCh38 human reference genome, and UMI counting. Seurat package (v4.4.0) was used to generate Seurat objects. Only genes detected in at least 3 cells were kept. Cells with fewer than 200 genes detected or >15% mitochondrial UMI counts were filtered out. Samples were merged in a unique Seurat object then count data normalization and scaling was performed using Seurat with default parameters. The 2000 most highly variable genes were used for Principal Component Analysis (PCA). Harmony (v0.1.1) was applied for batch effect correction then Uniform Manifold Approximation and Projection (UMAP) and clustering using the Louvain algorithm were performed on the harmony reduction. Non-T or -MoDC clusters were removed for further analysis.</p>
No evidence that visual impulses enhance the readout of retrieved long-term memory contents from EEG activity
<p>This is the EEG and behavioral data for the long-term memory ping study by Sander van Bree, Abbie Sarah Mackenzie, and Maria Wimber.</p> <p>Paper title: No evidence that visual impulses enhance the readout of retrieved long-term memory contents from EEG activity</p> <p>The behavioral data is named "behav_res_pp", which is the output of script 1 (s0_extractdata.m) on Github. The EEG data is named "pp_reorder" and it is the output of script 5 (s5_correctdata.m); i.e., it is both preprocessed and correctly formatted for the main analyses.</p> <p>Move the behavioral data to folder /data/behav_data/ and the EEG data to folder /data/eeg_data/</p> <p>For the analysis scripts and more information, check Github: https://github.com/sandervanbree/MemPing</p>
Figure 2 in Occurrence and temporal activity pattern of Burmese Red Serow (Capricornis rubidus, Bovidae) in Baraiyadhala National Park, Bangladesh: insights from a camera trapping study
Figure 2: Camera trapped photo of Red Serow from the study area. The top image depicts an adult and a juvenile, and the bottom image is of an adult male.
Figure 1 in Occurrence and temporal activity pattern of Burmese Red Serow (Capricornis rubidus, Bovidae) in Baraiyadhala National Park, Bangladesh: insights from a camera trapping study
Figure 1: Study area and camera trap sites, indicating camera trap sites with Burmese Red Serow detection and sites where serows were not detected.
Figure 1 in Notes on the ecology, activity patterns and behavior of the kinkajou (Potos flavus)
Figure 1: Localities where we studied kinkajous in Ecuador and Colombia. Tiputiní Biodiversity Station (TBS) in the Ecuadorian Amazon (red circle), San Juan del Carare in the Magdalena River valley in Colombia (blue circle) and Pijao in the Central Andean Mountains of Colombia (yellow circle).
Figure 3 in Notes on the ecology, activity patterns and behavior of the kinkajou (Potos flavus)
Figure 3: (A) Activity budget for the population of kinkajous from Pijao. (B) Activity budget for the population of kinkajous from San Juan.
Figure 2 in Notes on the ecology, activity patterns and behavior of the kinkajou (Potos flavus)
Figure 2: Activity patterns of kinkajous from 95 independent records of camera traps at Tiputini Biodiversity Station (TBS). The height of the bars represents the frequency of the registers throughout the day.
