cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0189095.10fu
title: SH0189095.10FU

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/sh0189096.10fu
title: SH0189096.10FU

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: 10.34740/kaggle/dsv/14448622
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15156/bio/sh0189097.10fu
title: SH0189097.10FU

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/sh0189098.10fu
title: SH0189098.10FU

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/sh0189099.10fu
title: SH0189099.10FU

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: 10.15468/dl.vpkhz9
title: Occurrence Download

description: A dataset listing the 93 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Machine Observation",
 "GadmGid is one of (COL.2.4_2, COL.2.6_2, COL.2.7_2, COL.2.18_2, COL.2.19_2, COL.2.28_2, COL.2.34_2, COL.2.37_2, COL.2.47_2, COL.2.57_2, COL.2.60_2, COL.2.61_2, COL.2.64_2, COL.2.70_2, COL.2.79_2, COL.2.88_2, COL.2.101_2, COL.2.108_2, COL.2.110_2, COL.2.111_2, COL.2.115_2, COL.2.117_2, COL.2.119_2)",
 "TaxonKey is Aves"
 ]
}

 The dataset's 93 records were derived from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008584-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26688002.v1
title: Additional file 11 of Loss of miR-101-3p in melanoma stabilizes genomic integrity, leading to cell death prevention

description: Additional file 11. SupplTab10_miRTargetLink_GeneTrail.
DOI: 10.6084/m9.figshare.26610591
title: Additional file 4 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 4: Sensitivity analysis results of causal effects of SCZ on immune cells
DOI: 10.6084/m9.figshare.26610594
title: Additional file 5 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 5: Sensitivity analysis results of causal effects of immune cells on SCZ
DOI: 10.6084/m9.figshare.26610588
title: Additional file 3 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 3: Results of the causal effect of immune cells on SCZ
DOI: 10.6084/m9.figshare.26610585.v1
title: Additional file 2 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 2: IVW results of the causal effect of SCZ on immune cells
DOI: 10.6084/m9.figshare.26610594.v1
title: Additional file 5 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 5: Sensitivity analysis results of causal effects of immune cells on SCZ
DOI: 10.6084/m9.figshare.26610582.v1
title: Additional file 1 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 1: Causal effects of schizophrenia on immune cells
DOI: 10.6084/m9.figshare.26688029
title: Additional file 2 of Effect-based monitoring of chemical hazards in drinking water from source to tap: seasonal trends over 2 years of sampling

description: Additional file 2. Limits of detection, correlation analyzes, calculated BEQs for AhR, ER and AR assays.
DOI: 10.6084/m9.figshare.26688029.v1
title: Additional file 2 of Effect-based monitoring of chemical hazards in drinking water from source to tap: seasonal trends over 2 years of sampling

description: Additional file 2. Limits of detection, correlation analyzes, calculated BEQs for AhR, ER and AR assays.
DOI: 10.15468/dl.qh96x6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.036504 -32.742036, 149.036504 -32.748773, 149.034258 -32.748773, 149.034258 -32.760002, 149.043241 -32.760002, 149.043241 -32.764494, 149.047733 -32.764494, 149.047733 -32.757756, 149.040996 -32.757756, 149.040996 -32.746527, 149.03875 -32.746527, 149.03875 -32.742036, 149.036504 -32.742036))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067525-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26688047
title: Additional file 1 of The proteome of the blood–brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture

description: Additional file 1: Data S1. Individual protein identification lists for all datasets.
DOI: 10.6084/m9.figshare.26688047.v1
title: Additional file 1 of The proteome of the blood–brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture

description: Additional file 1: Data S1. Individual protein identification lists for all datasets.
DOI: 10.6084/m9.figshare.26688050
title: Additional file 2 of The proteome of the blood–brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture

