cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15352005
title: Neutron Star Merger Accretion Disk Trajectories for Nucleosynthesis

description: Contained herein are a set of trajectories derived from 30 Lagrangian tracers from the post-neutron-star-merger accretion disk simulation described in Lund et al. 2024 (DOI:10.3847/1538-4357/ad25ef). These tracers are from the simulation labeled b10 in the text.

These tracers have been selected in a way that is agnostic to the actual abundance patterns yielded by the full set of 195k+ tracers. The aim was to obtain a small, significantly more manageable set of tracer that represent conditions in the disk. As such, the conditions for selection were bins in electron fraction (Ye) and radial velocity.The tracers with velocities of less than 0.2c are subdivided (binned) by 0-0.08c (low v) and 0.08-0.2c (high v). While these values capture most of the mass in the disk, it should be noted that higher velocity tracers do exist and are not necessarily captured in this sample. Then, for each of the two velocity "bins", the tracers are further binned by Ye, and one tracer is selected from each bin, for a total of 30.Each tracer has a mass from the simulation. While these are recorded in the file tracer_reference, one should instead use the "assigned mass", which represents the mass contained in the bin. The text file tracer_reference.txt contains the following:

Ye bin represented     ID (unique for each simulation tracer particle)        Velocity bin (either low or high as defined above) the tracer represents and the mass (in solar masses) one should assign to it

Folders and files included:- Trajectories folder: contains individual subdirectories for each of the 30 tracers particles, named trace_{ID_of_tracer}. Within, there are three individual files:    - initx.dat: The initial composition calculated at T=10GK, formatted as         Z | A | Mass Fraction    - metadata.dat: Can mostly be ignored, but contain some identifying information for the ID's tracer.     - trajectory.dat: Thermodynamic evolution in PRISM format, with columns:        time (s) | T (GK) | density (g/cm3)
DOI: 10.5281/zenodo.15352006
title: Neutron Star Merger Accretion Disk Trajectories for Nucleosynthesis

description: Contained herein are a set of trajectories derived from 30 Lagrangian tracers from the post-neutron-star-merger accretion disk simulation described in Lund et al. 2024 (DOI:10.3847/1538-4357/ad25ef). These tracers are from the simulation labeled b10 in the text.

These tracers have been selected in a way that is agnostic to the actual abundance patterns yielded by the full set of 195k+ tracers. The aim was to obtain a small, significantly more manageable set of tracer that represent conditions in the disk. As such, the conditions for selection were bins in electron fraction (Ye) and radial velocity.The tracers with velocities of less than 0.2c are subdivided (binned) by 0-0.08c (low v) and 0.08-0.2c (high v). While these values capture most of the mass in the disk, it should be noted that higher velocity tracers do exist and are not necessarily captured in this sample. Then, for each of the two velocity "bins", the tracers are further binned by Ye, and one tracer is selected from each bin, for a total of 30.Each tracer has a mass from the simulation. While these are recorded in the file tracer_reference, one should instead use the "assigned mass", which represents the mass contained in the bin. The text file tracer_reference.txt contains the following:

Ye bin represented     ID (unique for each simulation tracer particle)        Velocity bin (either low or high as defined above) the tracer represents and the mass (in solar masses) one should assign to it

Folders and files included:- Trajectories folder: contains individual subdirectories for each of the 30 tracers particles, named trace_{ID_of_tracer}. Within, there are three individual files:    - initx.dat: The initial composition calculated at T=10GK, formatted as         Z | A | Mass Fraction    - metadata.dat: Can mostly be ignored, but contain some identifying information for the ID's tracer.     - trajectory.dat: Thermodynamic evolution in PRISM format, with columns:        time (s) | T (GK) | density (g/cm3)
DOI: 10.15468/dl.g2g9x4
title: Occurrence Download

description: A dataset listing the 182 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Geometry POLYGON((54.42697 36.74967,54.49652 36.74967,54.49652 36.79895,54.42697 36.79895,54.42697 36.74967))",
 "HasCoordinate is true"
 ]
}

 The dataset's 182 records were derived from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018450-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15066413
title: Datasets for Genomic investigation of MRSA bacteremia relapse reveals diverse genomic profiles but convergence in bacteremia-associated genes

description: UPDATES From Version 1.0: 

--Addition of two files which are output from running Bactopia Pangenome pipeline using PIRATE. The files included are "pangenome.syntenic_blocks.tsv" and "PIRATE.gene_families.ordered.tsv" which identify gene families detected within all sequenced genomes. 

