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Academic Data and Datasets
by Nadja Grammes
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PLSDB files from 2019.06.05
Source: https://figshare.com/articles/dataset/PLSDB_2019_06_05/9959750/1
Academic Data and Datasets
by Sanjna Banerjee; Shrey Grover; Suhas Ganesh; Devarajan Sridharan
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Supplemental data and raw data sources for Banerjee, Grover, Ganesh and Sridharan, J. Neurophys. (2019)
Source: https://figshare.com/articles/dataset/Supplemental_Data_Banerjee_Grover_Ganesh_and_Sridharan_J_Neurophys_2019_/9751766/1
Academic Data and Datasets
by Mario Looso
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Output folder of TOBIAS software (https://github.com/loosolab/TOBIAS/), applied to Hendrikson et al. 2017 dataset
Source: https://figshare.com/articles/dataset/bias_correction_zip/9975926/1
Academic Data and Datasets
by Tannaz Pak; Nathaly Lopes Archilha; Iara Frangiotti Mantovani; Anderson Camargo Moreira; Ian B. Butler
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Segmented oil phase for image: WI-Filtered Segmentation performed using Watershed segmentation in Avizo. Image Dimension: 1024×1024×845 Image Type: 8 bit
Source: https://springernature.figshare.com/articles/dataset/WI-Segmented-Oil/6959327/1
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat NDVI difference 1990 2018 Tile 6
Source: https://springernature.figshare.com/articles/dataset/Landsat_NDVI_difference_1990_2018_Tile_6/7767695/1
Academic Data and Datasets
by Tony Alfredo Stabile; Claudia Mascandola; Marco Massa; Sara Amoroso; Deborah Di Naccio; Salomon Hailemikael; Lucia Luzi; Daniela Famiani; Fabrizio Cara; Giovanna Cultrera; Gaetano Riccio; Paola Bordoni; Augusto Bucci; Alessia Mercuri; Giuliano Milana; Marta Pischiutta; Luciana Cantore; Giuseppe Di Giulio; Maurizio Vassallo; Rocco Cogliano; Antonio Fodarella; Stefania Pucillo; Maria D'Amico; Simona Carannante; Chiara Felicetta; Gianlorenzo Franceschina; Giovanni Lanzano; Sara Lovati; Francesca...
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Seismic traces in binary MiniSeed format recorded by station MZ27. The daily records are separated in folders representing the channels: EHE.D, EHN.D, EHZ.D for the velocimetric data and HNE.D, HNN.D and HNZ.D for the accelerometric data. Both velocimetric and accelerometric data are available from October 10, 2016 to November 22, 2016.
Source: https://springernature.figshare.com/articles/dataset/Seismic_traces_recorded_by_station_MZ27/7803164/1
Academic Data and Datasets
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Last of four zipfiles providing all data and Python code necessary to replicate any of the 13 development potential indexes (DPIs) described within Oakleaf et al. (2019), “Mapping global development potential for renewable energy, fossil fuels, mining and agriculture sectors”. A README.pdf guides users on setting up environment necessary to use data and run Python code. To run Python code with accompanying spatial data, 64 GBs of disk space is required. Additionally ArcPY, a python module...
Source: https://springernature.figshare.com/articles/dataset/Spatial_Data_and_Python_Code_for_13_Development_Potential_Indices_part_04_/7890935/1
Academic Data and Datasets
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In this study, Beijing, the capital of China, is selected as the study area. Hourly mean concentrations of six regulatory air pollutants including O3 (μg/m3), SO2 (μg/m3), NO2 (μg/m3), PM2.5 (μg/m3), PM10 (μg/m3), and CO (mg/m3) were collected from 35 air quality monitoring stations labeled by 1 to 35 from 01/01/2017 to 05/30/2018. The data was provided by the Ministry of Environmental Protection (MEP) of China. Hourly averaged meteorological data in the same period were first accessed...
