cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7693110
title: BioWordlists

description: This describes the output files for the BioWordlists project. These files are ancillary data for other text mining projects. Each file is a tab-delimited file with one term per line. The first column is a unique ID. The second column is the main name of the term. The third column is a pipe-delimited set of the synonyms for this term (including the main term). <strong>terms_genes.tsv:</strong> This is a list of all human genes with synonyms. The first column is the HUGO gene ID. It includes an additional fourth column is the Entrez gene ID. Genes are built using the NCBI Gene resource with synonyms from the UMLS Metathesaurus. <strong>terms_drugs.tsv:</strong> This is a list of all drugs from the WikiData resource. It also includes some more general terms and inhibitors terms for all genes in the gene list. <strong>terms_cancers.tsv:</strong> This is a list of specific cancer types from the Disease Ontology. General cancer terms have been removed and synonyms added from the UMLS Metathesaurus. <strong>terms_variants.tsv:</strong> Common mutations, aberrations and other 'omic events that may occur to a gene, especially in the cancer setting. <strong>terms_conflicting.tsv:</strong> Several common biomedical terms that are easily confused with other useful concepts. An examples is "Cox Regression". This list is used to identify these to reduce ambiguity. <strong>terms_proteins.tsv:</strong> Human protein names from UniProt with synonyms.
DOI: 10.5281/zenodo.7699162
title: BioWordlists

description: This describes the output files for the BioWordlists project. These files are ancillary data for other text mining projects. Each file is a tab-delimited file with one term per line. The first column is a unique ID. The second column is the main name of the term. The third column is a pipe-delimited set of the synonyms for this term (including the main term). <strong>terms_genes.tsv:</strong> This is a list of all human genes with synonyms. The first column is the HUGO gene ID. It includes an additional fourth column is the Entrez gene ID. Genes are built using the NCBI Gene resource with synonyms from the UMLS Metathesaurus. <strong>terms_drugs.tsv:</strong> This is a list of all drugs from the WikiData resource. It also includes some more general terms and inhibitors terms for all genes in the gene list. <strong>terms_cancers.tsv:</strong> This is a list of specific cancer types from the Disease Ontology. General cancer terms have been removed and synonyms added from the UMLS Metathesaurus. <strong>terms_variants.tsv:</strong> Common mutations, aberrations and other 'omic events that may occur to a gene, especially in the cancer setting. <strong>terms_conflicting.tsv:</strong> Several common biomedical terms that are easily confused with other useful concepts. An examples is "Cox Regression". This list is used to identify these to reduce ambiguity. <strong>terms_proteins.tsv:</strong> Human protein names from UniProt with synonyms.
DOI: 10.5281/zenodo.7794768
title: BioWordlists

description: This describes the output files for the BioWordlists project. These files are ancillary data for other text mining projects. Each file is a tab-delimited file with one term per line. The first column is a unique ID. The second column is the main name of the term. The third column is a pipe-delimited set of the synonyms for this term (including the main term). <strong>terms_genes.tsv:</strong> This is a list of all human genes with synonyms. The first column is the HUGO gene ID. It includes an additional fourth column is the Entrez gene ID. Genes are built using the NCBI Gene resource with synonyms from the UMLS Metathesaurus. <strong>terms_drugs.tsv:</strong> This is a list of all drugs from the WikiData resource. It also includes some more general terms and inhibitors terms for all genes in the gene list. <strong>terms_cancers.tsv:</strong> This is a list of specific cancer types from the Disease Ontology. General cancer terms have been removed and synonyms added from the UMLS Metathesaurus. <strong>terms_variants.tsv:</strong> Common mutations, aberrations and other 'omic events that may occur to a gene, especially in the cancer setting. <strong>terms_conflicting.tsv:</strong> Several common biomedical terms that are easily confused with other useful concepts. An examples is "Cox Regression". This list is used to identify these to reduce ambiguity. <strong>terms_proteins.tsv:</strong> Human protein names from UniProt with synonyms.
DOI: 10.34740/kaggle/dsv/5303436
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.25773/5zet-aq32
title: A Data Repository for Impacts and uncertainties of climate-induced changes in watershed inputs on estuarine hypoxia
DOI: 10.6084/m9.figshare.22495765
title: Datasets

