cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/phvx-z886
title: OTTQA V1.0

description: Question Answer Pair dataset for Sentiment Analysis Tasks.
DOI: 10.34740/kaggle/dsv/3790420
title: Simplified washers for anomaly detection
DOI: 10.17632/b2xdk4h5xm.1
title: An unconventional integrin 3 and CD103 heterodimer improves the anti-tumor immunity of tissue-resident T cells. Abd Hamid et al.

description: Paired CD103+ and CD103- SSX2-specific CD8 T cells and paired CD103+ and CD103- NYESO1-specific CD8 T cells were activated for 0, 3 or 6 hours with anti-CD3/CD28 stimulation. Cells were then lysed in 1% NP40 cell lysis buffer before proteins pelleted and snap freezes. Dried proteins were digested into peptide before analysed by liquid chromatography tandem mass spectrometry (LC-MS/MS) using Ultimate 3000 UHPLC (ThermoFisher Scientific) connected to an Orbitrap Fusion Lumos Tribrid (ThermoFisher Scientific).
DOI: 10.17632/3h9s9czs6h.1
title: Integrative machine-learning on high-throughput human data identifies age-specific hallmarks of Alzheimer’s disease

description: Alzheimer’s disease (AD) is an incredibly complex and presently incurable age-related brain disorder. To better understand this debilitating disease, we collated publicly available RNA-Seq, microarray, proteomics, and microRNA samples derived from AD patients and non-AD controls. 4089 samples originating from brain tissues and blood remained after applying quality filters. Since disease progression in AD correlates with age, we stratified this large dataset into three different age groups: < 75 years, 75-84 years, and ≥ 85 years. The RNA-Seq, microarray, and proteomics datasets were then combined into different integrated datasets. Ensemble machine learning was employed to identify genes and proteins that can accurately classify samples as either AD or control. These predictive inputs were then subjected to network-based enrichment analyses. The ability of genes/proteins associated with different pathways in the Molecular Signatures Database to diagnose AD was also tested. We separately identified microRNAs that can be used to make an AD diagnosis and subjected the predicted gene targets of the most predictive microRNAs to an enrichment analysis. The following key themes emerged from our machine learning and bioinformatics analyses: cell death, cellular senescence, energy metabolism, genomic integrity, glia, immune system, metal ion homeostasis, oxidative stress, proteostasis, and synaptic function. Many of the results also demonstrated unique age-specificity. For example, results highlighting cellular senescence only emerged in the earliest and intermediate age ranges while the majority of results relevant to cell death appeared in the youngest patients. These data demonstrate that, like aging, AD is a multifaceted process characterized by diverse dysfunction.  Please see paper for detailed methods.
DOI: 10.6084/m9.figshare.20057231
title: Data Repository - Infodemic and health misinformation - Bulletin of the World Health Organization

description: List of excluded studies
DOI: 10.3886/e123001v1-120560
title: National Neighborhood Data Archive (NaNDA): Grocery Stores by Census Tract, United States, 2003-2017

description: This dataset contains measures of the number and density of grocery stores – including supermarkets, specialty food stores, and warehouse clubs – per United States census tract from 2003 through 2017. These types of businesses represent places where neighborhood residents can obtain fresh and healthy foods.
description: Grocery stores in all census tracts in the United States, including Puerto Rico and the US Virgin Islands. Smallest Geographic Unit: census tract
DOI: 10.6084/m9.figshare.20055701
title: tracer uptake.xlsx

description: The proportion of tracer absorbed by soil depth for trees and grasses at four study sites that represent a factorial combination of mesic (~750 mm precipitation, sabie, pkop), xeric (~450 mm precipitation, letaba, pborwa), sand (pkop, pborwa), and clay (letaba, sabie) conditions. Deuterium was injected to five depths in each of four replicate plots, during early, mid and late season sampling in each of two growing seasons.
DOI: 10.6084/m9.figshare.20055701.v1
title: tracer uptake.xlsx

description: The proportion of tracer absorbed by soil depth for trees and grasses at four study sites that represent a factorial combination of mesic (~750 mm precipitation, sabie, pkop), xeric (~450 mm precipitation, letaba, pborwa), sand (pkop, pborwa), and clay (letaba, sabie) conditions. Deuterium was injected to five depths in each of four replicate plots, during early, mid and late season sampling in each of two growing seasons.
DOI: 10.6084/m9.figshare.20057234
title: Data for "Wettability impacts residual trapping of immiscible fluids during cyclic injection"

