cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.j3jy2p
title: Occurrence Download

description: A dataset containing 473 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Caragana jubata (Pall.) Poir."
 ]
}

 The dataset includes 473 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004128-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qmerwe
title: Occurrence Download

description: A dataset containing 2479 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is International Barcode of Life project (iBOL)",
 "Year 1000-1908"
 ]
}

 The dataset includes 2479 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026807-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v58hsh
title: Occurrence Download

description: A dataset containing 188816 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ilex Tourn. ex L."
 ]
}

 The dataset includes 188816 records from 595 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004130-150528172251762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wyg7t3
title: Occurrence Download

description: A dataset containing 145 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.28_1",
 "TaxonKey is Salix iliensis"
 ]
}

 The dataset includes 145 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041056-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccrm6fz
title: CCDC 703651: Experimental Crystal Structure Determination

description: Related Article: M.Jimenez-Tenorio, M.C.Puerta, I.Salcedo, P.Valerga, I.de los Rios, K.Mereiter|2009|Dalton Trans.||1842|doi:10.1039/b818784c
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccrm6g0
title: CCDC 703652: Experimental Crystal Structure Determination

description: Related Article: M.Jimenez-Tenorio, M.C.Puerta, I.Salcedo, P.Valerga, I.de los Rios, K.Mereiter|2009|Dalton Trans.||1842|doi:10.1039/b818784c
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccrm6h1
title: CCDC 703653: Experimental Crystal Structure Determination

description: Related Article: M.Jimenez-Tenorio, M.C.Puerta, I.Salcedo, P.Valerga, I.de los Rios, K.Mereiter|2009|Dalton Trans.||1842|doi:10.1039/b818784c
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.28776825.v1
title: Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms

description: Alga toxins have recently emerged as environmental risk factors to multiple human health issues. Mitochondrial toxicity is an essential element in the field of ecotoxicology, it is necessary to screen and manage mitochondrial toxicants from common alga toxins. To overcome the limitations of traditional animal and cell experiments, computational toxicology is increasingly emphasized. In this study, all the publicly available datasets were compiled to create the largest mitochondrial toxicity dataset to date, establishing a robust and high-performance QSAR screening model. The model couples and filters 12 molecular fingerprints and 318 descriptors as features, capturing more information about molecular structure and properties. By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. Additionally, the efficacy of MACCS fingerprints in representing mitochondrial toxicants was established, and a mechanistic analysis of the identified model based on the SHAP method and 11 structural alerts uncovered in this study was conducted, enhancing the interpretability of this model. This study highlights the key roles of lipophilic structures such as aromatic rings and long hydrocarbon chains and their related physicochemical properties in predicting toxicity outcomes. The mitochondrial toxicity of six algal toxins was predicted by employing this model, and the results indicating that two of them possess mitochondrial toxic effects. This model has high reliability and accuracy, making it applicable for predicting mitochondrial toxicity of more marine biotoxins.
DOI: 10.6084/m9.figshare.28776825
title: Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms

description: Alga toxins have recently emerged as environmental risk factors to multiple human health issues. Mitochondrial toxicity is an essential element in the field of ecotoxicology, it is necessary to screen and manage mitochondrial toxicants from common alga toxins. To overcome the limitations of traditional animal and cell experiments, computational toxicology is increasingly emphasized. In this study, all the publicly available datasets were compiled to create the largest mitochondrial toxicity dataset to date, establishing a robust and high-performance QSAR screening model. The model couples and filters 12 molecular fingerprints and 318 descriptors as features, capturing more information about molecular structure and properties. By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. Additionally, the efficacy of MACCS fingerprints in representing mitochondrial toxicants was established, and a mechanistic analysis of the identified model based on the SHAP method and 11 structural alerts uncovered in this study was conducted, enhancing the interpretability of this model. This study highlights the key roles of lipophilic structures such as aromatic rings and long hydrocarbon chains and their related physicochemical properties in predicting toxicity outcomes. The mitochondrial toxicity of six algal toxins was predicted by employing this model, and the results indicating that two of them possess mitochondrial toxic effects. This model has high reliability and accuracy, making it applicable for predicting mitochondrial toxicity of more marine biotoxins.
DOI: 10.15468/dl.yz6krn
title: Occurrence Download

description: A dataset containing 102081 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is India Biodiversity Portal publication grade dataset"
 ]
}

 The dataset includes 102081 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004292-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13144/lil-0375
title: Enquête Consommation alimentaire des ménages - 1970

