cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.gq2pat
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ambrosiodmus rubricollis Wood & Bright, 1992",
 "HasCoordinate is true"
 ]
}

 The dataset includes 59 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002598-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15106237
title: Beyond the Gene in Genetics: How Isoform-Resolved Analysis Empowers the Study of Both Common and Rare Genetic Variation

description: This record contains genetic association data and annotations used in the "Exploration of Genes and Isoforms in Genetic Data" interactive web application (https://services.healthtech.dtu.dk/shiny/qtl_gwas/), complementing the publication named "Beyond the Gene in Genetics: How Isoform-Resolved Analysis Empowers the Study of Both Common and Rare Genetic Variation" (https://www.medrxiv.org/content/10.1101/2025.03.31.25324931v1). 



qtl_gwas_data.Rdata / qtl_gwas_data.gz:



Contains:



Significant QTLs processed from the EBI QTL database (geneListSigAnnot, txListSigAnnot)

Significant GWAS traits strictly colocalized with at least one significant QTL (gwasHitsFilt)



Available in both R (.Rdata) and CSV formats



gencode.v39.annotation.gtf.txinfo.Rdata / gencode.v39.annotation.gtf.txinfo.csv.gz:



Contains:



GENCODE version 39 gene and transcript annotations



Used for mapping and annotating gene identifiers

Available in both R (.Rdata) and CSV formats




These datasets support the exploration of genetic associations across multiple studies, providing both gene and transcript-level information integrated with GWAS data. The data is structured to facilitate both programmatic access through R (.Rdata), and general-purpose analysis through standard tabular (CSV) formats for flexibility in analysis approaches.

For more information and use cases, please visit the web application or refer to the associated publication.
DOI: 10.5281/zenodo.15106238
title: Beyond the Gene in Genetics: How Isoform-Resolved Analysis Empowers the Study of Both Common and Rare Genetic Variation

description: This record contains genetic association data and annotations used in the "Exploration of Genes and Isoforms in Genetic Data" interactive web application (https://services.healthtech.dtu.dk/shiny/qtl_gwas/), complementing the publication named "Beyond the Gene in Genetics: How Isoform-Resolved Analysis Empowers the Study of Both Common and Rare Genetic Variation" (https://www.medrxiv.org/content/10.1101/2025.03.31.25324931v1). 



qtl_gwas_data.Rdata / qtl_gwas_data.gz:



Contains:



Significant QTLs processed from the EBI QTL database (geneListSigAnnot, txListSigAnnot)

Significant GWAS traits strictly colocalized with at least one significant QTL (gwasHitsFilt)



Available in both R (.Rdata) and CSV formats



gencode.v39.annotation.gtf.txinfo.Rdata / gencode.v39.annotation.gtf.txinfo.csv.gz:



Contains:



GENCODE version 39 gene and transcript annotations



Used for mapping and annotating gene identifiers

Available in both R (.Rdata) and CSV formats




These datasets support the exploration of genetic associations across multiple studies, providing both gene and transcript-level information integrated with GWAS data. The data is structured to facilitate both programmatic access through R (.Rdata), and general-purpose analysis through standard tabular (CSV) formats for flexibility in analysis approaches.

For more information and use cases, please visit the web application or refer to the associated publication.
DOI: 10.5281/zenodo.12175912
title: Scorpio Gene-Taxa Benchmark Dataset

description:  
















We used the Woltka pipeline to compile the complete Basic genome dataset, consisting of 4634 genomes, with each genus represented by a single genome. After downloading all coding sequences (CDS) from the NCBI database, we extracted 8 million distinct CDS, focusing on bacteria and archaea and excluding viruses and fungi due to inadequate gene information.

To maintain accuracy, we excluded hypothetical proteins, uncharacterized proteins, and sequences without gene labels. We addressed issues with gene name inconsistencies in NCBI by keeping only genes with more than 1000 samples and ensuring each phylum had at least 350 sequences. This resulted in a curated dataset of 800,318 gene sequences from 497 genes across 2046 genera.

We created four datasets to evaluate our model: a training set (Train_set), a test set (Test_set) with different samples but the same genus and gene as the training set, a Taxa_out_set excluding 18 phyla present in the training set but from different phyla, and a Gene_out_set excluding 60 genes from the training set but from the same phyla. We ensured each CDS had only one representation per genome, removing genes with multiple representations within the same species.
description: test.fasta :  Contains sequences for model testing.




gene_out.fasta: Includes sequences excluded based on gene criteria for model evaluation.




taxa_out.fasta :Includes sequences excluded based on taxonomic criteria for model evaluation.


val.fasta: Contains sequences for model validation .



train.fasta: Contains sequences for model training.




metadata.csv: Contains metadata information for sequences in the FASTA files.




hierarchical-level.txt : Determines hierarchical levels for triplet training and hierarchical sampling required for Scorpio training.