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/USXCAK&version=1.0
Academic Data and Datasets
by Rahul Rao Madarapu
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Bike ride data of a month
Source: https://figshare.com/articles/dataset/two_json/10277954/1
Academic Data and Datasets
by Han, Xueyuan
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Preprocessed edgelist data of ta1-fivedirections-e3-official. CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/NVQFY0&version=1.0
Academic Data and Datasets
by Martin Jinye Zhang
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Toy data for the diversity score analysis in Tabula Muris Senis
Source: https://figshare.com/articles/dataset/Diversity_score_toy_data/11340128/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02095. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02095/7927067/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19359. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19359/7928666/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19795. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19795/7932278/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA21144. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA21144/7951910/1
Academic Data and Datasets
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Data files for four species. Each species has 9 data files (3 niche model approaches X 3 RCPs). Each individual file has lat/lon gridded projection output for 5 future time periods during the 21st century, for each of 18 Earth system climate models. This is provided for both a probability of occurrence based niche model and a delta biomass approach (separate files for each). NOTE: this data set pertains to a manuscript that is presently in review (as of June 2019). Contact...
Source: https://figshare.com/articles/dataset/Projection_uncertainty_ensemble_members_Morley_et_al_2019/8256815/1
Academic Data and Datasets
by Johannes Abeler
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Merged data set of all raw data of the meta study
Source: https://figshare.com/articles/dataset/truth_telling_meta_study_merged_data_csv/8850767/1
Optotrak recordings of Fitts task paradigm as presented in Valk et al. (2019) 'During rhythmic pointing, joint-angles are temporary linked in different synergies with similar relative joint-angle coupling across task constraints'
Source: https://figshare.com/articles/dataset/Dataset_During_rhythmic_pointing_joint-angles_are_temporary_linked_in_different_synergies_with_similar_relative_joint-angle_coupling_across_task_constraints_/8280893/1
Academic Data and Datasets
by Ben Dichter; Edward F Chang
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The enclosed data is collected using a high-density 256-channel electrocorticography array implanted in a human patient during treatment for epilepsy. The subjects are reading aloud consonant-vowel syllables from a list. The data was collected by Dr. Edward Chang at the University of California, San Francisco, and curated by Ben Dichter. Data is organized by subject ID, and each file is a continuous recording session in Neurodata Without Borders: Neurophysiology (NWB:N) 2.0 format. Voltage...
Source: https://figshare.com/articles/dataset/EC9_B46_nwb/9631880/1
Academic Data and Datasets
by Michael Lee
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https://astrobiomike.github.io/amplicon/dada2_workflow_ex
Source: https://figshare.com/articles/dataset/dada2_amplicon_ex_workflow_tar_gz/6225761/3
Academic Data and Datasets
by Andrea Capiluppi
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These are the raw java classes of the projects parsed off SourceForge. The projects are categorised by application domain
Source: https://figshare.com/articles/dataset/raw_data_Java_source_code_for_MSR_data_track_2019/7673264/1
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3319012
Academic Data and Datasets
by Tony Chu; Kidder, Larry; Pfeiffer, Harald; Scheel, Mark; Boyle, Michael; Hemberger, Dan; Lovelace, Geoffrey; Szilagyi, Bela
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3274549
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3273341
Academic Data and Datasets
by Jonathan Blackman; SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3272877
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3307711
Academic Data and Datasets
by Shunliu Zhao; Matthew G. Russell; Amir Hakami; Shannon L. Capps; Matthew D. Turner; Daven K. Henze; Peter B. Percell; Jaroslav Resler; Huizhong Shen; Armistead G. Russell; Athanasios Nenes; Amanda J. Pappin; Sergey L. Napelenok; Jesse O. Bash; Kathleen M. Fahey; Gregory R. Carmichael; Charles O. Stanier; Tianfeng Chai
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The data set that is used for testing the adjoint model.
