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

description: A dataset containing 156 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bursera glabra (Jacq.) Triana & Planch."
 ]
}

 The dataset includes 156 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033988-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x8c6su
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tigridia estelae López-Ferr. & Espejo"
 ]
}

 The dataset includes 17 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033989-240626123714530/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.26357626
title: Exeter Pilot DS 4-5 Return

description: DS Dimensions Research Integrity Data return. Exeter DataThis is the DS return of the Exeter dataset analysed as part of United Kingdom Reproducability Network (UKRN) Research Indicators Project, pilot 4 - the prevalence and quality of data availability statements.Noted - Null records logged with support (may ned a refresh)False Negatives logged with support - explanations provided and should be amended with an updated training model.
DOI: 10.6084/m9.figshare.26357626.v1
title: Exeter Pilot DS 4-5 Return

description: DS Dimensions Research Integrity Data return. Exeter DataThis is the DS return of the Exeter dataset analysed as part of United Kingdom Reproducability Network (UKRN) Research Indicators Project, pilot 4 - the prevalence and quality of data availability statements.Noted - Null records logged with support (may ned a refresh)False Negatives logged with support - explanations provided and should be amended with an updated training model.
DOI: 10.15468/dl.6unfw4
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Harvard University Herbaria: All Records",
 "TaxonKey is Aquilegia elegantula Greene"
 ]
}

 The dataset includes 22 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033991-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k4cd4t
title: Occurrence Download

description: A dataset containing 364 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Pethia ticto (Hamilton, 1822)"
 ]
}

 The dataset includes 364 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033992-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10234392
title: Transcriptional and epigenetic profiling of Arabidopsis thaliana exposed to low dose ionizing radiation

description: RNA and methylation profiling of Arabidopsis seedlings to low dose ionizing radiation
DOI: 10.5281/zenodo.10234393
title: Transcriptional and epigenetic profiling of Arabidopsis thaliana exposed to low dose ionizing radiation

description: RNA and methylation profiling of Arabidopsis seedlings to low dose ionizing radiation
DOI: 10.6084/m9.figshare.26357641
title: Fake data

description: sdfsdfsd
DOI: 10.6084/m9.figshare.26357641.v1
title: Fake data

description: sdfsdfsd
DOI: 10.15468/dl.k3s4yf
title: Occurrence Download

description: A dataset containing 121 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bursera glauca Griseb."
 ]
}

 The dataset includes 121 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033994-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2qjhax
title: Occurrence Download

description: A dataset containing 16858 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lactarius deliciosus (L.) Gray"
 ]
}

 The dataset includes 16858 records from 332 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033993-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ufa47a
title: Occurrence Download

description: A dataset containing 6798 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is GPS locations of Northern Gannets season 2017 / Localisations GPS de fous de Bassan saison 2017",
 "Geometry POLYGON((-66.80143 46.7418,-64.65731 46.7418,-64.65731 48.26092,-66.80143 48.26092,-66.80143 46.7418))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6798 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033995-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c7g8yj
title: Occurrence Download

description: A dataset containing 6557 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is GPS locations of Northern Gannets season 2016 / Localisations GPS de fous de Bassan saison 2016",
 "Geometry POLYGON((-66.80143 46.7418,-64.65731 46.7418,-64.65731 48.26092,-66.80143 48.26092,-66.80143 46.7418))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6557 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033996-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qe7ycw
title: Occurrence Download

description: A dataset containing 6058 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Invertebrate Paleontology Division, Yale Peabody Museum",
 "Geometry POLYGON((-66.80143 46.7418,-64.65731 46.7418,-64.65731 48.26092,-66.80143 48.26092,-66.80143 46.7418))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6058 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033997-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ac3fnn
title: Occurrence Download

description: A dataset containing 152610 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is PRT.15.18_1",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 152610 records from 106 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033987-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tq25nv
title: Occurrence Download