description: L'enquête sur la consommation alimentaire de 1970 a permis de recueillir auprès des 8149 ménages (25 150 individus) répondants, toute l'information relative aux approvisionnements alimentaires et au repas pris hors domiciles pour une semaine. Pour tenir compte des aspects saisonniers l'enquête se déroule sur toute l'année à l'exception d'une quinzaine en aout et une en décembre. Le ménage est décrit par ses caractéristiques socio-démographiques (CSP de la personne de référence, nombre d'individus ...) ainsi que le revenu. Pour chaque achat de produit alimentaire, la nature des données recueillies concerne la désignation précise du produit (170 produits différents sont répertoriés en 1969), la dépense et la quantité correspondante ainsi que le lieu d'achat. Pour les produits obtenus gratuitement ne sont relevées que la désignation du produit et la quantité correspondante. La valorisation est effectuée par l'enquêteur à l'aide des prix de détail pratiqués sur le marché local. Pour les repas pris hors domicile sont relevés le lieu de consommation (restaurant, cantine, invitation dans un autre ménage ...), le moment de la consommation (midi ou soir), la dépense occasionnée pour les repas payants et le nombre de convives correspondant à cette dépense. Les repas pris dans le logement par des personnes extérieures au ménage sont également notés.
DOI: 10.13144/lil-0376
title: Enquête Consommation alimentaire des ménages - 1971

description: L'enquête sur la consommation alimentaire de 1971 a permis de recueillir auprès des 8047 ménages (24 820 individus) répondants, toute l'information relative aux approvisionnements alimentaires et au repas pris hors domiciles pour une semaine. Pour tenir compte des aspects saisonniers l'enquête se déroule sur toute l'année à l'exception d'une quinzaine en aout et une en décembre. Le ménage est décrit par ses caractéristiques socio-démographiques (CSP de la personne de référence, nombre d'individus ...) ainsi que le revenu. Pour chaque achat de produit alimentaire, la nature des données recueillies concerne la désignation précise du produit (170 produits différents sont répertoriés en 1969), la dépense et la quantité correspondante ainsi que le lieu d'achat. Pour les produits obtenus gratuitement ne sont relevées que la désignation du produit et la quantité correspondante. La valorisation est effectuée par l'enquêteur à l'aide des prix de détail pratiqués sur le marché local. Pour les repas pris hors domicile sont relevés le lieu de consommation (restaurant, cantine, invitation dans un autre ménage ...), le moment de la consommation (midi ou soir), la dépense occasionnée pour les repas payants et le nombre de convives correspondant à cette dépense. Les repas pris dans le logement par des personnes extérieures au ménage sont également notés.
DOI: 10.13144/lil-0378
title: Enquête Consommation alimentaire des ménages - 1976

description: L'enquête sur la consommation alimentaire de 1976 a permis de recueillir auprès des 8715 ménages (25 869 individus) répondants, toute l'information relative aux approvisionnements alimentaires et au repas pris hors domiciles pour une semaine. Pour tenir compte des aspects saisonniers l'enquête se déroule sur toute l'année à l'exception d'une quinzaine en aout et une en décembre. Le ménage est décrit par ses caractéristiques socio-démographiques (CSP de la personne de référence, nombre d'individus ...) ainsi que le revenu. Pour chaque achat de produit alimentaire, la nature des données recueillies concerne la désignation précise du produit (170 produits différents sont répertoriés en 1969), la dépense et la quantité correspondante ainsi que le lieu d'achat. Pour les produits obtenus gratuitement ne sont relevées que la désignation du produit et la quantité correspondante. La valorisation est effectuée par l'enquêteur à l'aide des prix de détail pratiqués sur le marché local. Pour les repas pris hors domicile sont relevés le lieu de consommation (restaurant, cantine, invitation dans un autre ménage ...), le moment de la consommation (midi ou soir), la dépense occasionnée pour les repas payants et le nombre de convives correspondant à cette dépense. Les repas pris dans le logement par des personnes extérieures au ménage sont également notés.
DOI: 10.15468/dl.nt9wmp
title: Occurrence Download

description: A dataset containing 657 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capros aper (Linnaeus, 1758)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen, Material sample)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 657 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004298-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.87vnbe
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Populus tristis Fisch. ex Dippel",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042055-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vvjxvc
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Impatiens echinosperma H.Perrier"
 ]
}

 The dataset includes 20 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032063-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f3jwyy
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Campuloclinium parvulum (Glaz. ex B.L.Rob.) R.King & H.Rob."
 ]
}

 The dataset includes 15 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008169-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gk8ecd
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Impatiens elegans Bedd."
 ]
}

 The dataset includes 12 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032083-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nbv9km
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Crossoptilon mantchuricum Swinhoe, 1863",
 "Year 2019-2024"
 ]
}

 The dataset includes 62 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069755-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yq5zvs
title: Occurrence Download

description: A dataset containing 32262 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Rwanda",
 "HasCoordinate is true"
 ]
}

 The dataset includes 32262 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008170-150615163101818/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xz78st
title: Occurrence Download

description: A dataset containing 912 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acacia bakeri Maiden"
 ]
}

 The dataset includes 912 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032089-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yjaw2k
title: Occurrence Download

description: A dataset containing 2656 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Marine plankton Metagenome"
 ]
}

 The dataset includes 2656 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016189-240216155721649/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zhgwvt
title: Occurrence Download

description: A dataset containing 124 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinguicula calyptrata Kunth"
 ]
}

 The dataset includes 124 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008170-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0174969.10fu
title: SH0174969.10FU

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/sh0174970.10fu
title: SH0174970.10FU

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/sh0174971.10fu
title: SH0174971.10FU

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/sh0174972.10fu
title: SH0174972.10FU

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/sh0174973.10fu
title: SH0174973.10FU

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.