description: Additional file 2: Data S2. MSFragger peptide-spectrum match (psm) details after filtering for all datasets. Note that this table includes hits to the decoy database (if applicable).
DOI: 10.6084/m9.figshare.26688050.v1
title: Additional file 2 of The proteome of the blood–brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture

description: Additional file 2: Data S2. MSFragger peptide-spectrum match (psm) details after filtering for all datasets. Note that this table includes hits to the decoy database (if applicable).
DOI: 10.6084/m9.figshare.26688056
title: Additional file 4 of The proteome of the blood–brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture

description: Additional file 4: Table S1. Sample and MS run information. Table S2. Proteins identified by in vivo glycocapture from rat brain. Table S3. Proteins identified by in vivo glycocapture from mouse brain. Table S4. All proteins identified by in vivo glycocapture from rat or mouse brain. Table S5. All proteins identified by cell surface glycocapture in a rat endothelial cell line (SV-ARBEC). Table S6. All proteins identified by cell surface glycocapture in a rat endothelial cell line (SV-ARBEC).
DOI: 10.6084/m9.figshare.26688056.v1
title: Additional file 4 of The proteome of the blood–brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture

description: Additional file 4: Table S1. Sample and MS run information. Table S2. Proteins identified by in vivo glycocapture from rat brain. Table S3. Proteins identified by in vivo glycocapture from mouse brain. Table S4. All proteins identified by in vivo glycocapture from rat or mouse brain. Table S5. All proteins identified by cell surface glycocapture in a rat endothelial cell line (SV-ARBEC). Table S6. All proteins identified by cell surface glycocapture in a rat endothelial cell line (SV-ARBEC).
DOI: 10.6084/m9.figshare.26688062
title: Additional file 2 of CDSKNNXMBD: a novel clustering framework for large-scale single-cell data based on a stable graph structure

description: Additional file 2: Table S1. General information and detailed preprocessing pipeline for the validation single-cell sequencing datasets.
DOI: 10.6084/m9.figshare.26688062.v1
title: Additional file 2 of CDSKNNXMBD: a novel clustering framework for large-scale single-cell data based on a stable graph structure

description: Additional file 2: Table S1. General information and detailed preprocessing pipeline for the validation single-cell sequencing datasets.
DOI: 10.6084/m9.figshare.26610642.v1
title: Additional file 1 of Are ready biodegradation tests effective screens for non-persistence in all environmental compartments?

description: Additional file 1: Table S1. The list of substances and biodegradation conclusions as retrieved from the ECHA database via the OECD QSAR Toolbox v4.4.1 in October 2021. In order to conform with the Intellectual Property Rights Notice in ECHA's legal notice, specifically on the subject of systematic data collection, only the outcomes of the testing are here provided, with no specific values underpinning those conclusions. For the specific data, the reader is directed to the ECHA database at https://echa.europa.eu . The phys-chem parameters (log Kow, vapour pressure, water solubility, and log Koc) were predicted by entering the CAS number into the US EPA EpiSuite model, as described in the methods. It is noted that for substances without a CAS or for UVCBs, it was not possible to generate the data (marked as #NA). Table S2. Number of non-readily biodegradable substances with simulation test data per compartment. The right-hand side of the table shows how many of those data points met all of the data quality criteria defined and were included in the final study set. A similar assessment of the readily biodegradable substances is available in Table 2.
DOI: 10.6084/m9.figshare.26688065
title: Additional file 1 of Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants

description: Additional file 1: Table S1. Information on genome-wide association studies (GWAS) of cancers among individuals of European ancestry. Table S2. Summary statistics of instrumental variables (IVs) for the 94 significant associations identified in primary Mendelian randomization (MR) analyses. Table S3. Significant associations identified in primary MR analyses using the inverse-variance weighted (IVW) method. Table S4. MR results based on instrumental variables (IVs) selected under a more stringent threshold (P &lt; 5 × 10–8 & LD r2 &lt; 0.001) for the 94 significant associations identified in primary analyses. Table S5. Summary statistics of instrumental variables (IVs) used for reverse Mendelian randomization (MR) analyses for the 94 significant associations identified in primary analyses. Table S6. Replication analyses results using an independent metabolite GWAS dataset for the 94 significant associations identified in primary analyses. Table S7. Twenty-one associations that remained significant in Multivariable MR (MVMR) analyses. Table S8. Seven metabolite-cancer pairs showing a nominally significant genetic correlation. Table S9. Colocalization analyses for the 94 significant associations identified in primary analyses.
DOI: 10.6084/m9.figshare.26688065.v1
title: Additional file 1 of Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants

description: Additional file 1: Table S1. Information on genome-wide association studies (GWAS) of cancers among individuals of European ancestry. Table S2. Summary statistics of instrumental variables (IVs) for the 94 significant associations identified in primary Mendelian randomization (MR) analyses. Table S3. Significant associations identified in primary MR analyses using the inverse-variance weighted (IVW) method. Table S4. MR results based on instrumental variables (IVs) selected under a more stringent threshold (P &lt; 5 × 10–8 & LD r2 &lt; 0.001) for the 94 significant associations identified in primary analyses. Table S5. Summary statistics of instrumental variables (IVs) used for reverse Mendelian randomization (MR) analyses for the 94 significant associations identified in primary analyses. Table S6. Replication analyses results using an independent metabolite GWAS dataset for the 94 significant associations identified in primary analyses. Table S7. Twenty-one associations that remained significant in Multivariable MR (MVMR) analyses. Table S8. Seven metabolite-cancer pairs showing a nominally significant genetic correlation. Table S9. Colocalization analyses for the 94 significant associations identified in primary analyses.
DOI: 10.15468/dl.x8dzry
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "DatasetKey is one of (Herbario Nacional Colombiano (COL), Herbario Universidad de Antioquia (HUA), Herbario CDMB - Jardín Botánico Eloy Valenzuela, Herbario TULV - Jardín Botánico \"Juan María Céspedes\", Colección Herbario Federico Medem Bogotá - FMB, Herbario Enrique Forero de la Universidad de la Amazonia (HUAZ))",
 "OccurrenceStatus is Present",
 "TaxonKey is Heliconia rostrata Ruiz & Pav."
 ]
}

 The dataset includes 57 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067526-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.457pmx
title: Occurrence Download

description: A dataset containing 139 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((147.543048 -32.69712, 147.543048 -32.703857, 147.547539 -32.703857, 147.547539 -32.706103, 147.552031 -32.706103, 147.552031 -32.699365, 147.545294 -32.699365, 147.545294 -32.69712, 147.543048 -32.69712)), ((147.552031 -32.706103, 147.552031 -32.710594, 147.554277 -32.710594, 147.554277 -32.706103, 147.552031 -32.706103)), ((147.554277 -32.710594, 147.554277 -32.715086, 147.556523 -32.715086, 147.556523 -32.726315, 147.561014 -32.726315, 147.561014 -32.721823, 147.56326 -32.721823, 147.56326 -32.719578, 147.561014 -32.719578, 147.561014 -32.715086, 147.56326 -32.715086, 147.56326 -32.71284, 147.556523 -32.71284, 147.556523 -32.710594, 147.554277 -32.710594)), ((147.556523 -32.726315, 147.554277 -32.726315, 147.554277 -32.735298, 147.552031 -32.735298, 147.552031 -32.737544, 147.547539 -32.737544, 147.547539 -32.742036, 147.552031 -32.742036, 147.552031 -32.744281, 147.554277 -32.744281, 147.554277 -32.753265, 147.56326 -32.753265, 147.56326 -32.75551, 147.565506 -32.75551, 147.565506 -32.753265, 147.576735 -32.753265, 147.576735 -32.744281, 147.578981 -32.744281, 147.578981 -32.742036, 147.585718 -32.742036, 147.585718 -32.737544, 147.583472 -32.737544, 147.583472 -32.735298, 147.572243 -32.735298, 147.572243 -32.737544, 147.56326 -32.737544, 147.56326 -32.733052, 147.556523 -32.733052, 147.556523 -32.726315)), ((147.554277 -32.753265, 147.547539 -32.753265, 147.547539 -32.748773, 147.545294 -32.748773, 147.545294 -32.757756, 147.554277 -32.757756, 147.554277 -32.753265)), ((147.556523 -32.710594, 147.561014 -32.710594, 147.561014 -32.706103, 147.556523 -32.706103, 147.556523 -32.710594)))"
 ]
}