Source: https://zenodo.org/record/3473444
Academic Data and Datasets
by Kevin Barkett; SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3303728
Dioxin response elements were computationally identified and matrix similarity scores estimated as previously described (PMIDs: 15328365, 21762485, and 26582802) CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JASCVZ&version=1.0
Academic Data and Datasets
by Stephan Rasp
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Sample data
Source: https://figshare.com/articles/dataset/WB_Sample_Data/11370675/2
Academic Data and Datasets
by Dalberg
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The State of Aadhaar survey is the largest primary dataset collected on digital identity, globally. The dataset contains; 1. Household and member-level data collected for the in-depth and pulse survey 2. R codes used for analysis and visualisations 3. Additional spatial and meta data required for analysis and visuals The data, and all materials, are shared under Creative Commons Attribution 4.0 International license (CC-BY 4.0). You are free to: Share — copy and redistribute the material in...
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/M9RWZN&version=1.1
Academic Data and Datasets
by SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3303264
Academic Data and Datasets
by Matt Giesler; SXS Collaboration
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Simulation of a black-hole binary system evolved by the SpEC code .
Source: https://zenodo.org/record/3307421
Academic Data and Datasets
by Raphaël Nussbaumer; Lionel Benoit; Grégoire Mariethoz; Felix Liechti; Silke Bauer; Baptiste Schmid
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This dataset contains the interpolated values of bird density and bird flight speed (N-S and E-W) resulting from the methodology presented in [reference].The methodology is explained in less detail at  rafnuss-postdoc.github.io/BMM . The resulting interpolation is a probability distribution (define the probability of each value to occurs). Only the median, quantile 10 and 90 are given in this file.  The spatio-temporal grid has a resolution of 0.2° in latitude (43°-68°) and longitude...
Source: https://zenodo.org/record/3243466
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat based peak NDVI image Year 1997 Tile 14
Source: https://springernature.figshare.com/articles/dataset/Landsat_based_peak_NDVI_image_Year_1997_Tile_14/7769753/1
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat based peak NDVI image Year 2018 Tile 13
Source: https://springernature.figshare.com/articles/dataset/Landsat_based_peak_NDVI_image_Year_2018_Tile_13/7769732/1
Academic Data and Datasets
by Janet Loebach; Kate Tilleczek; Brent Chaisson; Brian Sharp
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The Young Lives Research Laboratory is concerned with the lives of modern youth from education to technology to mental health. Technology is ubiquitous in the day to day lives of young people in Canada but little is known about the ways in which digital media affects their mental health, especially for Indigenous youth. Research seldom engages youth to clarify and or interrogate digital media and well-being. This paper addresses the dearth of empirical work and supports the development of...
Source: https://tandf.figshare.com/articles/dataset/_i_Keyboard_warriors_i_Visualising_technology_and_well-being_i_with_for_i_and_i_by_i_indigenous_youth_through_digital_stories/11106794/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG00097.
Source: https://figshare.com/articles/dataset/gVCF_HG00097/7841411/1
Academic Data and Datasets
by Andrew D. Richardson; David Y. Hollinger; Julie Shoemaker; Holly Hughes; Kathleen Savage; Eric A. Davidson
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Carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) are the greenhouse gases largely responsible for anthropogenic climate change. Natural plant and microbial metabolic processes play a major role in the global atmospheric budget of each. We have been studying ecosystem-atmosphere trace gas exchange at a sub-boreal forest in the northeastern United States for over two decades. Historically our emphasis was on turbulent fluxes of CO 2 and water vapor. In 2012 we embarked on an...