--The Clinical_MetaData_Public_v2.csv file was updated with metadata to recreate supplemental table S2

These are the datasets associated with the preprint "Genomic investigation of MRSA bacteremia relapse reveals diverse genomic profiles but convergence in bacteremia-associated genes", and which includes files needed to run using the provided Rmarkdown. The markdown code is also available at github.com/bmtalbot/bacteremia_recurrence
DOI: 10.5281/zenodo.15066414
title: Datasets for Genomic investigation of MRSA bacteremia relapse reveals diverse genomic profiles but convergence in bacteremia-associated genes

description: These are the datasets associated with the preprint "Genomic investigation of MRSA bacteremia relapse reveals diverse genomic profiles but convergence in bacteremia-associated genes", and which includes files needed to run using the provided Rmarkdown. The markdown code is also available at github.com/bmtalbot/bacteremia_recurrence
DOI: 10.5281/zenodo.15346219
title: Datasets for Genomic investigation of MRSA bacteremia relapse reveals diverse genomic profiles but convergence in bacteremia-associated genes

description: UPDATES From Version 1.0: 

--Addition of two files which are output from running Bactopia Pangenome pipeline using PIRATE. The files included are "pangenome.syntenic_blocks.tsv" and "PIRATE.gene_families.ordered.tsv" which identify gene families detected within all sequenced genomes. 

--The Clinical_MetaData_Public_v2.csv file was updated with metadata to recreate supplemental table S2

These are the datasets associated with the preprint "Genomic investigation of MRSA bacteremia relapse reveals diverse genomic profiles but convergence in bacteremia-associated genes", and which includes files needed to run using the provided Rmarkdown. The markdown code is also available at github.com/bmtalbot/bacteremia_recurrence
DOI: 10.15468/dl.cv67q8
title: Occurrence Download

description: A dataset containing 15638 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Juniperus thurifera L."
 ]
}

 The dataset includes 15638 records from 190 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018454-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15352232
title: Final Project Data - ML4MS: Will and Zoe
DOI: 10.5281/zenodo.15352233
title: Final Project Data - ML4MS: Will and Zoe
DOI: 10.5281/zenodo.15086207
title: Designer artificial environments for membrane protein synthesis

description: Protein synthesis in natural cells involves intricate interactions between chemical environments, protein-protein interactions, and protein machinery. Replicating such interactions in artificial and cell-free environments can control the precision of protein synthesis, elucidate complex cellular mechanisms, create synthetic cells, and discover new therapeutics. Yet, creating artificial synthesis environments, particularly for membrane proteins, is challenging due to the poorly defined chemical-protein-lipid interactions. Here, we introduce MEMPLEX (Membrane Protein Learning and Expression), which utilizes machine learning and a fluorescent reporter to rapidly design artificial synthesis environments of membrane proteins. MEMPLEX generates over 20,000 different artificial chemical-protein environments spanning 28 membrane proteins. It captures the interdependent impact of lipid types, chemical environments, chaperone proteins, and protein structures on membrane protein synthesis. As a result, MEMPLEX creates new artificial environments that successfully synthesize membrane proteins of broad interest but previously intractable. In addition, we identify a quantitative metric, based on the hydrophobicity of the membrane-contacting amino acids, that predicts membrane protein synthesis in artificial environments. Our work allows others to rapidly study and resolve the “dark” proteome using predictive generation of artificial chemical-protein environments. Furthermore, the results represent a new frontier in artificial intelligence-guided approaches to creating synthetic environments for protein synthesis.
DOI: 10.5281/zenodo.15086208
title: Designer artificial environments for membrane protein synthesis

description: Protein synthesis in natural cells involves intricate interactions between chemical environments, protein-protein interactions, and protein machinery. Replicating such interactions in artificial and cell-free environments can control the precision of protein synthesis, elucidate complex cellular mechanisms, create synthetic cells, and discover new therapeutics. Yet, creating artificial synthesis environments, particularly for membrane proteins, is challenging due to the poorly defined chemical-protein-lipid interactions. Here, we introduce MEMPLEX (Membrane Protein Learning and Expression), which utilizes machine learning and a fluorescent reporter to rapidly design artificial synthesis environments of membrane proteins. MEMPLEX generates over 20,000 different artificial chemical-protein environments spanning 28 membrane proteins. It captures the interdependent impact of lipid types, chemical environments, chaperone proteins, and protein structures on membrane protein synthesis. As a result, MEMPLEX creates new artificial environments that successfully synthesize membrane proteins of broad interest but previously intractable. In addition, we identify a quantitative metric, based on the hydrophobicity of the membrane-contacting amino acids, that predicts membrane protein synthesis in artificial environments. Our work allows others to rapidly study and resolve the “dark” proteome using predictive generation of artificial chemical-protein environments. Furthermore, the results represent a new frontier in artificial intelligence-guided approaches to creating synthetic environments for protein synthesis.
DOI: 10.15468/dl.6zewgr
title: Occurrence Download

description: A dataset containing 1245 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is CNMA/Colección Nacional de mamíferos",
 "TaxonKey is Desmodus rotundus murinus Wagner, 1840"
 ]
}

