cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh462638.07fu
title: SH462638.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh462639.07fu
title: SH462639.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh462640.07fu
title: SH462640.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1830719.08fu
title: SH1830719.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1830720.08fu
title: SH1830720.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1830721.08fu
title: SH1830721.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh462641.07fu
title: SH462641.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.18112/openneuro.ds003676.v1.0.0
title: diffusion_fMRI
DOI: 10.6084/m9.figshare.13116920.v1
title: Puy_2020.xlsx

description: Experimental data
DOI: 10.5281/zenodo.4762971
title: Data accompanying the publication "Sensitivity of grass fires burning in marginal conditions to atmospheric turbulence" in the Journal of Geophysical Research-Atmospheres

description: Data accompanying Jonko, Yedinak, Conley, and Linn (2021): "Sensitivity of grass fires burning in marginal conditions to atmospheric turbulence", JGR-Atmospheres. LA-UR-21-24832. The following files were generated from simulations performed with Los Alamos National Laboratory coupled atmosphere-fire behavior model FIRETEC v1.3: area_burned.csv contains the area burned per second in m^2 for 45 CORE simulations, 20 INIT simulations and 20 BOUND simulations (85 columns), and 600 seconds of simulation (600 rows). fire_perimeter.csv containing the fire perimeters in m for 45 CORE simulations, 20 INIT simulations and 20 BOUND simulations (85 columns), and 600 seconds of simulation (600 rows). consumption_per_second.csv containing consumption in kg/s for 45 CORE simulations, 20 INIT simulations and 20 BOUND simulations (85 columns), and 600 seconds of simulation (600 rows). rate_of_spread.csv containing the distance of the fire front from the ignition line in m for 45 CORE simulations, 20 INIT simulations and 20 BOUND simulations (85 columns), and 600 seconds of simulation (600 rows). CORE1_u_10m_300_sec.hdf, INIT3_u_10m_300_sec.hdf, and BOUND3_u_10m_300_sec.hdf contain u wind speeds at 10 m height for 300 seconds (3D: time, x, y) of simulation for simulations CORE1, INIT3, and BOUND3, respectively. CORE.final.fuel.density.hdf contains final fuel densities in the surface layer of the model (3D: ensemble member, x, y) for all 45 CORE simulations. CORE{1-45}_3D_u_120_sec.hdf: 45 files containing vertically and horizontally resolved u winds for 120 seconds of simulation (4D: time, x, y, z) for the 45 CORE ensemble members. For additional information about this data, please contact the corresponding author at ajonko@lanl.gov.
DOI: 10.5281/zenodo.4762970
title: Data accompanying the publication "Sensitivity of grass fires burning in marginal conditions to atmospheric turbulence" in the Journal of Geophysical Research-Atmospheres

description: Data accompanying Jonko, Yedinak, Conley, and Linn (2021): "Sensitivity of grass fires burning in marginal conditions to atmospheric turbulence", JGR-Atmospheres. LA-UR-21-24832. The following files were generated from simulations performed with Los Alamos National Laboratory coupled atmosphere-fire behavior model FIRETEC v1.3: area_burned.csv contains the area burned per second in m^2 for 45 CORE simulations, 20 INIT simulations and 20 BOUND simulations (85 columns), and 600 seconds of simulation (600 rows). fire_perimeter.csv containing the fire perimeters in m for 45 CORE simulations, 20 INIT simulations and 20 BOUND simulations (85 columns), and 600 seconds of simulation (600 rows). consumption_per_second.csv containing consumption in kg/s for 45 CORE simulations, 20 INIT simulations and 20 BOUND simulations (85 columns), and 600 seconds of simulation (600 rows). rate_of_spread.csv containing the distance of the fire front from the ignition line in m for 45 CORE simulations, 20 INIT simulations and 20 BOUND simulations (85 columns), and 600 seconds of simulation (600 rows). CORE1_u_10m_300_sec.hdf, INIT3_u_10m_300_sec.hdf, and BOUND3_u_10m_300_sec.hdf contain u wind speeds at 10 m height for 300 seconds (3D: time, x, y) of simulation for simulations CORE1, INIT3, and BOUND3, respectively. CORE.final.fuel.density.hdf contains final fuel densities in the surface layer of the model (3D: ensemble member, x, y) for all 45 CORE simulations. CORE{1-45}_3D_u_120_sec.hdf: 45 files containing vertically and horizontally resolved u winds for 120 seconds of simulation (4D: time, x, y, z) for the 45 CORE ensemble members. For additional information about this data, please contact the corresponding author at ajonko@lanl.gov.
DOI: 10.5281/zenodo.4642458
title: Dataset: Relativistic EOM-CCSD for core-excited and core-ionized state energiesbased on the 4-component Dirac-Coulomb(-Gaunt) Hamiltonian