Source: https://figshare.com/articles/dataset/Tower-_and_chamber-based_greenhouse_gas_flux_measurements_from_Howland_Forest_Maine_2012-2018_/7445657/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA18864. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA18864/7890737/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01624. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01624/7895774/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03452. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03452/7901339/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01950. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01950/7911317/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03558. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03558/7907651/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19185. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19185/7927103/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19475. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19475/7929941/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03812. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03812/7928066/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02286. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02286/7928966/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03874. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03874/7928795/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02561. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02561/7931462/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02554. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02554/7931255/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA18504. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA18504/7944293/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA20786. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA20786/7944296/1
Academic Data and Datasets
by Soon-Chun Jeong; Myung-Shin Kim; Ji Hong Kim; Youn Young Hur
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Candidate SNP variants detected by analysis of genome resequencing data from 33 grape accessions
Source: https://figshare.com/articles/dataset/33Grapes_Total_SNP_final_chr06_vcf_gz/8116106/1
Academic Data and Datasets
by Hacking Materials
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Matbench v0.1 test dataset for predicting DFT PBE band gap from structure. Adapted from Materials Project database. Removed entries having a formation energy (or energy above the convex hull) more than 150meV and those containing noble gases. Retrieved April 2, 2019.
Source: https://figshare.com/articles/dataset/mp_gap/9461444/1
Academic Data and Datasets
by Musfiqur Rahman
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English - code parallel corpus from StackOverflow
Source: https://figshare.com/articles/dataset/SOParallelData_zip/7673927/1
Academic Data and Datasets
by figshare admin cellimagelibrary
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Single computed slice through a tomographic reconstruction of a protoplasmic astrocyte in a 0.5 um thick section from the hippocampus of a 1 month old male mouse, imaged with intermediate voltage electron microscopy. This reconstruction is the 14th in a series of 26 serial reconstructions through the cell soma. The complete reconstruction can be viewed under MP7503.
Source: https://cellimagelibrary.figshare.com/articles/dataset/CCDB_6727_jpg/8179529/1
Academic Data and Datasets
by Aydin Ayanzadeh; Özden Yalçın Özuysal; Devrim Pesen Okvur; Behçet Uğur Töreyin; Devrim Ünay; Sevgi Önal
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Phase contrast Microscopy
Source: https://figshare.com/articles/dataset/Phase_Contrast_Microscopy_of_cells_with_annotation/8965820/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG00154.
Source: https://figshare.com/articles/dataset/gVCF_HG00154/7872560/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19663. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19663/7930124/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03792. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03792/7927244/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA19467. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA19467/7929692/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02661. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02661/7934975/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG02793. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG02793/7940702/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA11931. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA11931/7936667/1
Academic Data and Datasets
by Raphael Neukom; Luis A. Barboza; Michael P. Erb; Feng Shi; Julien Emile-geay; Michael N. Evans; Jörg Franke; Darrell S. Kaufman; Lucie Lücke; Kira Rehfeld; Andrew Schurer; Feng Zhu; Stefan Brönnimann; Gregory J. Hakim; Benjamin J. Henley; Fredrik Charpentier Ljungqvist; Nicholas Mckay; Veronika Valler; Lucien von Gunten
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Input data for the reconstructions and required datasets and code to generate the figures in the paper. Proxy data used for the reconstructions: proxy_ama_2.0.0_PAGES-crit-regional+FDR.txt: PAGES2k v2.0.0 proxy records, R-FDR screened subset (See PAGES2k Consortium, 2017, Scientific Data, doi: 10.1038/sdata.2017.88). Data are tab separated, the first column is the "paleoData_TSid" to identify each record in the metadata file. First row is year CE....
Source: https://figshare.com/articles/dataset/input_data_zip/8137715/3
Academic Data and Datasets
by Steven Peterson
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High-density EEG data recorded during tandem standing and tandem walking at 0.22 m/s. Data includes selected neural independent components, along with EMG from 8 lower leg muscles (4 on each leg). Subjects were exposed to 20 degree visual field rotations in virtual reality (SVZ and WVZ events) and brief mediolateral pull perturbations (Stand_Pull and Walk_Pull events). Each subject has approximately 150 of each event type for both physical conditions (walking and standing). Both EEG.data and...