description: The data contain the number of reads assigned to taxa and the number of genes mappped in KEGG pathways database.
DOI: 10.6084/m9.figshare.22495765.v1
title: Datasets

description: The data contain the number of reads assigned to taxa and the number of genes mappped in KEGG pathways database.
DOI: 10.5281/zenodo.7794181
title: Plant dieback in Mediterranean shrublands under 2014 extreme drought (Alicante, Spain)

description: Field data from four Mediterranean shrublands monitored during an extreme drought in 2014 (hydrological year) in SE Spain. Data are plant dieback of the total plant community and main plant biotypes (shrubs, subshrubs and grasses), vegetation structure attributes (phytovolume, plant height, LAI, and sizes of patch and inter-patch areas), soil properties (soil depth and soil surface cover types) and water availability indicators (soil moisture and environmental variables).
DOI: 10.5281/zenodo.7794180
title: Plant dieback in Mediterranean shrublands under 2014 extreme drought (Alicante, Spain)

description: Field data from four Mediterranean shrublands monitored during an extreme drought in 2014 (hydrological year) in SE Spain. Data are plant dieback of the total plant community and main plant biotypes (shrubs, subshrubs and grasses), vegetation structure attributes (phytovolume, plant height, LAI, and sizes of patch and inter-patch areas), soil properties (soil depth and soil surface cover types) and water availability indicators (soil moisture and environmental variables).
DOI: 10.6084/m9.figshare.22495798
title: Data of the Indawgyi mafic rocks.xlsx

description: The zircon U–Pb isotopes and trace elements, whole-rock major-trace elements and Sr–Nd–Pb isotopes, and mineral major elements for the Indawgyi mafic rocks
DOI: 10.6084/m9.figshare.22495798.v1
title: Data of the Indawgyi mafic rocks.xlsx

description: The zircon U–Pb isotopes and trace elements, whole-rock major-trace elements and Sr–Nd–Pb isotopes, and mineral major elements for the Indawgyi mafic rocks
DOI: 10.6084/m9.figshare.20525698
title: Barriers and Facilitators to DATA Waivered Providers Prescribing Buprenorphine: A Qualitative Analysis Applying the Theory of Planned Behavior

description: <i>Background:</i> Provider beliefs about the treatment of people with addiction may influence their prescribing behavior. <i>Objective:</i> This study applied the Theory of Planned Behavior (TPB), to identify the salient beliefs of Drug Addiction Treatment Act of 2000 (DATA 2000) waivered providers, concerning prescribing buprenorphine to patients with Opioid Use Disorder (OUD). <i>Methods:</i> Texas buprenorphine providers participated in one of four online focus group discussions conducted in fall 2019. The focus group discussion were audio recorded and the total length was between 60-90 minutes. Thematic analysis was conducted to identify emerging themes and to categorize the behavioral, normative, and control beliefs related to buprenorphine prescribing. <i>Results:</i> Of the 14 total participants, 57% of the participants were male and annually treated between zero to sixty patients with buprenorphine. The codes generated were represented in thematic maps, specifying the positive or negative aspects of buprenorphine prescribing. Results indicate that providers’ primary motivation to prescribe buprenorphine was, implementation of a whole-patient approach through collaboration with behavioral health providers, in the provision of medications for opioid use disorder (MOUD). Providers primary normative belief was the recognition of key members of the medical community and patients’ families and friends as influential groups. Providers’ control beliefs focused on their ability to use buprenorphine in different practice settings. <i>Conclusion:</i> These results indicate that buprenorphine access may be expanded by increasing support for DATA waivered providers from other parts of the healthcare system such as behavioral health providers and pharmacists. Implications for clinical practice and future research will be discussed.
DOI: 10.6084/m9.figshare.20525698.v1
title: Barriers and Facilitators to DATA Waivered Providers Prescribing Buprenorphine: A Qualitative Analysis Applying the Theory of Planned Behavior

