cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.k686jk
title: Occurrence Download

description: A dataset containing 21273 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Tecticornia"
 ]
}

 The dataset includes 21273 records from 86 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003624-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13018/bmr50549
title: Chemical shift assignment of End Binding Protein 1
DOI: 10.13018/bmr50550
title: 13C and 15N Chemical Shift Assignments for the Spherical Assembly of the Rous Sarcoma Virus Capsid Protein
DOI: 10.13018/bmr50552
title: structure of SRSF1 RRM1 bound to RNA (AACAAA)
DOI: 10.13018/bmr50553
title: 15N relaxation measurements of an FG Nucleoporin in crowded conditions
DOI: 10.13018/bmr50554
title: C8-AcpP FabF titration
DOI: 10.13018/bmr50555
title: Backbone assignment of B-domain of bacterial Fatty acid kinase bound to palmitic acid
DOI: 10.13018/bmr50556
title: A121I-FakB1 bound to palmitic acid
DOI: 10.13018/bmr50557
title: SARS-CoV-2 nucleoprotein 175-263
DOI: 10.13018/bmr50558
title: 1H, 13C and 15N Backbone Chemical Shift Assignments of the N-terminal and Central Intrinsically Disordered Domains of SARS-CoV-2 Nucleoprotein
DOI: 10.13018/bmr50559
title: Titration of C8-AcpP with the E. coli thioesterase 1 TesA
DOI: 10.13018/bmr50560
title: Titration of AcpP with the E. coli 3-oxoacyl-[acyl-carrier-protein] reductase FabG
DOI: 10.13018/bmr50561
title: Titration of C8-AcpP with the E. coli Enoyl-[acyl-carrier-protein] reductase FabI
DOI: 10.13018/bmr50563
title: Mutation G132S enhances resistance of Mycobacterium tuberculosis b-lactamase against sulbactam
DOI: 10.13018/bmr50564
title: Mutation G269S enhances resistance of Mycobacterium tuberculosis b-lactamase against sulbactam
DOI: 10.13018/bmr50565
title: Mutation A55E enhances resistance of Mycobacterium tuberculosis b-lactamase against sulbactam
DOI: 10.13018/bmr50566
title: Mutation D172N enhances resistance of Mycobacterium tuberculosis b-lactamase against sulbactam
DOI: 10.5281/zenodo.18662383
title: Supplementary Material for "Research topics and trends about MIMIC-IV, a large ICU database relevant for critical care nursing"

description: Abstract

This dataset contains the bibliometric and keyword-frequency data underlying a systematic review of publications related to the MIMIC-IV clinical database from 2021 to 2024. Records were retrieved from the Science Citation Index Expanded (SCI-EXPANDED) in the Web of Science Core Collection using a structured topic search strategy. Following eligibility screening and front-page filtering, 1,150 research articles were retained for analysis.

The dataset was processed in Microsoft Excel 365 and was designed to support transparent, reproducible identification of dominant research themes in MIMIC-IV literature. It provides standardised frequency counts and rankings of keywords extracted from multiple bibliographic metadata sources.

Data Collection and Processing

Bibliographic records were downloaded in plain-text format from Web of Science and imported into Microsoft Excel. Keywords and terms were extracted from four metadata fields: article titles, abstracts, author keywords, and Keywords Plus.

A word-frequency analysis was conducted to quantify the prevalence of terms across the publication corpus. All terms were standardised to ensure consistency in spelling and format. High-frequency terms were then compiled into a consolidated word bank.

Research themes were identified through expert-led qualitative clustering of the most frequent keywords, prioritising clinical relevance and interpretive validity.

Dataset Structure

The dataset is provided as a Microsoft Excel workbook containing five worksheets:





TitleKeywords extracted from article titles.




AbstractKeywords extracted from article abstracts.




Author KeywordsKeywords supplied by authors.




Keyword PlusKeywords generated by the Web of Science database.




Word BankConsolidated list of high-frequency keywords from all sources.



Variables and Columns

Each worksheet contains the following variables:

Common Variables





Words: Individual keywords or terms extracted from bibliographic records.




TP (Total Publications): Number of publications in which a given term appears.



Additional Variables (Title, Abstract, Author Keywords, Keyword Plus)





Rank: Position of the term based on frequency.




% (Percentage): Proportion of publications containing the term relative to the total dataset (n = 1,150).




Rank (%): Ranking and percentile rank.



The Word Bank sheet includes only Words and TP, as it functions as a reference pool for thematic analysis.

Intended Use

This dataset is intended for:





Bibliometric and scientometric research




Mapping research trends in critical care and clinical informatics




Secondary analyses of MIMIC-IV literature




Methodological studies in keyword-based literature reviews




Nursing and healthcare informatics research



It enables users to replicate, validate, or extend the thematic analysis presented in the associated publication.
DOI: 10.13018/bmr50567
title: Structure of PCSK9 antagonist P9-38
DOI: 10.5281/zenodo.18662382
title: Supplementary Material for "Research topics and trends about MIMIC-IV, a large ICU database relevant for critical care nursing"

description: Abstract

This dataset contains the bibliometric and keyword-frequency data underlying a systematic review of publications related to the MIMIC-IV clinical database from 2021 to 2024. Records were retrieved from the Science Citation Index Expanded (SCI-EXPANDED) in the Web of Science Core Collection using a structured topic search strategy. Following eligibility screening and front-page filtering, 1,150 research articles were retained for analysis.