 The dataset includes 139 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067527-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26688134
title: Additional file 4 of Platycodon D protects human nasal epithelial cells from pyroptosis through the Nrf2/HO-1/ROS signaling cascade in chronic rhinosinusitis

description: Additional file 4. 1483 CRS-related genes and 100 targets of PLD in the human body.
DOI: 10.6084/m9.figshare.26688134.v1
title: Additional file 4 of Platycodon D protects human nasal epithelial cells from pyroptosis through the Nrf2/HO-1/ROS signaling cascade in chronic rhinosinusitis

description: Additional file 4. 1483 CRS-related genes and 100 targets of PLD in the human body.
DOI: 10.6084/m9.figshare.26688167
title: Additional file 1 of Effectiveness of tranexamic acid in burn patients undergoing surgery – a systematic review and meta-analysis

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.26688167.v1
title: Additional file 1 of Effectiveness of tranexamic acid in burn patients undergoing surgery – a systematic review and meta-analysis

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.26610582
title: Additional file 1 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 1: Causal effects of schizophrenia on immune cells
DOI: 10.6084/m9.figshare.26610642
title: Additional file 1 of Are ready biodegradation tests effective screens for non-persistence in all environmental compartments?

description: Additional file 1: Table S1. The list of substances and biodegradation conclusions as retrieved from the ECHA database via the OECD QSAR Toolbox v4.4.1 in October 2021. In order to conform with the Intellectual Property Rights Notice in ECHA's legal notice, specifically on the subject of systematic data collection, only the outcomes of the testing are here provided, with no specific values underpinning those conclusions. For the specific data, the reader is directed to the ECHA database at https://echa.europa.eu . The phys-chem parameters (log Kow, vapour pressure, water solubility, and log Koc) were predicted by entering the CAS number into the US EPA EpiSuite model, as described in the methods. It is noted that for substances without a CAS or for UVCBs, it was not possible to generate the data (marked as #NA). Table S2. Number of non-readily biodegradable substances with simulation test data per compartment. The right-hand side of the table shows how many of those data points met all of the data quality criteria defined and were included in the final study set. A similar assessment of the readily biodegradable substances is available in Table 2.
DOI: 10.6084/m9.figshare.26610585
title: Additional file 2 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 2: IVW results of the causal effect of SCZ on immune cells
DOI: 10.6084/m9.figshare.26610588.v1
title: Additional file 3 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 3: Results of the causal effect of immune cells on SCZ
DOI: 10.6084/m9.figshare.26610591.v1
title: Additional file 4 of Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

description: Supplementary file 4: Sensitivity analysis results of causal effects of SCZ on immune cells
DOI: 10.6084/m9.figshare.26610693
title: Additional file 3 of The current distribution of tick species in Inner Mongolia and inferring potential suitability areas for dominant tick species based on the MaxEnt model

description: Additional file 3: Table S1 Environmental and bioclimatic variables for the four dominant tick species distribution models by MaxEnt.
DOI: 10.6084/m9.figshare.26610693.v1
title: Additional file 3 of The current distribution of tick species in Inner Mongolia and inferring potential suitability areas for dominant tick species based on the MaxEnt model

description: Additional file 3: Table S1 Environmental and bioclimatic variables for the four dominant tick species distribution models by MaxEnt.