Source: https://figshare.com/articles/dataset/EEG_connectivity_data_Walk_Pull_/8165747/1
Academic Data and Datasets
by Niklas König Ignasiak; Deepak K Ravi; Stefan Orter; Seyyed Hamed Hosseini Nasab; William R Taylor; Navrag Singh
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Gait variability is a sensitive metric for assessing functional deficits in individuals with mobility impairments. To correctly represent the temporal evolution of gait kinematics, nonlinear measures require extended and uninterrupted time series. The full-body gait patterns of twenty healthy subjects were captured during five walking trials (at least 5 minutes) on a treadmill under different weight perturbation conditions with both weight reductions (of 40 and 20% using a harness labelled...
Source: https://figshare.com/articles/dataset/Does_variability_of_footfall_kinematics_correlate_with_dynamic_stability_of_the_centre_of_mass_during_walking_/8153819/3
Academic Data and Datasets
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Assembled transcriptome, and predicted non-redundant proteins it encodes, for the choanoflagellate Choanoeca flexa.
Source: https://figshare.com/articles/dataset/Choanoeca_flexa_nonredundant_predicted_proteins_fasta/8216291/2
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01113. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01113/7883471/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01204. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01204/7885034/1
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat based peak NDVI image Year 2012 Tile 10
Source: https://springernature.figshare.com/articles/dataset/Landsat_based_peak_NDVI_image_Year_2012_Tile_10/7769879/2
Academic Data and Datasets
by James Watson; Oscar Venter; Andrew Hansen; MC Hansen; Kevin Barnett; Linda Phillips; Patrick Jantz; Patrick Burns; Scott Aktinson; Susana Rodríguez-Buritica; Jamison Ervin; Anne Virnig; Scott Goetz; Christina Supples
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GeoTIFF representing canopy cover for the moist broadleaf biome of the humid tropics in South America. Derived from remotely sensed imagery, this layer is used as an input into the forest structural condition index
Source: https://springernature.figshare.com/articles/dataset/Canopy_Cover_-_South_America/8411858/1
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat based peak NDVI image Year 2015 Tile 12
Source: https://springernature.figshare.com/articles/dataset/Landsat_based_peak_NDVI_image_Year_2015_Tile_12/7769633/2
Academic Data and Datasets
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Basal neoceratopsians are a relatively diverse group of small- to medium-sized herbivorous dinosaurs from the Early to Late Cretaceous of Asia and North America. Although known for over a century, this group has only relatively recently received intense independent study, tied to the rapid increase in known diversity since 1997. Auroraceratops rugosus is one of these recently discovered species and is one of the best-known basal neoceratopsians, being represented by over 80 specimens, and is...
Source: https://tandf.figshare.com/articles/dataset/Phylogenetic_history_of_i_Auroraceratops_rugosus_i_Ceratopsia_Ornithischia_from_the_Lower_Cretaceous_of_Gansu_Province_China/8798480/1
Academic Data and Datasets
by Cefan Zhou; Xuehong Qian; Miao Hu; Rui Zhang; Nanxi Liu; Yuan Huang; Jing Yang; Juan Zhang; Hua Bai; Yuyan Yang; Yefu Wang; Declan Ali; Marek Michalak; Xing-Zhen Chen; Jingfeng Tang
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Macroautophagy/autophagy plays key roles in development, oncogenesis, and cardiovascular and metabolic diseases. Autophagy-specific class III phosphatidylinositol 3-kinase complex I (PtdIns3K-C1) is essential for autophagosome formation. However, the regulation of this complex formation requires further investigation. Here, we discovered that STYK1 (serine/threonine/tyrosine kinase 1), a member of the receptor tyrosine kinases (RTKs) family, is a new upstream regulator of autophagy. We...
Source: https://tandf.figshare.com/articles/dataset/STYK1_promotes_autophagy_through_enhancing_the_assembly_of_autophagy-specific_class_III_phosphatidylinositol_3-kinase_complex_I/10265156/1
Genome alignments for data generated in the project " Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol – Optimization of the protocol. " Files names indicate unique identifiers of MOIRAI workflow runs, with the following structure: library name, dot, workflow ID (OP-WORKFLOW-CAGEscan-short-reads-v2.0.), dot, timestamp. The raw (FASTQ) data of each library is also deposited in Zenodo ( 10.5281/zenodo.250156 ). Library names...