description: <i>Background:</i> Provider beliefs about the treatment of people with addiction may influence their prescribing behavior. <i>Objective:</i> This study applied the Theory of Planned Behavior (TPB), to identify the salient beliefs of Drug Addiction Treatment Act of 2000 (DATA 2000) waivered providers, concerning prescribing buprenorphine to patients with Opioid Use Disorder (OUD). <i>Methods:</i> Texas buprenorphine providers participated in one of four online focus group discussions conducted in fall 2019. The focus group discussion were audio recorded and the total length was between 60-90 minutes. Thematic analysis was conducted to identify emerging themes and to categorize the behavioral, normative, and control beliefs related to buprenorphine prescribing. <i>Results:</i> Of the 14 total participants, 57% of the participants were male and annually treated between zero to sixty patients with buprenorphine. The codes generated were represented in thematic maps, specifying the positive or negative aspects of buprenorphine prescribing. Results indicate that providers’ primary motivation to prescribe buprenorphine was, implementation of a whole-patient approach through collaboration with behavioral health providers, in the provision of medications for opioid use disorder (MOUD). Providers primary normative belief was the recognition of key members of the medical community and patients’ families and friends as influential groups. Providers’ control beliefs focused on their ability to use buprenorphine in different practice settings. <i>Conclusion:</i> These results indicate that buprenorphine access may be expanded by increasing support for DATA waivered providers from other parts of the healthcare system such as behavioral health providers and pharmacists. Implications for clinical practice and future research will be discussed.
DOI: 10.5281/zenodo.7794779
title: 3D ED / MicroED data of BI-3812

description: The sample was obtained from Boehringer Ingelheim within a frame of opnme project https://www.opnme.com Electron diffraction tilt series were recorded with GLACIOS TEM (Thermo Fisher) at liquid nitrogen temperature. Measurements were performed using the EPU-D (Thermo Fisher) module in continuous rotation mode with 200 kV electrons (wavelength of 0.0251 Å). Tilt series were collected within ±60° goniometer tilt range with 1° frame interval and rotation speed of 1° per second. The data were collected using an electron dose rate of 6.016 e/nm<sup>2</sup>s. The electron beam size used for diffraction data collection was 1.2 µm. The pixel size within diffraction patterns is 0.001075 Å<sup>-1</sup>.
DOI: 10.5281/zenodo.7794778
title: 3D ED / MicroED data of BI-3812

description: The sample was obtained from Boehringer Ingelheim within a frame of opnme project https://www.opnme.com Electron diffraction tilt series were recorded with GLACIOS TEM (Thermo Fisher) at liquid nitrogen temperature. Measurements were performed using the EPU-D (Thermo Fisher) module in continuous rotation mode with 200 kV electrons (wavelength of 0.0251 Å). Tilt series were collected within ±60° goniometer tilt range with 1° frame interval and rotation speed of 1° per second. The data were collected using an electron dose rate of 6.016 e/nm<sup>2</sup>s. The electron beam size used for diffraction data collection was 1.2 µm. The pixel size within diffraction patterns is 0.001075 Å<sup>-1</sup>.
DOI: 10.6084/m9.figshare.22496047
title: Datasets of the occurrence records of gypsy moths (Lymantria dispar Linnaeus) in Asia,North America and Europe

description: More recently introduced gypsy moths (Lymantria dispar Linnaeus) in Asia showed higher threats to North America than those in Europe: a perspective on niche and range shifts
DOI: 10.6084/m9.figshare.22496047.v1
title: Datasets of the occurrence records of gypsy moths (Lymantria dispar Linnaeus) in Asia,North America and Europe

description: More recently introduced gypsy moths (Lymantria dispar Linnaeus) in Asia showed higher threats to North America than those in Europe: a perspective on niche and range shifts
DOI: 10.6084/m9.figshare.22496092
title: Zebrafish_cell_type_colors.csv

description: Colors for cell types in scRNA from Hu, Lelek, Spanjaard et al. (Nature Genetics 2022). Please cite the original publication: https://www.nature.com/articles/s41588-022-01129-5
DOI: 10.6084/m9.figshare.22496092.v1
title: Zebrafish_cell_type_colors.csv