General Description of FASTA Files:

FASTA files contain sequence data where each sequence entry begins with a header line, starting with ">" followed by a sequence identifier (seqid). 

Retrieving Information from Metadata:

To retrieve metadata information based on the sequence ID (seqid) from the FASTA files:



Extract the seqid from the header of the FASTA file

Use the extracted seqid to look up the corresponding row in the metadata.csv file.


 

 

@article{refahi2025enhancing,
  title={Enhancing nucleotide sequence representations in genomic analysis with contrastive optimization},
  author={Refahi, Mohammadsaleh and Sokhansanj, Bahrad A and Mell, Joshua C and Brown, James R and Yoo, Hyunwoo and Hearne, Gavin and Rosen, Gail L},
  journal={Communications Biology},
  volume={8},
  number={1},
  pages={517},
  year={2025},
  publisher={Nature Publishing Group UK London}
}
DOI: 10.5281/zenodo.12964684
title: Scorpio Gene-Taxa Benchmark Dataset

description:  
















We used the Woltka pipeline to compile the complete Basic genome dataset, consisting of 4634 genomes, with each genus represented by a single genome. After downloading all coding sequences (CDS) from the NCBI database, we extracted 8 million distinct CDS, focusing on bacteria and archaea and excluding viruses and fungi due to inadequate gene information.

To maintain accuracy, we excluded hypothetical proteins, uncharacterized proteins, and sequences without gene labels. We addressed issues with gene name inconsistencies in NCBI by keeping only genes with more than 1000 samples and ensuring each phylum had at least 350 sequences. This resulted in a curated dataset of 800,318 gene sequences from 497 genes across 2046 genera.

We created four datasets to evaluate our model: a training set (Train_set), a test set (Test_set) with different samples but the same genus and gene as the training set, a Taxa_out_set excluding 18 phyla present in the training set but from different phyla, and a Gene_out_set excluding 60 genes from the training set but from the same phyla. We ensured each CDS had only one representation per genome, removing genes with multiple representations within the same species.
description: test.fasta :  Contains sequences for model testing.




gene_out.fasta: Includes sequences excluded based on gene criteria for model evaluation.




taxa_out.fasta :Includes sequences excluded based on taxonomic criteria for model evaluation.


val.fasta: Contains sequences for model validation .



train.fasta: Contains sequences for model training.




metadata.csv: Contains metadata information for sequences in the FASTA files.




hierarchical-level.txt : Determines hierarchical levels for triplet training and hierarchical sampling required for Scorpio training.



General Description of FASTA Files:

FASTA files contain sequence data where each sequence entry begins with a header line, starting with ">" followed by a sequence identifier (seqid). 

Retrieving Information from Metadata:

To retrieve metadata information based on the sequence ID (seqid) from the FASTA files:



Extract the seqid from the header of the FASTA file

Use the extracted seqid to look up the corresponding row in the metadata.csv file.


 

 

@article{refahi2025enhancing,
  title={Enhancing nucleotide sequence representations in genomic analysis with contrastive optimization},
  author={Refahi, Mohammadsaleh and Sokhansanj, Bahrad A and Mell, Joshua C and Brown, James R and Yoo, Hyunwoo and Hearne, Gavin and Rosen, Gail L},
  journal={Communications Biology},
  volume={8},
  number={1},
  pages={517},
  year={2025},
  publisher={Nature Publishing Group UK London}
}
DOI: 10.5281/zenodo.15123623
title: Continuum-estimated lattice susceptibilites of order 2 and 4

description: Set of continuum-estimated lattice susceptibilities of order 2 and 4, as well as $T$-derivatives of order 2 susceptibilities, obtained with the 4stout action on lattices with $N_\tau=10, 12, 16, 20, 24$ timeslices with aspect ratio $LT = 4$, except for the $64^4 \times 24$ lattice.All quantities are provided for a range $T = 30 - 800$ MeV, with at step $\Delta T=1$ MeV.

Each susceptibility is produced a cubic spline fit of 3 datasets:



HRG data with fictitious 5-10% at low temperature

cubic-spline spline fitted lattice data at intermediate temperature

$1/T$-polynomial fitted of lattice data at high temperature


Both lattice-fitted datasets are also continuum-extrapolated using several timeslice lattice simulation results.