description: These data are simulation results of quasi-static cyclic injections using the interface tracking algorithm under different wettabilities (contact angles, CA). <br> 5 different realizations of porous media are simulated for each wetting condition, with 15 injection cycles each. <br> Both the .mat file (raw data that can be opened by MATLAB) and the corresponding image showing the residual liquid distribution are included. <br> Note that files with names "drainage" ALWAYS correspond to CO2 injection processes, whereas "imbibition" corresponds to water injection, although the wettability of the porous media can be either CO2-wet or water-wet. See the manuscript for more detail. <br> <br> <br>
DOI: 10.6084/m9.figshare.20057246
title: final iso summary

description: Deuterium and 18O concentrations relative to VSMOW for plants collected in plots where deuterium was injected into target soil depths. Values reported for four replicate plots for each target soil depth. Injections were performed in different plots for early, mid, late season sampling campaigns in each of two growing seasons. Sampling was performed in four different study sites within Kruger National Park. These sites represented a factorial combination of wet (750 mm precipitation, sabie, pkop), dry (450 mm precipitation, pborwa, letaba), sand (pkop, pborwa) and clay (sabie, letaba) conditions.
DOI: 10.6084/m9.figshare.20057246.v1
title: final iso summary

description: Deuterium and 18O concentrations relative to VSMOW for plants collected in plots where deuterium was injected into target soil depths. Values reported for four replicate plots for each target soil depth. Injections were performed in different plots for early, mid, late season sampling campaigns in each of two growing seasons. Sampling was performed in four different study sites within Kruger National Park. These sites represented a factorial combination of wet (750 mm precipitation, sabie, pkop), dry (450 mm precipitation, pborwa, letaba), sand (pkop, pborwa) and clay (sabie, letaba) conditions.
DOI: 10.6084/m9.figshare.20055704
title: water uptake.xlsx

description: Deuterium injections were used to describe the proportion of tree or grass roots with soil depth. These active root distributions were used with climate and soils data in the Hydrus 1D model to simulate water uptake by a theoretical plant canopy to estimate the effect of vertical root 'shape' on water uptake. Values represent the mm of soil water absorbed by tree or grass roots across two growing seasons. Data provided for four study sites in Kruger Park that represent a factorial combination of mesic (750 mm precipitation) and xeric (450 mm precipitation) savanna.
DOI: 10.6084/m9.figshare.20055704.v1
title: water uptake.xlsx

description: Deuterium injections were used to describe the proportion of tree or grass roots with soil depth. These active root distributions were used with climate and soils data in the Hydrus 1D model to simulate water uptake by a theoretical plant canopy to estimate the effect of vertical root 'shape' on water uptake. Values represent the mm of soil water absorbed by tree or grass roots across two growing seasons. Data provided for four study sites in Kruger Park that represent a factorial combination of mesic (750 mm precipitation) and xeric (450 mm precipitation) savanna.
DOI: 10.6084/m9.figshare.20057249
title: ANME-1 viruses and MGEs file version 1

description: All viral and MGE contigs used in the manuscript describing methanotrophic ANME-1 and their viruses
DOI: 10.6084/m9.figshare.20057249.v1
title: ANME-1 viruses and MGEs file version 1

description: All viral and MGE contigs used in the manuscript describing methanotrophic ANME-1 and their viruses
DOI: 10.6084/m9.figshare.20055695
title: water uptake ratio.xlsx

description: The ratio of water absorbed by a theoretical plant canopy with a tree rooting distribution or a grass rooting distribution. The ratio is the ratio of total water absorbed across three growing seasons. The ratio was calculated for soils where 10%, 50% or 90% of the roots in the soil had a 'tree-shaped' rooting distribution. Results are shown for four sites in Kruger National Park that represent a two-way factorial combination of mesic (750 mm precipitation), dry (450 mm precipitation), sand, or clay soil conditions.
DOI: 10.5281/zenodo.6636849
title: League of Legends KR High Elo 5v5 Match Data

description: League of Legends KR High Elo 5v5 Match Data Related project link: GitHub The dataset is retrieved using the Riot API. For documentation of the API please visit the website. The dataset contains information about all League of Legends KR server challengers (n=300) as of 2022-06-12. The account information is stored in<strong> accounts.json</strong>, whereas the information about the challenger league is in <strong>kr_challenger_league.json</strong>. Match data was retrieved from the 5 most recent 5v5 ranked solo matches for each challenger account. There are in total 2166 unique matches. The matches are further cleaned only to include games that last more than 16 minutes (n=2078), which are stored in <strong>matches.json.</strong>
DOI: 10.5281/zenodo.6582780
title: League of Legends KR High Elo 5v5 Match Data