 The dataset includes 1245 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018455-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mvwsfd
title: Occurrence Download

description: A dataset listing the 71 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is BRA.25.60_2",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 1957-2025"
 ]
}

 The dataset's 71 records were derived from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018452-250426092105405/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.24233269
title: paingen_perspective_taking_data.nii.gz_encrypted

description: Participants painful thermal stimuli while imaging themselves as strong or weak individuals, or in a neutral condition. Most participants have a twin in the dataset. ~250 independent families are included. Stimuli were delivered to glabrous skin of the fingers.
DOI: 10.15468/dl.xrr48h
title: Occurrence Download

description: A dataset containing 398 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-121.76088 38.53233,-121.76597 38.53175,-121.76681 38.52889,-121.76307 38.52653,-121.75753 38.53135,-121.74683 38.53688,-121.74477 38.53893,-121.7417 38.53924,-121.73969 38.54112,-121.74125 38.54192,-121.74692 38.54045,-121.74901 38.53822,-121.75325 38.53483,-121.75744 38.53286,-121.76088 38.53233))",
 "OccurrenceStatus is Present",
 "Year 2025-2025"
 ]
}

 The dataset includes 398 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018461-250426092105405/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.28941305
title: Mayerl et al 2025 ICB - Data used in statistical analyses

description: Data used in statistical analysis
DOI: 10.6084/m9.figshare.28941305.v1
title: Mayerl et al 2025 ICB - Data used in statistical analyses

description: Data used in statistical analysis
DOI: 10.5281/zenodo.15350059
title: Lakes, Rivers and Glaciers in Canada - CanVec Series - Hydrographic Features

description: The hydrographic features of the CanVec series include watercourses, water linear flow segments, hydrographic obstacles (falls, rapids, etc.), waterbodies (lakes, watercourses, etc.), permanent snow and ice features, water wells and springs.

The Hydrographic features theme provides quality vector geospatial data (current, accurate, and consistent) of Canadian hydrographic phenomena. It aims to offer a geometric description and a set of basic attributes on hydrographic features that comply with international geomatics standards, seamlessly across Canada.

More information about this dataset can be found here; the files uploaded here were downloaded from the "Prepackaged FGDB files (download directory)", specifically, the 50K files.
DOI: 10.5281/zenodo.15350060
title: Lakes, Rivers and Glaciers in Canada - CanVec Series - Hydrographic Features

description: The hydrographic features of the CanVec series include watercourses, water linear flow segments, hydrographic obstacles (falls, rapids, etc.), waterbodies (lakes, watercourses, etc.), permanent snow and ice features, water wells and springs.

The Hydrographic features theme provides quality vector geospatial data (current, accurate, and consistent) of Canadian hydrographic phenomena. It aims to offer a geometric description and a set of basic attributes on hydrographic features that comply with international geomatics standards, seamlessly across Canada.

More information about this dataset can be found here; the files uploaded here were downloaded from the "Prepackaged FGDB files (download directory)", specifically, the 50K files.
DOI: 10.15468/dl.pngjgc
title: Occurrence Download

description: A dataset containing 1539 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cinchona officinalis L."
 ]
}

 The dataset includes 1539 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018463-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9wrny3
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Philippines",
 "TaxonKey is Lepidochelys olivacea (Eschscholtz, 1829)"
 ]
}

 The dataset includes 20 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018467-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5yzfgc
title: Occurrence Download

description: A dataset containing 706807 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Russian Federation",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 706807 records from 344 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018456-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mm2f8v
title: Occurrence Download

description: A dataset listing the 205 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is BRA.25.289_2",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 1957-2025"
 ]
}

 The dataset's 205 records were derived from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018460-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eycgt4
title: Occurrence Download

description: A dataset containing 706807 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Russian Federation",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 706807 records from 344 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018457-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57967/hf/5356
title: EthioMT
DOI: 10.15468/dl.y7qx9e
title: Occurrence Download

description: A dataset containing 1155241 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corylus avellana L."
 ]
}