description: This dataset collects the unprocessed (= outputs from calculations) and processed (jupyter notebooks) results discussed in the paper titled "Relativistic EOM-CCSD for core-excited and core-ionized state energies based on the 4-component Dirac-Coulomb(-Gaunt) Hamiltonian", by Loïc Halbert, Marta Lopez Vidal, Avijit Shee, Sonia Coriani and Andre Severo Pereira Gomes. It also contains the figures used in the manuscript.
description: ASPG and LH acknowledge support from PIA ANR project CaPPA (ANR-11-LABX-0005-01), the Franco-German project CompRIXS (Agence nationale de la recherche ANR-19-CE29-0019, Deutsche Forschungsgemeinschaft JA 2329/6-1), I-SITE ULNE projects OVER-SEE and MESONM International Associated Laboratory (LAI) (ANR-16-IDEX-0004), the French Ministry of Higher Education and Research, region Hautsde France council and European Regional Development Fund (ERDF) project CPER CLIMIBIO, and the French national supercomputing facilities (grants DARI A0050801859, A0070801859). MLV and SC acknowledge support from DTU Chemistry (start-up Ph.D. grant).MLV acknowledges support from COST (CM1405)
DOI: 10.5281/zenodo.4116366
title: Dataset: Relativistic EOM-CCSD for core-excited and core-ionized state energiesbased on the 4-component Dirac-Coulomb(-Gaunt) Hamiltonian

description: This dataset collects the unprocessed (= outputs from calculations) and processed (jupyter notebooks) results discussed in the paper titled "Relativistic EOM-CCSD for core-excited and core-ionized state energies based on the 4-component Dirac-Coulomb(-Gaunt) Hamiltonian", by Loïc Halbert, Marta Lopez Vidal, Avijit Shee, Sonia Coriani and Andre Severo Pereira Gomes. It also contains the figures used in the manuscript.
description: ASPG and LH acknowledge support from PIA ANR project CaPPA (ANR-11-LABX-0005-01), the Franco-German project CompRIXS (Agence nationale de la recherche ANR-19-CE29-0019, Deutsche Forschungsgemeinschaft JA 2329/6-1), I-SITE ULNE projects OVER-SEE and MESONM International Associated Laboratory (LAI) (ANR-16-IDEX-0004), the French Ministry of Higher Education and Research, region Hautsde France council and European Regional Development Fund (ERDF) project CPER CLIMIBIO, and the French national supercomputing facilities (grants DARI A0050801859, A0070801859). MLV and SC acknowledge support from DTU Chemistry (start-up Ph.D. grant).MLV acknowledges support from COST (CM1405)
DOI: 10.25345/c5tf9v
title: MassIVE MSV000087546 - GNPS streptomyces albidoflavus 19-S21
title: Data of molecular networking of streptomyces albidoflavus 19-S21
DOI: 10.6084/m9.figshare.14706990
title: AxialGzWallThickness.xlsx

description: This is the raw data sheet for Table 4 in the article entitled "Growth-Profile Configuration for Specific Deformations of Tubular Organs: A Study of Growth-induced Thinning and Dilation of the Human Cervix" published in PLOS ONE
DOI: 10.6084/m9.figshare.14706990.v2
title: AxialGzWallThickness.xlsx

description: This is the raw data sheet for Table 4 in the article entitled "Growth-Profile Configuration for Specific Deformations of Tubular Organs: A Study of Growth-induced Thinning and Dilation of the Human Cervix" published in PLOS ONE
DOI: 10.6084/m9.figshare.14706990.v1
title: AxialGzWallThickness.xlsx

description: This is the raw data sheet for Table 4 in the article entitled "Growth-Profile Configuration for Specific Deformations of Tubular Organs: A Study of Growth-induced Thinning and Dilation of the Human Cervix" published in PLOS ONE
DOI: 10.5281/zenodo.4737506
title: Information about articles screened for the Brazilian Reproducibility Initiative

description: <strong>Description:</strong> A dataset containing some data regarding the experiments described by articles published by biomedical scientists with Brazilian affiliations. This dataset was collected for a systematic review conducted in the course of the Brazilian Reproducibility Initiative - see here and here for details. In brief, we started with a search on Web of Science for articles published between 1998-2017, in the biomedical sciences, by Brazilian authors. We searched their full text for occurrences of the names of a few methods of interest. Each article where we found hits for these methods was manually evaluated to confirm that the method was indeed used in at least one experiment reported in the article. For some articles, other information was also extracted by the evaluator. It is on the basis of this evaluation by a person that this dataset was built. Note that this is not an exhaustive description of the article - it is not an exhaustive list of all methods, models or tissues used in the work. The information here is only indicating that the methods listed were used, not that they were the only methods used. <strong>Columns:</strong> <strong>DOI</strong>: The Digital Object Identifier corresponding to the article.<br> <strong>Methods</strong>: A method (or many, separated by semicolons) used in the work reported in the article.<br> <strong> PCR details</strong>: Details of the RT-PCR protocol – usually the type of PCR (conventional, SYBR, Taqman).<br> <strong>Tissue</strong>: A tissue (or many, separated by semicolons) used in the work reported in the article.<br> <strong>Model (general)</strong>: The type of the experimental models used in the work reported in the article (possible values are cell line, rats or mice).<br> <strong>Model (specific)</strong>: The specific experimental model used in the work reported in the article. For cell lines, this is a common name for the cell (e.g. GRX or B16). For animals, it is the particular breed (e.g. Balb/c or C57BL/6). For primary cultures, the tissue used is reported in the Tissue column.
DOI: 10.5281/zenodo.4737505
title: Information about articles screened for the Brazilian Reproducibility Initiative