When using this data, please cite also the following work (contain details about the fitting procedure and the lattice data, respectively):



A. Abuali, S. Borsányi, Z. Fodor, J. Jahan, M. Kahangirwe, P. Parotto, A. Pásztor, C. Ratti, H. Shah and S.A. Trabulsi, arXiv:2504.01881 [hep-lat, het-ph] 

R. Bellwied, S. Borsányi, Z. Fodor, S.D. Katz, A. Pásztor, C. Ratti, K.K. Szabo, Phys.Rev.D 92 (2015) 11, 114505 [hep-lat]
DOI: 10.15468/dl.eqzeru
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Megachile victoriana Mitchell, 1933, Megachile victoriana Mitchell, 1933)",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Material sample)"
 ]
 }
 },
 "CoordinateUncertaintyInMeters is less than or equal to 2000",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002599-250402121839773/datasets/export for details.
DOI: 10.15468/dl.9hn5dv
title: Occurrence Download

description: A dataset containing 2137310 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is United States of America",
 "Geometry POLYGON((-120.75996 48.95257,-122.28856 44.31533,-121.29195 41.30028,-117.18093 36.55466,-108.78222 35.76699,-103.74955 36.37091,-103.35295 43.86796,-104.47414 45.28762,-104.85674 46.4614,-104.22765 48.97774,-120.75996 48.95257))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Spermophilus lateralis (Say, 1823), Lepus americanus Erxleben, 1777, Didelphis marsupialis virginiana (Kerr, 1792), Sylvilagus floridanus (J.A.Allen, 1890), Neotomodon alstoni Merriam, 1898, Microtus mexicanus (Saussure, 1861), Peromyscus beatae Thomas, 1903, Peromyscus maniculatus (Wagner, 1845), Didelphis marsupialis Linnaeus, 1758, Quiscalus quiscula (Linnaeus, 1758), Procyon lotor (Linnaeus, 1758), Odocoileus virginianus (Zimmermann, 1780), Molothrus ater (Boddaert, 1783), Agelaius phoeniceus (Linnaeus, 1766), Equus caballus Linnaeus, 1758, Cardinalis cardinalis (Linnaeus, 1758), Canis lupus Linnaeus, 1758, Zonotrichia albicollis (J.F.Gmelin, 1789), Vulpes vulpes (Linnaeus, 1758), Urocyon cinereoargenteus (Schreber, 1775), Cerdocyon thous (Linnaeus, 1766), Tayassu pecari (Link, 1795), Pecari tajacu (Linnaeus, 1758), Cuniculus paca (Linnaeus, 1766), Dasypus novemcinctus Linnaeus, 1758, Tamandua tetradactyla (Linnaeus, 1758), Kinosternon scorpioides (Linnaeus, 1766), Colinus virginianus (Linnaeus, 1758), Sigmodon hispidus Say & Ord, 1825, Bos taurus Linnaeus, 1758, Canis familiaris Linnaeus, 1758, Didelphis aurita (Wied-Neuwied, 1826), Neotoma cinerea (Ord, 1815), Urocitellus columbianus (Ord, 1815), Eutamias amoenus (Allen, 1890), Citellus lateralis (Say, 1823), Pitymys pinetorum (Le Conte, 1830), Peromyscus leucopus (Rafinesque, 1818), Microtus pennsylvanicus (Ord, 1815), Sylvilagus audubonii (Baird, 1858), Lepus californicus Gray, 1837, Otospermophilus beecheyi (Richardson, 1829))"
 ]
}

 The dataset includes 2137310 records from 142 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002570-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7tnym8
title: Occurrence Download

description: A dataset containing 314307 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((75.27042 15.24247,77.82545 15.24937,77.84453 17.83063,75.27042 17.84782,75.27042 15.24247))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 314307 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002565-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8un8pv
title: Occurrence Download

description: A dataset containing 8126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Myrmecophaga tridactyla Linnaeus, 1758",
 "Year 1900-2025"
 ]
}

 The dataset includes 8126 records from 162 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002600-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2vkxy7
title: Occurrence Download

description: A dataset containing 114883 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Pygoscelis adeliae (Hombron & Jacquinot, 1841)"
 ]
}

 The dataset includes 114883 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002587-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.abj7g4
title: Occurrence Download

description: A dataset containing 1127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Country is one of (Russian Federation, Svalbard and Jan Mayen, Greenland)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Calidris alba (Pallas, 1764)",
 "Year 2014-2024"
 ]
}