Single-molecule analysis of transcription activation: dynamics of SAGA co-activator recruitment
<p>Source data for:</p> <p><strong>Single-molecule analysis of transcription activation: dynamics of SAGA co-activator recruitment</strong></p> <p><strong> </strong></p> <p>Jongcheol Jeon<sup>1</sup>, Larry J. Friedman<sup>2</sup>, Daniel H. Zhou<sup>2</sup>, Hogyu David Seo<sup>1</sup>, Oluwatobi A. Adeleke<sup>3</sup>, Bria Graham<sup>3</sup>, Emily F. Patteson<sup>3</sup>, Jeff Gelles<sup>2</sup>*, and Stephen Buratowski<sup>1,</sup>*</p> <p> </p> <p><sup>1</sup>Department of Biological Chemistry and Molecular Pharmacology,</p> <p>Harvard Medical School, Boston, MA 02115</p> <p><sup>2</sup> Department of Biochemistry, Brandeis University, Waltham, MA 02454</p> <p><sup>3</sup> EpiCypher Inc., Durham NC 27709</p> <p> </p> <p>*Corresponding authors</p> <p>Lead author contact information:</p> <p><a href="mailto:steveb@hms.harvard.edu">steveb@hms.harvard.edu</a></p> <p> </p> <p> </p> <p>The source data for the single molecule experiments are provided as "intervals" files and "CoSMoS parameters", which can be read and manipulated using the publicly available programs "Imscroll" and "Tapqir", respectively:</p> <p><a href="https://github.com/gelles-brandeis/CoSMoS_Analysis">https://github.com/gelles-brandeis/CoSMoS_Analysis</a></p> <p><a href="https://github.com/gelles-brandeis/tapqir">https://github.com/gelles-brandeis/tapqir</a></p>
Active fluctuations of axoneme oscillations scale with number of dynein motors
<p> </p> <p>The dataset published here was used to measure the<strong> phase fluctuations</strong> <strong>(frequency jitter) </strong>of isolated and <strong>reactivated axonemes from <em>Chlamydomonas reinhardtii </em></strong>as a function of the dynein motor density in these axonemes. <br>The corresponding article is published in PNAS: https://doi.org/10.1073/pnas.2406244121</p> <p>Axonemes were isolated from wt(cc-125) and oda1(cc-2228) cells.</p> <p>Reactivation was performed:<br>(1) after dynein extraction with different amounts of salt (KCL) or<br>(2) in the presence of different concentrations of ATP .</p> <p>For all experimental conditions we provide the following data files:<br><br></p> <p><strong>Movies of reactivated axonemes:</strong></p> <p>Reactivated axonemes were imaged with phase-contrast microscopy. Recorded movies are organized in folders (.zip) which are labeled according to the respective reactivation condition (KCL and ATP concentration as well as the <em>Chlamydomonas</em> strain, from which the axonemes were purified, e.g. <strong>50mM_KCl_750uM_ATP_ODA_Extracted.zip</strong>).</p> <p>Those folders contain (1) movie files (multilayer .tif) of single axonemes and (.txt) files with a corresponding number-label (with microscope, camera settings and experimental condition (<em>Chlamydomonas</em> strain, [ATP], [KCL]).</p> <p>Using the number-label, the corresponding data file can be identified. <br><br></p> <p><strong>Data files (for the corresponding movies):</strong></p> <p>The experimental data is organized in MATLAB (.mat) files. Those files contain shape and waveform information (see below) for the respective reactivation condition (axoneme type, [ATP], [KCL] detailed below the file name).</p> <p><strong>WT_KCL_master.mat</strong> - WT axonemes, KCL extracted and reactivated with 750uM ATP</p> <p><strong>0mM_KCl_750uM_ATP_WT_Extracted<br>50mM_KCl_750uM_ATP_WT_Extracted<br>100mM_KCl_750uM_ATP_WT_Extracted<br>200mM_KCl_750uM_ATP_WT_Extracted<br>300mM_KCl_750uM_ATP_WT_Extracted<br>400mM_KCl_750uM_ATP_WT_Extracted<br></strong></p> <p><strong>WT_ATP_master.mat </strong> - WT axonemes reactivated with different ATP concentraions</p> <p><strong>0mM_KCl_50uM_ATP_WT<br>0mM_KCl_100uM_ATP_WT<br>0mM_KCl_370uM_ATP_WT<br>0mM_KCl_500uM_ATP_WT<br>0mM_KCl_750uM_ATP_WT<br></strong></p> <p><strong>ODA_KCL_master.mat </strong>- ODA axonemes, KCL extracted and