description: League of Legends KR High Elo 5v5 Match Data Related project link: GitHub The dataset is retrieved using the Riot API. For documentation of the API please visit the website. The dataset contains information about all League of Legends KR server challengers (n=300) as of 2022-06-12. The account information is stored in<strong> accounts.json</strong>, whereas the information about the challenger league is in <strong>kr_challenger_league.json</strong>. Match data was retrieved from the 5 most recent 5v5 ranked solo matches for each challenger account. There are in total 2166 unique matches. The matches are further cleaned only to include games that last more than 16 minutes (n=2078), which are stored in <strong>matches.json.</strong>
DOI: 10.5517/ccdc.csd.cc25ysdb
title: CCDC 2024622: Experimental Crystal Structure Determination

description: Related Article: Ivanka Jeric|2020|CSD Communication|||
description: Related Article: Josipa Suć Sajko, Ivanka Jerić|2022|J.Org.Chem.|87|7076|doi:10.1021/acs.joc.2c00238
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5519/qd.jtjkau4k
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (217 records)
DOI: 10.5519/qd.tmjlobam
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (287 records)
DOI: 10.5519/qd.p4qt9qg0
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (46 records)
DOI: 10.5519/qd.soefldkd
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (15 records)
DOI: 10.5519/qd.gyhotfaz
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (69 records)
DOI: 10.5519/qd.b02dh5e6
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (158 records)
DOI: 10.5519/qd.fhpn4qug
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5519/qd.9g65rtfc
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (20 records)
DOI: 10.5519/qd.mtvhc65d
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (113 records)
DOI: 10.5519/qd.iq1nygtf
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (46 records)
DOI: 10.5519/qd.atdo9mse
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (181 records)
DOI: 10.5519/qd.49udy63n
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (28 records)
DOI: 10.34740/kaggle/dsv/3791215
title: BBC News
DOI: 10.34740/kaggle/dsv/3791298
title: Polish-Ukrainian translations from Tatoeba
DOI: 10.6084/m9.figshare.20057399.v1
title: Additional file 1 of A retrospective cohort study of the effect of SARS-CoV-2 point of care rapid RT-PCR at the Emergency Department on targeted admission

description: Additional file 1. Grouping of ICD-10 diagnosis on discharge from the ED and hospital wards into compound variables.
DOI: 10.6084/m9.figshare.20057399
title: Additional file 1 of A retrospective cohort study of the effect of SARS-CoV-2 point of care rapid RT-PCR at the Emergency Department on targeted admission

description: Additional file 1. Grouping of ICD-10 diagnosis on discharge from the ED and hospital wards into compound variables.
DOI: 10.6084/m9.figshare.20057400
title: Additional file 10 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 10: Skimmed data from DrugBank for the workflow.
DOI: 10.6084/m9.figshare.20057400.v1
title: Additional file 10 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 10: Skimmed data from DrugBank for the workflow.
DOI: 10.6084/m9.figshare.20057403
title: Additional file 11 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 11: Downloaded data from the SIGNOR database.
DOI: 10.6084/m9.figshare.20057403.v1
title: Additional file 11 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 11: Downloaded data from the SIGNOR database.
DOI: 10.6084/m9.figshare.20057412.v1
title: Additional file 2 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 2: CHEMBL mode of action annotation.
DOI: 10.6084/m9.figshare.20057412
title: Additional file 2 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 2: CHEMBL mode of action annotation.
DOI: 10.6084/m9.figshare.20057415
title: Additional file 3 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 3: IUPHAR mode of action annotation.
DOI: 10.6084/m9.figshare.20057415.v1
title: Additional file 3 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 3: IUPHAR mode of action annotation.
DOI: 10.6084/m9.figshare.20057418
title: Additional file 4 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 4: Full assay annotation with text mining based on ChEMBL data.
DOI: 10.6084/m9.figshare.20057421
title: Additional file 5 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 5: Exclusions for the text mining of assay data.
DOI: 10.6084/m9.figshare.20057418.v1
title: Additional file 4 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 4: Full assay annotation with text mining based on ChEMBL data.
DOI: 10.6084/m9.figshare.20057424
title: Additional file 6 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 6: ChEMBL identifiers of mostDILI compounds.
DOI: 10.6084/m9.figshare.20057427
title: Additional file 7 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 7: ChEMBL identifiers of noDILI compounds.
DOI: 10.6084/m9.figshare.20057421.v1
title: Additional file 5 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 5: Exclusions for the text mining of assay data.
DOI: 10.6084/m9.figshare.20057424.v1
title: Additional file 6 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 6: ChEMBL identifiers of mostDILI compounds.
DOI: 10.6084/m9.figshare.20057427.v1
title: Additional file 7 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 7: ChEMBL identifiers of noDILI compounds.
DOI: 10.6084/m9.figshare.20057430
title: Additional file 8 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 8: ChEMBL identifiers of cardiac therapy compounds.
DOI: 10.6084/m9.figshare.20057430.v1
title: Additional file 8 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 8: ChEMBL identifiers of cardiac therapy compounds.
DOI: 10.6084/m9.figshare.20057433
title: Additional file 9 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 9: ChEMBL identifiers of cardiotoxic compounds.
DOI: 10.6084/m9.figshare.20057433.v1
title: Additional file 9 of KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study