 The dataset includes 1127 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002602-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5rn30m03
title: MassIVE MSV000097516 - Omics Insights into the Effects of Highbush Blueberry and Cranberry Crop Agroecosystems on Honey Bee Health and Physiology
title: Honey bees (Apis mellifera) are essential pollinators in agricultural systems, particularly in fruit-producing agroecosystems such as highbush blueberry and cranberry. However, their health is increasingly compromised by multiple interacting stressors, including pesticide exposure, pathogen infections, and changing nutritional landscapes. To test the hypothesis that distinct agricultural ecosystems, with different combinations of agrochemical exposure, pathogen loads, and floral resources, elicit ecosystem specific, tissue level molecular responses in honey bees, we conducted an integrated multiomics analysis. We combined RNA sequencing, quantitative proteomics, and gut microbiome profiling across three key tissues: head, abdomen, and gut collected from bees in blueberry and cranberry agroecosystems over two field seasons. In parallel, we quantified pesticide residues and pathogen and parasite loads (e.g., Nosema spp., Varroa destructor, and several viruses). Notably, our weighted gene co-expression network analysis (WGCNA) revealed tissue specific coregulated protein modules with ecosystem associated patterns. Bees from blueberry agroecosystems exhibited elevated expression of modules in oxidative phosphorylation, and translation, while those from cranberry agroecosystems showed increased activity in immune pathways and endoplasmic reticulum associated protein processing, indicating potential as robust markers for ecosystem induced physiological adaptation. To further explore the molecular mechanisms underlying different ecosystems, we also conducted the integrative analysis of proteomics, transcriptomics and gut microbiome metagenomics. Gut microbiota composition also differed significantly, with key genera (e.g., Gilliamella, Snodgrassella, Bartonella) correlating with host metabolic and immune modules. These findings underscore the complex, environment-dependent impacts of agroecosystem conditions on bee health. Our study provides a systems level understanding of how combined pesticide, pathogen, and parasitic stressors, mediated by diet and microbiome, shape molecular phenotypes in honey bees, informing strategies for pollinator protection in managed landscapes.
DOI: 10.6073/pasta/442895326274ea09942bd04e6ea92df2
title: Species cover, community biomass, and richness in global grasslands from NutNet (2007–2023): Dominant species predict plant richness and biomass in global grasslands

description: The Nutrient Network (NutNet) is a globally coordinated research initiative designed to investigate the impacts of human-driven alterations in nutrient availability and consumer presence on grassland ecosystems. Data were collected from over 130 herbaceous-dominated sites worldwide, spanning diverse environmental conditions from desert grasslands to arctic tundra. Standardized methodologies were employed across all sites to enable direct comparisons of productivity, diversity, and ecosystem responses. Experimental treatments included nutrient additions to assess co-limitation of plant growth by multiple nutrients, as well as grazer manipulations to examine their role in regulating biomass, species diversity, and community composition. By compiling these cross-site data, NutNet aims to enhance our understanding of productivity-diversity relationships and provide new insights into the ecological consequences of anthropogenic changes to nutrient cycles and food webs at a global scale.
DOI: 10.15468/dl.29r8db
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Megachile victoriana Mitchell, 1933, Megachile victoriana Mitchell, 1933)",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Material sample)"
 ]
 }
 },
 "CoordinateUncertaintyInMeters is less than or equal to 2000"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002603-250402121839773/datasets/export for details.
DOI: 10.15468/dl.hunfm7
title: Occurrence Download

description: A dataset containing 6500 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tamandua tetradactyla (Linnaeus, 1758)",
 "Year 1900-2025"
 ]
}

 The dataset includes 6500 records from 169 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002604-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pe46fy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptothorax torrei (Aguayo, 1931)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002606-250402121839773/datasets/export for details.
DOI: 10.25318/1510004001-eng
title: Use of the minority official language to obtain services or information from government employees, by level of government, age group and gender, among adults in the official language minority population

description: Use of the minority official language to obtain services or information from municipal, provincial and territorial, and federal government employees by age group and gender, Canada, Quebec, Canada outside Quebec, by select provinces and regions, among adults in the official language minority population, 2022.
DOI: 10.15468/dl.nw3p98
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepidosaphes noxia McKenzie, 1946",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002605-250402121839773/datasets/export for details.
DOI: 10.15468/dl.gt6szr
title: Occurrence Download

description: A dataset containing 9432 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Geometry POLYGON((-95.91174 14.36044,-90.32815 14.36044,-90.32815 18.93356,-95.91174 18.93356,-95.91174 14.36044))",
 "HasCoordinate is true",
 "TaxonKey is Molothrus aeneus (Wagler, 1829)",
 "Year 1960-2024"
 ]
}

 The dataset includes 9432 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002607-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dqruvb
title: Occurrence Download

description: A dataset containing 71314 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Country is one of (Russian Federation, Sweden, Norway, Finland)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Calidris temminckii (Leisler, 1812)",
 "Year 2014-2024"
 ]
}

 The dataset includes 71314 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002583-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.