 The dataset includes 1155241 records from 3594 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018459-250426092105405/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.30340267
title: H5N8 Influenza A Virus Genomes: Codon Usage Bias and Spatiotemporal Distribution n = 5219

description: This dataset features <b>5,219</b> complete <b>H5N8</b> influenza A virus sequences from NCBI, processed through local bioinformatics workflows. Sequences were filtered for completeness, aligned with MAFFT (--parttree --retree 1), and trimmed. Codon-level metrics including ENc, CAI (human and avian), GC3, RSCU, CPB, and PR2 were computed per sequence. Collection year and country were parsed from headers. Includes aligned FASTA, codon metrics CSV, QC summaries, and publication-ready visualizations.CODON USAGE SUMMARY: H5N8========================================Total sequences: 5,219Valid CDS: 1,703 (32.6%)Valid CAI: 1,703 (32.6%)<br>METRIC STATISTICS (Mean ± SD): ENc (Effective Number of Codons): 35.697 ± 1.497 CPB (Codon Pair Bias): 5.186 ± 1.103 CAI_human: 3.416 ± 0.137 CAI_avian: 3.436 ± 0.141 GC3: 0.449 ± 0.031 PR2_A (A3/(A3+T3)): 0.564 ± 0.043 PR2_G (G3/(G3+C3)): 0.531 ± 0.032<br>INTERPRETATION: → Strong codon usage bias (ENc &lt; 40) → Similar adaptation to human/avian hostsData processed by: TahirHB@Hotmail.Com for upcoming journal Article.<br>
DOI: 10.6084/m9.figshare.30340267.v1
title: H5N8 Influenza A Virus Genomes: Codon Usage Bias and Spatiotemporal Distribution n = 5219

description: This dataset features <b>5,219</b> complete <b>H5N8</b> influenza A virus sequences from NCBI, processed through local bioinformatics workflows. Sequences were filtered for completeness, aligned with MAFFT (--parttree --retree 1), and trimmed. Codon-level metrics including ENc, CAI (human and avian), GC3, RSCU, CPB, and PR2 were computed per sequence. Collection year and country were parsed from headers. Includes aligned FASTA, codon metrics CSV, QC summaries, and publication-ready visualizations.CODON USAGE SUMMARY: H5N8========================================Total sequences: 5,219Valid CDS: 1,703 (32.6%)Valid CAI: 1,703 (32.6%)<br>METRIC STATISTICS (Mean ± SD): ENc (Effective Number of Codons): 35.697 ± 1.497 CPB (Codon Pair Bias): 5.186 ± 1.103 CAI_human: 3.416 ± 0.137 CAI_avian: 3.436 ± 0.141 GC3: 0.449 ± 0.031 PR2_A (A3/(A3+T3)): 0.564 ± 0.043 PR2_G (G3/(G3+C3)): 0.531 ± 0.032<br>INTERPRETATION: → Strong codon usage bias (ENc &lt; 40) → Similar adaptation to human/avian hostsData processed by: TahirHB@Hotmail.Com for upcoming journal Article.<br>
DOI: 10.15468/dl.d3yk3h
title: Occurrence Download

description: A dataset containing 36817 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Streptomyces Waksman & Henrici, 1943"
 ]
}

 The dataset includes 36817 records from 429 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005159-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14469/hpc/13370
title: FAIR Table: Calculated isotope effects for the SWERN oxidation

description: Calculated using Kinisot.py
DOI: 10.5281/zenodo.15535868
title: Dataset and R Code for "Meta-analysis and Machine Learning Reveal Key Drivers of Microbial Carbon Use Efficiency Under Nitrogen Enrichment"

description: This repository contains the dataset and R code used in the study titled "Meta-analysis and Machine Learning Reveal Key Drivers of Microbial Carbon Use Efficiency Under Nitrogen Enrichment". The study performs a meta-analysis on soil microbial carbon use efficiency (CUE) under nitrogen addition and applies MetaForest machine learning to identify key environmental and management moderators.
DOI: 10.15468/dl.qtcx4b
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Hylobates agilis)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082998-250717081556266/datasets/export for details.
DOI: 10.3535/f4s-y18-yqn
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/1r6-97f-nm7
title: Ostracoda Latreille, 1802

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/d2h-ftz-d84
title: Placopsilina bradyi Cushman & McCulloch, 1939

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/83z-1s6-k2s
title: Melonis affinis (Reuss, 1851)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7r9-epw-4yb
title: †Monoceratina Roth, 1928

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.