description: Colors for cell types in scRNA from Hu, Lelek, Spanjaard et al. (Nature Genetics 2022). Please cite the original publication: https://www.nature.com/articles/s41588-022-01129-5
DOI: 10.6084/m9.figshare.22496146
title: Zebrafish cell type colors

description: Colors for cell types in scRNA from Hu, Lelek, Spanjaard et al. (Nature Genetics 2022). Please cite the original publication: https://www.nature.com/articles/s41588-022-01129-5
DOI: 10.6084/m9.figshare.22496146.v1
title: Zebrafish cell type colors

description: Colors for cell types in scRNA from Hu, Lelek, Spanjaard et al. (Nature Genetics 2022). Please cite the original publication: https://www.nature.com/articles/s41588-022-01129-5
DOI: 10.6084/m9.figshare.21900462.v2
title: Dynamic Gut Microbiota Changes in Patients with Advanced Malignancies Experiencing Secondary Resistance to Immune Checkpoint Inhibitors and Immune-Related Adverse Events

description: Dynamic Gut Microbiota Changes in Patients with Advanced Malignancies Experiencing Secondary Resistance to Immune Checkpoint Inhibitors and Immune-Related Adverse Events <br> 16S rRNA gene sequencing data
DOI: 10.5285/24aef4f2-3bfc-4014-88e8-34644fdc71a3
title: Digital Elevation Models of Thwaites Glacier main trunk (2011-2022)

description: This dataset consists of Digital Elevation Models (DEMs) of the surface elevation of Thwaites Glacier. The region covered includes the floating area of the fast-flowing main trunk of Thwaites Glacier, sometimes referred to as Thwaites West Ice Tongue. The DEMs are derived from TanDEM-X SAR data. There are 172 individual scenes that reveal the geometric evolution of this area between 2011 and 2022. This work was supported by the NERC project CALISMO NE/P011365/1.
description: We created a time series of 168 DEMs from June 2011 to April 2022 based on experimental SAR data from the TanDEM-X satellite system using Gamma Remote Sensing software. The processing is fully described in Bevan et al., 2021 (10.5194/tc-15-3317-2021).
description: TanDEM-X satellite system. Gamma Remote Sensing software.
description: Via comparison with ICESat-2 data and in consideration of orbit uncertainty, the original DEMs have an estimated vertical uncertainty of +/-3 m. This is fully documented in the accompanying paper.
DOI: 10.6084/m9.figshare.22496170
title: Tree times

description: Timepoints for single cell lineage trees from Hu, Lelek, Spanjaard et al. (Nature Genetics 2022). Please cite the original publication: https://www.nature.com/articles/s41588-022-01129-5
DOI: 10.25822/gc7q-g526
title: Maternal Sleep in Pregnancy and the Fetus
DOI: 10.6084/m9.figshare.22496161
title: Soil_Foliage.txt

description: The Soil_Foliage file contains measured element concentrations (mg/kg) in soils and assimilative organs and their ratios. The data are supplemented with measured soil pH and total exchangeable acidity (in mmolc/kg).
DOI: 10.6084/m9.figshare.22496161.v1
title: Soil_Foliage.txt

description: The Soil_Foliage file contains measured element concentrations (mg/kg) in soils and assimilative organs and their ratios. The data are supplemented with measured soil pH and total exchangeable acidity (in mmolc/kg).
DOI: 10.5066/p9l7s3nq
title: Input and output data from streamflow and water-quality regression models used to characterize streamflow and water-quality conditions in the Upper Yampa River Basin, Colorado, from 1992-2018