description: Additional file 9: ChEMBL identifiers of cardiotoxic compounds.
DOI: 10.5281/zenodo.6631159
title: WMT-SLT FocusNews: Training data for the WMT shared task on sign language translation

description: This is data from a former Deaf online TV channel, FocusFive. We provide news episodes (FocusNews) that were broadcast between 2008 and 2014. Each episode is about 5 minutes long. For a more extended description of the data, visit https://www.wmt-slt.com/data.
description: We additionally acknowledge funding through the Innosuisse Flagship "Inclusive Information and Communication Technologies" (IICT) (grant agreement no. PFFS-21-47).
DOI: 10.5281/zenodo.6621479
title: WMT-SLT FocusNews: Training data for the WMT shared task on sign language translation

description: This is data from a former Deaf online TV channel, FocusFive. We provide news episodes (FocusNews) that were broadcast between 2008 and 2014. Each episode is about 5 minutes long. For a more extended description of the data, visit https://www.wmt-slt.com/data.
description: We additionally acknowledge funding through the Innosuisse Flagship "Inclusive Information and Communication Technologies" (IICT) (grant agreement no. PFFS-21-47).
DOI: 10.5281/zenodo.6631275
title: WMT-SLT SRF: Training data for the WMT shared task on sign language translation (poses)

description: These are Standard German daily news (Tagesschau) and Swiss German weather forecast (Meteo) episodes broadcast and interpreted into Swiss German Sign Language by hearing interpreters (among them, children of Deaf adults, CODA) via Swiss National TV (Schweizerisches Radio und Fernsehen, SRF) (https://www.srf.ch/play/tv/sendung/tagesschau-in-gebaerdensprache?id=c40bed81-b150-0001-2b5a-1e90e100c1c0). For a more extended description of the data, visit https://www.wmt-slt.com/data.
description: We additionally acknowledge funding through the Innosuisse Flagship "Inclusive Information and Communication Technologies" (IICT) (grant agreement no. PFFS-21-47).
DOI: 10.5281/zenodo.6630144
title: WMT-SLT SRF: Training data for the WMT shared task on sign language translation (poses)

description: These are Standard German daily news (Tagesschau) and Swiss German weather forecast (Meteo) episodes broadcast and interpreted into Swiss German Sign Language by hearing interpreters (among them, children of Deaf adults, CODA) via Swiss National TV (Schweizerisches Radio und Fernsehen, SRF) (https://www.srf.ch/play/tv/sendung/tagesschau-in-gebaerdensprache?id=c40bed81-b150-0001-2b5a-1e90e100c1c0). For a more extended description of the data, visit https://www.wmt-slt.com/data.
description: We additionally acknowledge funding through the Innosuisse Flagship "Inclusive Information and Communication Technologies" (IICT) (grant agreement no. PFFS-21-47).
DOI: 10.26180/20057528
title: Developmental environments and personality data

description: Behavioural data from southern rainforest sunskinks incubated at 23 and 26 degrees, and skinks caught from the wild. Behaviours include activity, exploration, sociability, and boldness.
DOI: 10.26180/20057528.v1
title: Developmental environments and personality data

description: Behavioural data from southern rainforest sunskinks incubated at 23 and 26 degrees, and skinks caught from the wild. Behaviours include activity, exploration, sociability, and boldness.