reactivated with 750uM ATP</p> <p><strong>0mM_KCl_750uM_ATP_ODA_Extracted<br>50mM_KCl_750uM_ATP_ODA_Extracted<br>100mM_KCl_750uM_ATP_ODA_Extracted<br>200mM_KCl_750uM_ATP_ODA_Extracted<br>300mM_KCl_750uM_ATP_ODA_Extracted<br></strong></p> <p><strong>ODA_ATP_master.mat</strong> - ODA axonemes reactivated with different ATP concentraions</p> <p><strong>0mM_KCl_70uM_ATP_ODA<br>0mM_KCl_100uM_ATP_ODA<br>0mM_KCl_370uM_ATP_ODA<br>0mM_KCl_500uM_ATP_ODA<br>0mM_KCl_750uM_ATP_ODA</strong></p> <p>Each file includes a data-cell ‘Master’ with a columns for the different experimental conditions (e.g. concentrations of ATP or KCL). Data-cells contain one structure for each axoneme. </p> <p> </p> <p>These structures have the following fields:</p> <p>nframe… number of frames of the dataset</p> <p>phi_in_rad… phase angle (beat-cycle-phase) (rad)</p> <p>tangent_angle_psi_in_rad… the tangent angle for 24 positions along arc-length (rad)</p> <p>xy_in_micron… the x,y positions (µm)</p> <p>dt_in_second… time between adjacent frames (second)</p> <p>ds_in_micron… spacing between adjacent arc-length positions (µm)</p> <p>f0_in_Hz… beat frequency (Hz)</p> <p>A… beat amplitude (arc-length average) (rad)</p> <p>Q… quality factor</p> <p>sexp… string with experiment label</p> <p>KCL_in_mM… KCL concentration (mM) used for dynein extraction</p> <p>ATP_in_uM… ATP concentration (mM) used for reactivation</p> <p>File… filename, includes a number-label that corresponds to the imaging data provided</p>
Ciência Vitae controlled vocabulary - Type of activity
Open the record for dataset details and reuse information.
Morphology rather than surface tension determines CCN activity of submicron inorganic salt/organic oxidized sulfur mixed particles
<p>The measurement data. </p>
Figure 3 in Occurrence and temporal activity pattern of Burmese Red Serow (Capricornis rubidus, Bovidae) in Baraiyadhala National Park, Bangladesh: insights from a camera trapping study
Figure 3: Temporal activity pattern and overlap estimates for focal species Burmese Red Serow and sympatric Barking Deer and Wild Boar.
Research Data for "Electronic structure and stability of the active surface phase of NixCo3-xO4 spinel alkaline O2 evolution electrocatalysts: from an epitaxial model catalyst perspective"
<p>These datasets support main text and supplementary figures and tables of the paper "Electronic structure and stability of the active surface phase of NixCo3-xO4 spinel alkaline O2 evolution electrocatalysts: from an epitaxial model catalyst perspective" appearing in <em>ACS Applied Energy Materials </em>under DOI: <a href="https://doi.org/10.1021/acsaem.4c01688">https://doi.org/10.1021/acsaem.4c01688 </a></p>
Data described in the article "Design and evaluation of composite films for in situ synthesis and antibacterial activity of allicin vapour"
Open the record for dataset details and reuse information.
Active Regions of Secondary Ice Production in a Modeled Tropical Mesoscale Convective System
<p>The animations of the modeled tropical mesoscale convective system (MCS). The red regions indicate the cloud regions with the secondary ice production rate dNice/dt >10<sup>5</sup> m<sup>-3</sup> s<sup>-1</sup>. The numerical simulation of the MCS was performed with the help of the Environment and Climate Change Canada's (ECCC) Global Environmental Multiscale (GEM) model.</p> <p>For details see Korolev, A., Z. Qu, J. Milbrandt, I. Heckman, M. Cholette, M. Wolde, C. Nguyen, G. M. McFarquhar, P. Lawson, and A. M. Fridlind: High ice water content in tropical mesoscale convective systems (a conceptual model). Atmos. Chem. Phys., 2024.</p>
Raw data related to KIF1C activates and extends dynein movement through the FHF cargo adaptor
Open the record for dataset details and reuse information.
Neuromorphic-enabled video-activated cell sorting
Open the record for dataset details and reuse information.
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.