description: This dataset includes input and output data from streamflow and water-quality regression models used to characterize streamflow and water-quality conditions in the Upper Yampa River Basin, Colorado from 1999-2018. All input data, including discrete and continuous streamflows and discrete concentrations of suspended sediment, Kjeldahl nitrogen, and total phosphorus, were compiled from the U.S. Geological Survey (USGS) National Water Information System (NWIS) database. Input data were used in multiple models including Maintenance of Variance Extension Type 2 (MOVE.2), LOAD ESTimator (LOADEST), and Weighted Regressions on Time, Discharge, and Season (WRTDS) to estimate continuous streamflow records, daily concentrations and loads, and streamflow-normalized annual mean concentrations and loads of selected water-quality constituents. All data were collected by the USGS. Prepared in cooperation with Upper Yampa River Watershed Group, Upper Yampa Water Conservancy District, Colorado Water Conservation Board, Yampa White Green Basin Roundtable, Mount Werner Water and Sanitation District, Routt County, and the City of Steamboat Springs.
DOI: 10.6084/m9.figshare.22496182
title: Mediating role of self-compassion in the relationship between psychological flexibility and psychological well-being in women with breast cancer

description: The data related to the paper titled Mediating role of self-compassion in the relationship between psychological flexibility and psychological well-being in women with breast cancer
DOI: 10.25345/c5445hn93
title: MassIVE MSV000091612 - Test1Test1Test1Test1Test1Test1Test1Test1
title: Hmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm
DOI: 10.57745/ghhla0
title: z.tritici.IP0323.reannot.isoforms.gff3

description: Zymoseptoria tritici IPO323 gene models gff3 file with isoforms
DOI: 10.57745/kacook
title: z.tritici.IP0323.annotations.metadata

description: Zymoseptoria tritici IPO323 annotations metadata
DOI: 10.57745/sw0box
title: z.tritici.IP0323.reannot.gff3

description: Zymoseptoria tritici IPO323 gene models gff3 file
DOI: 10.57745/x6k4gr
title: z.tritici.IP0323.annotations.txt

description: Zymoseptoria tritici IPO323 annotations
DOI: 10.57745/bpjrim
title: z.tritici.IP0323.annotations.txt

description: Zymoseptoria tritici IPO323 annotations
DOI: 10.57745/oyf0ui
title: z.tritici.IP0323.annotations.txt

description: Zymoseptoria tritici IPO323 annotations
DOI: 10.57745/ub7feu
title: z.tritici.IP0323.annotations.metadata

description: Zymoseptoria tritici IPO323 annotations metadata
DOI: 10.6084/m9.figshare.22496164
title: Input_13C.txt

description: The Input_13C file contains the measured d13C values in tree rings, supplemented by the main environmental characteristics including the temporal evolution of sulphur and nitrogen deposition, growing season air temperature, growing season precipitation, growing season PDSI, and the canopy width index.
DOI: 10.5281/zenodo.7794886
title: SciExpeM - 10.5281/zenodo.7794886

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794885
title: SciExpeM - 10.5281/zenodo.7794886

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794888
title: SciExpeM - 10.5281/zenodo.7794888

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794887
title: SciExpeM - 10.5281/zenodo.7794888

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794892
title: SciExpeM - 10.5281/zenodo.7794892

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794891
title: SciExpeM - 10.5281/zenodo.7794892

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794894
title: SciExpeM - 10.5281/zenodo.7794894

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794893
title: SciExpeM - 10.5281/zenodo.7794894

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794896
title: SciExpeM - 10.5281/zenodo.7794896

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794895
title: SciExpeM - 10.5281/zenodo.7794896

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794898
title: SciExpeM - 10.5281/zenodo.7794898

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794897
title: SciExpeM - 10.5281/zenodo.7794898

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794900
title: SciExpeM - 10.5281/zenodo.7794900

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794899
title: SciExpeM - 10.5281/zenodo.7794900

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794902
title: SciExpeM - 10.5281/zenodo.7794902

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794901
title: SciExpeM - 10.5281/zenodo.7794902

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794904
title: SciExpeM - 10.5281/zenodo.7794904

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794903
title: SciExpeM - 10.5281/zenodo.7794904

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794906
title: SciExpeM - 10.5281/zenodo.7794906

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794905
title: SciExpeM - 10.5281/zenodo.7794906

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794908
title: SciExpeM - 10.5281/zenodo.7794908

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610
DOI: 10.5281/zenodo.7794907
title: SciExpeM - 10.5281/zenodo.7794908

description: Zhang, Changhua; Li, Ping; Li, Youliang; He, Jiuning; Li, Xiangyuan - Energy & Fuels, 2014, (28), 4603-4610