description: <strong>Description:</strong> A dataset containing some data regarding the experiments described by articles published by biomedical scientists with Brazilian affiliations. This dataset was collected for a systematic review conducted in the course of the Brazilian Reproducibility Initiative - see here and here for details. In brief, we started with a search on Web of Science for articles published between 1998-2017, in the biomedical sciences, by Brazilian authors. We searched their full text for occurrences of the names of a few methods of interest. Each article where we found hits for these methods was manually evaluated to confirm that the method was indeed used in at least one experiment reported in the article. For some articles, other information was also extracted by the evaluator. It is on the basis of this evaluation by a person that this dataset was built. Note that this is not an exhaustive description of the article - it is not an exhaustive list of all methods, models or tissues used in the work. The information here is only indicating that the methods listed were used, not that they were the only methods used. <strong>Columns:</strong> <strong>DOI</strong>: The Digital Object Identifier corresponding to the article.<br> <strong>Methods</strong>: A method (or many, separated by semicolons) used in the work reported in the article.<br> <strong> PCR details</strong>: Details of the RT-PCR protocol – usually the type of PCR (conventional, SYBR, Taqman).<br> <strong>Tissue</strong>: A tissue (or many, separated by semicolons) used in the work reported in the article.<br> <strong>Model (general)</strong>: The type of the experimental models used in the work reported in the article (possible values are cell line, rats or mice).<br> <strong>Model (specific)</strong>: The specific experimental model used in the work reported in the article. For cell lines, this is a common name for the cell (e.g. GRX or B16). For animals, it is the particular breed (e.g. Balb/c or C57BL/6). For primary cultures, the tissue used is reported in the Tissue column.
DOI: 10.34740/kaggle/dsv/2290407
title: multilevel causality relations deaths age sex
DOI: 10.6084/m9.figshare.13116920.v2
title: Puy_NewPhytologist_2020.xlsx

description: Experimental data
DOI: 10.6084/m9.figshare.13116920
title: Puy_NewPhytologist_2020.xlsx

description: Experimental data
DOI: 10.6084/m9.figshare.13116920.v4
title: Puy_NewPhytologist_2020.xlsx

description: Experimental data
DOI: 10.6084/m9.figshare.13116920.v3
title: Puy_NewPhytologist_2020.xlsx

description: Experimental data
DOI: 10.5281/zenodo.1436990
title: Circuit theoretic accessibility map of the Malaysian states of Borneo, based on land characteristics and population density

description: Created using freely available geospatial data and open source code (available from mairindeith/CircuitTheoreticAccessibility), this is a map of modelled bushmeat hunting effort according to landscape resistance and circuit-theoretic principles. It is part of a manuscript in preparation for publication.
DOI: 10.5281/zenodo.1436989
title: Circuit theoretic accessibility map of the Malaysian states of Borneo, based on land characteristics and population density

description: Created using freely available geospatial data and open source code (available from mairindeith/CircuitTheoreticAccessibility), this is a map of modelled bushmeat hunting effort according to landscape resistance and circuit-theoretic principles. It is part of a manuscript in preparation for publication.
DOI: 10.5519/qd.brk5sid0
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (23 records)
DOI: 10.5281/zenodo.4884836
title: COVID-19 KG

description: a KG combining GNBR, COVID-19 Disease Map and CROssBAR.
DOI: 10.5281/zenodo.4783051
title: COVID-19 KG

description: a KG combining GNBR, COVID-19 Disease Map and CROssBAR.
DOI: 10.15468/dl.x5vb5u
title: Occurrence Download

description: A dataset containing 11987804 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Dutch Vegetation Database"
 ]
}

 The dataset includes 11987804 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064250-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bhjvjr
title: Occurrence Download

description: A dataset containing 1515208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Polypodiopsida",
 "Year 1945-2021"
 ]
}

 The dataset includes 1515208 records from 787 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0313359-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.1kdinu
title: Occurrence Download

description: A dataset containing 18652 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Specimen",
 "BasisOfRecord is Literature Occurrence"
 ]
 },
 "HasCoordinate is true",
 {
 "or" : [
 "TaxonKey is Sturnira bidens (Thomas, 1915)",
 "TaxonKey is Sturnira erythromos (Tschudi, 1844)",
 "TaxonKey is Artibeus fraterculus Anthony, 1924",
 "TaxonKey is Glossophaga soricina (Pallas, 1766)"
 ]
 },
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 18652 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007125-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.