cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0200319.10fu
title: SH0200319.10FU

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/sh0200320.10fu
title: SH0200320.10FU

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/sh0200321.10fu
title: SH0200321.10FU

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/sh0200322.10fu
title: SH0200322.10FU

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/sh0200323.10fu
title: SH0200323.10FU

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/sh0200324.10fu
title: SH0200324.10FU

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/sh0200325.10fu
title: SH0200325.10FU

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/sh0200326.10fu
title: SH0200326.10FU

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/sh0200327.10fu
title: SH0200327.10FU

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.tc95qd
title: Occurrence Download

description: A dataset containing 583 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Angelica dahurica (Hoffm.) Benth. & Hook.fil. ex Franch. & Sav."
 ]
}

 The dataset includes 583 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009433-250402121839773/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.25157428.v1
title: Additional file 1 of Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

description: Additional file 1: Table S1. Variant categories by confidence and number of variants in the1000 Bull Genomes project (Run9). Table S2. Accession Number and Project ID of the out-species samples used in this study for the determination of ancestral alleles including the cattle group used for principal component analysis. Table S3. Attribution for the images used in Fig. 1.
DOI: 10.6084/m9.figshare.25157804
title: Additional file 2 of Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

description: Additional file 2: Method S1. Tools, command lines and thresholds used in processing of raw reads (fastq) to gVCF.
DOI: 10.6084/m9.figshare.25157804.v1
title: Additional file 2 of Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

description: Additional file 2: Method S1. Tools, command lines and thresholds used in processing of raw reads (fastq) to gVCF.
DOI: 10.6084/m9.figshare.26677679
title: Additional file 4 of Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

description: Additional file 4: Method S3. Bash script for determining ancestral alleles using the likelihood ratio test steps 1 to 3 in Additional file 3: Method S2.
DOI: 10.6084/m9.figshare.26677679.v1
title: Additional file 4 of Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

description: Additional file 4: Method S3. Bash script for determining ancestral alleles using the likelihood ratio test steps 1 to 3 in Additional file 3: Method S2.
DOI: 10.6084/m9.figshare.26677682
title: Additional file 5 of Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

description: Additional file 5: Table S8. Summary of likelihood ratios for major and minor alleles designated as ancestral alleles and number of species contributing to the likelihood ratio. Table S9. Annotation of variant positions of ancestral alleles from high confidence and low/failed categories. Table S10. Partitioning of positions of ancestral alleles according to categories in the1000 Bull Genomes project.
DOI: 10.6084/m9.figshare.26677682.v1
title: Additional file 5 of Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

description: Additional file 5: Table S8. Summary of likelihood ratios for major and minor alleles designated as ancestral alleles and number of species contributing to the likelihood ratio. Table S9. Annotation of variant positions of ancestral alleles from high confidence and low/failed categories. Table S10. Partitioning of positions of ancestral alleles according to categories in the1000 Bull Genomes project.
DOI: 10.6084/m9.figshare.25157316
title: Additional file 1 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.25157316.v1
title: Additional file 1 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26677721
title: Additional file 3 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26677721.v1
title: Additional file 3 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26677724
title: Additional file 4 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.26677724.v1
title: Additional file 4 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.26677730
title: Additional file 6 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.26677730.v1
title: Additional file 6 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.26677736
title: Additional file 8 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 8
DOI: 10.6084/m9.figshare.26677736.v1
title: Additional file 8 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 8
DOI: 10.6084/m9.figshare.26677739
title: Additional file 9 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 9
DOI: 10.6084/m9.figshare.26677739.v1
title: Additional file 9 of Identification of candidate genes associated with host-seeking behavior in the parasitoid wasp Diachasmimorpha longicaudata

description: Supplementary Material 9
DOI: 10.6084/m9.figshare.25157811
title: Additional file 2 of Rare subclonal sequencing of breast cancers indicates putative metastatic driver mutations are predominately acquired after dissemination

description: Additional file 2. Contains data on the regions-of-interest assayed in each UDS-UMI/UDG panel (“UDS panel designs”), all variants called by UDS-UMI/UDG (“All UDS-UMI/UDG variants” and “UDS-UMI/UDG data dictionary”), metastasis-specific mutations as determined by WES (“MetSpec WES mutations”), information on the detection (or lack thereof) of metastasis-specific putative metastatic driver mutations within primary tumors (“UDS MetSpec Detection”), and CCFs of putative metastatic driver mutations used in Figs. 3 and 4 (“CCFs of visualized mutations”).
DOI: 10.6084/m9.figshare.25157811.v1
title: Additional file 2 of Rare subclonal sequencing of breast cancers indicates putative metastatic driver mutations are predominately acquired after dissemination