The dataset was processed in Microsoft Excel 365 and was designed to support transparent, reproducible identification of dominant research themes in MIMIC-IV literature. It provides standardised frequency counts and rankings of keywords extracted from multiple bibliographic metadata sources.

Data Collection and Processing

Bibliographic records were downloaded in plain-text format from Web of Science and imported into Microsoft Excel. Keywords and terms were extracted from four metadata fields: article titles, abstracts, author keywords, and Keywords Plus.

A word-frequency analysis was conducted to quantify the prevalence of terms across the publication corpus. All terms were standardised to ensure consistency in spelling and format. High-frequency terms were then compiled into a consolidated word bank.

Research themes were identified through expert-led qualitative clustering of the most frequent keywords, prioritising clinical relevance and interpretive validity.

Dataset Structure

The dataset is provided as a Microsoft Excel workbook containing five worksheets:





TitleKeywords extracted from article titles.




AbstractKeywords extracted from article abstracts.




Author KeywordsKeywords supplied by authors.




Keyword PlusKeywords generated by the Web of Science database.




Word BankConsolidated list of high-frequency keywords from all sources.



Variables and Columns

Each worksheet contains the following variables:

Common Variables





Words: Individual keywords or terms extracted from bibliographic records.




TP (Total Publications): Number of publications in which a given term appears.



Additional Variables (Title, Abstract, Author Keywords, Keyword Plus)





Rank: Position of the term based on frequency.




% (Percentage): Proportion of publications containing the term relative to the total dataset (n = 1,150).




Rank (%): Ranking and percentile rank.



The Word Bank sheet includes only Words and TP, as it functions as a reference pool for thematic analysis.

Intended Use

This dataset is intended for:





Bibliometric and scientometric research




Mapping research trends in critical care and clinical informatics




Secondary analyses of MIMIC-IV literature




Methodological studies in keyword-based literature reviews




Nursing and healthcare informatics research



It enables users to replicate, validate, or extend the thematic analysis presented in the associated publication.
DOI: 10.13018/bmr50568
title: 1H and 15N assignments for 14-residues peptide that is cleaved by MPro
DOI: 10.13018/bmr50569
title: 1H and 15N assignments for 14-residue peptide after cleavage by MPro
DOI: 10.13018/bmr50570
title: PfAlu RNA Helix3
DOI: 10.13018/bmr50571
title: PfAlu RNA Helix4
DOI: 10.13018/bmr50572
title: PfAlu RNA Helix5
DOI: 10.13018/bmr50574
title: 1H, 15N and 13C sequence-specific backbone assignment of the MAP Kinase Binding Domain of Dual Specificity Phosphatase 1
DOI: 10.13018/bmr50575
title: Cyclosporin E in chloroform
DOI: 10.13018/bmr50576
title: NfsB + nicotinate
DOI: 10.13018/bmr50579
title: 1H, 13C, and 15N resonance assignments of WRKY33-C(V352-A422) from Arabidopsis thaliana
DOI: 10.13018/bmr50580
title: WRKY33-C(331-422)
DOI: 10.48580/dgtz3.v10
title: Additional Assessment Report - Crucea North Wind Farm 99 MW
DOI: 10.48580/dgwqb.v2
title: Checklist of species indicated for Leningrad Oblast in Illyustrirovannyi Opredelitel Rasteniy Leningradskoy Oblasti (Averyanov et al., 2006): accepted names
DOI: 10.13018/bmr50581
title: combined_WRKY33-C
DOI: 10.15468/dl.n36bm4
title: Occurrence Download

description: A dataset containing 1124092 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sus scrofa"
 ]
}

 The dataset includes 1124092 records from 3268 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003564-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1413519.10fu
title: SH1413519.10FU

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/sh1413520.10fu
title: SH1413520.10FU

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/sh1413522.10fu
title: SH1413522.10FU

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/sh1413524.10fu
title: SH1413524.10FU

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/sh1413537.10fu
title: SH1413537.10FU

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/sh1413538.10fu
title: SH1413538.10FU

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/sh1413539.10fu
title: SH1413539.10FU

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/sh1413541.10fu
title: SH1413541.10FU

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/sh1413543.10fu
title: SH1413543.10FU

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.y6b5n8
title: Occurrence Download

description: A dataset containing 1118560 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is one of (India)"
 ]
}

 The dataset includes 1118560 records from 1310 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006335-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dh6dd9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Fissidens arcticus)",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025538-260208012135463/datasets/export for details.
DOI: 10.15468/dl.5vre8c
title: Occurrence Download

description: A dataset containing 83 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anomodon rugelii)",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 83 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025539-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pq8xrd
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sphecotera Vieillot, 1816"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007655-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60712/si-id48646.1
title: StrainInfo SI-ID 48646.1

description: StrainInfo dataset 48646 about a strain of Halothermothrix orenii. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id48647.1
title: StrainInfo SI-ID 48647.1

description: StrainInfo dataset 48647 about a strain of Halanaerobacter chitinivorans. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id48648.1
title: StrainInfo SI-ID 48648.1

description: StrainInfo dataset 48648 about a strain of Brachybacterium nesterenkovii. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.