Source: https://zenodo.org/record/3340196
Academic Data and Datasets
by Peter Vogt; Kurt H. Riitters; Giovanni Caudullo; Bernd Eckhardt
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This document summarizes the design process, definitions, and algorithmic implementation conducted by the Joint Research Centre to support the development and implementation of FAO’s global forest analysis for the thematic topics Accounting and Fragmentation. The analysis scheme and data products were designed to support the indicator Forest Fragmentation in the State of the World's Forests (SOFO) report 2020. The spatial forest coverage is derived from the Copernicus Global Land Cover 2015...
Source: https://figshare.com/articles/dataset/FAO_gez19_zip/11113325/1
Data sets generated in the study "Social calls of Myotis nattereri during swarming" CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/AHIWQA&version=2.0
Academic Data and Datasets
by Simon Porter; Jared Watts
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Network data for What does NZ research look like
Source: https://figshare.com/articles/dataset/grid_414055_1/10022990/1
Academic Data and Datasets
by figshare admin cellimagelibrary
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Single computed slice through a tomographic reconstruction of a protoplasmic astrocyte in a 0.5 um thick section from the hippocampus of a 1 month old male mouse, imaged with intermediate voltage electron microscopy. This reconstruction is the 22nd in a series of 26 serial reconstructions through the cell soma. The complete reconstruction can be viewed under MP7503.
Source: https://cellimagelibrary.figshare.com/articles/dataset/CCDB_6736_jpg/8184362/1
Academic Data and Datasets
by Abel Gomes
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Gaussian Finder's cavity dataset in CSV. This dataset describes the protein cavities output by a protein cavity detection method called Gaussian Finder. This method is described in the article available at: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1913-4
Source: https://figshare.com/articles/dataset/Gaussian_Finder_s_cavity_dataset_in_CSV/9916745/1
Academic Data and Datasets
by Benedikt Geier
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CLSM of the main dataset "MPIMM_054_QE_P_BP_CF" apllying FISH after AP-MALDI-MSI and after widefield fluorescence overviews were made
Source: https://figshare.com/articles/dataset/CLSM_of_FISH_sample/6887315/2
Academic Data and Datasets
by emmanuel levy; Benjamin Dubreuil
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Supplementary Dataset from the work "Rules of amino acid composition by which disordered regions adjust to high expression". This table contains amino-acid level information of human proteins.
Source: https://figshare.com/articles/dataset/Dataset_2_2_Human_amino-acids_raw_data/8058854/1
The data and programs replicate tables and figures from "From Hyperinflation to Stable Prices: Argentina's Evidence on Menu Cost Models", by Alvarez, Beraja, Gonzalez-Rozada, and Neumeyer. Please see the Readme file for additional details. CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/C8ZOAS&version=2.2
Academic Data and Datasets
by tw70455@gmail.com tw70455@gmail.com
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For the paper 'Spontaneous thought-related network connectivity predicts sertraline effect on major depressive disorder'
Source: https://figshare.com/articles/dataset/sertraline_effect_on_major_depressive_disorder/8135552/1
Academic Data and Datasets
by Katarina Kleinova
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The CT data of Zootoca vivipara NHMW 32438-1 from Čerňanský and Syromyatnikova Plos One. It can by open by winrar and volume graphics.
Source: https://figshare.com/articles/dataset/Cernansky_and_Syromyatnikova_Zootoca_vivipara_NHMW_32438-1/8396822/1
Academic Data and Datasets
by Michael Lee
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angus 2019 genomes from metagenomes
Source: https://figshare.com/articles/dataset/angus_2019_genomes_from_metagenomes/8863388/1
Academic Data and Datasets
by Hyung Rae Cho; Saehoon Kim
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This file contains the EEG raw data of 14 participants in the laboratory experiment and of 89 participants in the fieldwork in Nangok-dong. As stated in the manuscript, this EEG dataset was analysed to investigated valence values that show positive/negative emotions. This data was analysed by MATLAB and EEGLAB. The EEG raw data of 10 participants in the fieldwork were removed in the final analysis due to the issue of poor connection between laptop and EEG device.