description: Additional file 2. Contains data on the regions-of-interest assayed in each UDS-UMI/UDG panel (“UDS panel designs”), all variants called by UDS-UMI/UDG (“All UDS-UMI/UDG variants” and “UDS-UMI/UDG data dictionary”), metastasis-specific mutations as determined by WES (“MetSpec WES mutations”), information on the detection (or lack thereof) of metastasis-specific putative metastatic driver mutations within primary tumors (“UDS MetSpec Detection”), and CCFs of putative metastatic driver mutations used in Figs. 3 and 4 (“CCFs of visualized mutations”).
DOI: 10.6084/m9.figshare.25157380
title: Additional file 1 of Comparing the gut microbiota of Sichuan golden monkeys across multiple captive and wild settings: roles of anthropogenic activities and host factors

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.25157380.v1
title: Additional file 1 of Comparing the gut microbiota of Sichuan golden monkeys across multiple captive and wild settings: roles of anthropogenic activities and host factors

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.25157293
title: Additional file 1 of The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery

description: Additional file 1: Table S1. Table of number of genes, and genes in KEGG signaling pathways contained in HiPathia R package sharing an increasing number of RP-HPO terms.
DOI: 10.6084/m9.figshare.25157293.v1
title: Additional file 1 of The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery

description: Additional file 1: Table S1. Table of number of genes, and genes in KEGG signaling pathways contained in HiPathia R package sharing an increasing number of RP-HPO terms.
DOI: 10.6084/m9.figshare.25157828
title: Additional file 2 of The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery

description: Additional file 2: Table S2. Table of RP mechanistic map circuits with their code, name (Pathway: effector node), their hallmark/s module/s and the UniprotKB and Gene Ontology functions tagging them.
DOI: 10.6084/m9.figshare.25157828.v1
title: Additional file 2 of The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery

description: Additional file 2: Table S2. Table of RP mechanistic map circuits with their code, name (Pathway: effector node), their hallmark/s module/s and the UniprotKB and Gene Ontology functions tagging them.
DOI: 10.6084/m9.figshare.26677823
title: Additional file 3 of The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery

description: Additional file 3: Table S3. Table with DrugBank 5.1.8 database filtered by approved human drugs with known pharmacological action and known protein targets.
DOI: 10.6084/m9.figshare.26677823.v1
title: Additional file 3 of The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery

description: Additional file 3: Table S3. Table with DrugBank 5.1.8 database filtered by approved human drugs with known pharmacological action and known protein targets.
DOI: 10.15468/dl.unx7mt
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is one of (Description of two new species in the Ixodes ricinus complex from the New World (Acari: Ixodidae), and redescription of Ixodes affinis Neumann, 1899)"
 ]
}

 The dataset includes 36 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039958-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13241584
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.26j38g
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rissoina bertholleti",
 "Country is Türkiye",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039959-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.brs4yu
title: Occurrence Download

description: A dataset containing 2988967 records in GBIF matching the query:
SELECT
 -- Dimensions:
 PRINTF('%04d-%02d', "year", "month") AS yearMonth,
 GBIF_EEARGCode(
 50000,
 decimalLatitude,
 decimalLongitude,
 COALESCE(coordinateUncertaintyInMeters, 50000)
 ) AS eeaCellCode,
 speciesKey,
 species,
 -- Measurements
 COUNT(*) AS occurrences,
 MIN(COALESCE(coordinateUncertaintyInMeters, 50000)) AS minCoordinateUncertaintyInMeters,
 MIN(GBIF_TemporalUncertainty(eventDate, null)) AS minTemporalUncertainty
FROM
 occurrence
WHERE occurrenceStatus = 'PRESENT'
 AND countryCode = 'DE'
 AND "year" &gt;= 2000
 AND classKey = 212
-- AND kingdomKey = 1
 AND hasCoordinate = TRUE
 AND (coordinateUncertaintyInMeters &lt;= 50000 OR coordinateUncertaintyInMeters IS NULL)
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND "month" IS NOT NULL
GROUP BY
 yearMonth,
 eeaCellCode,
 speciesKey,
 species;

 The dataset's 2988967 records were derived from 945 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039938-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.