Source: https://figshare.com/articles/dataset/EEG_raw_data_zip/9958946/1
Academic Data and Datasets
by Bolivar Samuel Sosa Madrid; agustin blasco; noelia ibañez escriche
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Genomic Data from divergently selected lines for intramuscular fat in rabbits. This database was used for the analyses of the article titled: "Genomic regions influencing intramuscular fat in divergently selected rabbit lines." Animal Genetics - Journal, accepted in 2019.
Source: https://figshare.com/articles/dataset/Genomic_Data_from_divergently_selected_lines_for_intramuscular_fat_in_rabbits/9934058/2
This dataset contains data files and identifiers for original data sources for 39 gene expression datasets from over 7,000 individuals with estrogen receptor positive (ER-positive) Breast Cancer (BC). Background The related study developed a novel in silico approach to assess activation of different signalling pathways. The phosphatidylinositol 3-kinase (PI3K)/AKT/mTOR signalling pathway mediates key cellular functions, including growth, proliferation and survival and is frequently involved in...
Source: https://springernature.figshare.com/articles/dataset/Gene_expression_data_sources_for_in_silico_approach_to_assessing_activation_of_AKT_mTOR_signalling_pathway_in_ER-positive_early_Breast_Cancer/7461776/1
Academic Data and Datasets
by Jiapeng Qu; Fabian Ewald fassnacht; Christopher Schiller; Teja Kattenborn; Xinquan Zhao
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Landsat based peak NDVI image Year 1993 Tile 14
Source: https://springernature.figshare.com/articles/dataset/Landsat_based_peak_NDVI_image_Year_1993_Tile_14/7769750/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for NA18951. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_NA18951/7892684/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG03095. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG03095/7890959/1
Academic Data and Datasets
by Jonathan Pevsner
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1000 Genomes gVCF mapped to hs37d5 for HG01682. Complete collection: https://doi.org/10.6084/m9.figshare.c.4414307
Source: https://figshare.com/articles/dataset/gVCF_HG01682/7897922/1
Replication Data for: "Nonparametric Welfare and Demand Analysis with Unobserved Individual Heterogeneity" CC0 Waiver
Source: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/SDUGGM&version=1.2
Academic Data and Datasets
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The dataset contains genotype (tped and tfam files) and phenotype data GWAS analyses on canine hip dysplasia. See README file for more information.
Source: https://figshare.com/articles/dataset/Genetic_dissection_of_canine_hip_dysplasia_phenotypes_and_osteoarthritis_reveals_three_novel_loci/10096595/1
Academic Data and Datasets
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Filtered genotype calls from high coverage sequencing data of Alca Tarma (LOP-868), IVP101, PL4, and three selected dihaploids
Source: https://figshare.com/articles/dataset/Dataset_S3_tsv_Genomic_outcomes_of_haploid_induction_crosses_in_potato/10052357/1
Academic Data and Datasets
by Raymond Haggerty
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Contains all the input and output files used to generate figure 4 IN_[stress].mat are the input files for each stress (glucose, H2O2, KCl) OUT_[stress].mat are the output files run through MISC corresponding to each of the input files.
Source: https://figshare.com/articles/dataset/Figure_4_Reproduction_Files/11383662/1
Academic Data and Datasets
by Antonis Michalas
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Text files of different size and structure. More precisely, we selected random data from the Gutenberg dataset. This artefact contains five different datasets with random text files (i.e. e-books in .txt format) from the Gutenberg database. The datasets that we selected ranged from text files with a total size of 184MB to a set of text files with a total size of 1.7GB. More precisely, the following datasets can be found in this package: 1. 184MB 2. 357MB 3. 670MB 4. 1GB 5. 1.7GB In our case, we...
Source: https://zenodo.org/record/3360392