description: A dataset containing 6024 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is GPS locations of Northern Gannets season 2013 / Localisations GPS de fous de Bassan saison 2013",
 "Geometry POLYGON((-66.80143 46.7418,-64.65731 46.7418,-64.65731 48.26092,-66.80143 48.26092,-66.80143 46.7418))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6024 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033998-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12751513
title: GCD Datasets for Self-Proving Models

description: Transcripts and annotated transcripts for training Self-Proving Models to compute the Greatest Common Divisor (GCD) of two integers. Integers are encoded in base 210. Full details of the tokenization scheme can be found in the paper.
DOI: 10.5281/zenodo.12751514
title: GCD Datasets for Self-Proving Models

description: Transcripts and annotated transcripts for training Self-Proving Models to compute the Greatest Common Divisor (GCD) of two integers. Integers are encoded in base 210. Full details of the tokenization scheme can be found in the paper.
DOI: 10.15468/dl.drr9q2
title: Occurrence Download

description: A dataset containing 34478 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Chile",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Insecta"
 ]
}

 The dataset includes 34478 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033999-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5b56dg77
title: MassIVE MSV000095417 - Identification of Disease-relevant, Sex-based Proteomic Differences in iPSC-derived Vascular Smooth Muscle
title: The prevalence of cardiovascular disease varies with sex, and the impact of intrinsic sex-based differences on vasculature is not well understood. Animal models can provide important insight into some aspects of human biology, however not all discoveries in animal systems translate well to humans. To explore the impact of chromosomal sex on proteomic phenotypes, we used iPSC-derived vascular smooth muscle cells from healthy donors of both sexes to identify sex-based proteomic differences and their possible effects on cardiovascular pathophysiology. Our analysis confirmed that differentiated cells have a proteomic profile more similar to healthy primary aortic smooth muscle than iPSCs. We also identified sex-based differences in iPSC-derived vascular smooth muscle in pathways related to ATP binding, glycogen metabolic process, and cadherin binding as well as multiple proteins relevant to cardiovascular pathophysiology and disease. Additionally, we explored the role of autosomal and sex chromosomes in protein regulation, identifying that proteins on autosomal chromosomes also show sex-based regulation that may affect the protein expression of proteins from autosomal chromosomes. This work supports the biological relevance of iPSC-derived vascular smooth muscle cells as a model for disease, and further exploration of the pathways identified here can lead to the discovery of sex-specific pharmacological targets for cardiovascular disease.
DOI: 10.5281/zenodo.8052721
title: Cortical cell assemblies and their underlying connectivity: an in silico study

description: Dataset linked to the article with the same title



	
simulation_config.zip: contains SONATA config files needed to re-run an exemplary simulation (after downloading the circuit from 10.5281/zenodo.7930275). In order to run it, paths in circuit_config.json, and simulation_config.json have to be updated!
	
assemblies.h5 is a dataset produced (and can be easily opened) by: assemblyfire (see GitHub README for more documentation) and serves as a basis for the manuscript. As the assemblies are the results of an unsupervised clustering (of high activity time bins) the resulting labels are not necessary meaningful. In the manuscript we have ordered the assemblies (from early to late responding ones, and from pattern A to J responsive ones) but the HDF5 file still stores the original labels. The mapping from the "random" labels to the ones presented in our article is stored in the config files on GitHub.



The development of this dataset was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
DOI: 10.5281/zenodo.8158472
title: Long-term plasticity induces sparse and specific synaptic changes in a biophysically detailed cortical model

description: Dataset linked to the article with the same title The model itself is very similar to its non-plastic counterpart under the following DOI: 10.5281/zenodo.7930275, i.e. a 1.5 mm diameter cortical tissue comprising 211,712 neurons and their connectivity in the front limb and jaw subregions and the dysgranular zone of the Paxinos & Watson rat brain atlas. It's formatted in the open SONATA standard and contains neuron locations and their properties (such as morphological types, cortical layer, etc.), their detailed morphologies, and synaptic connectivity (with all their anatomical and physiological parameters). The main difference from the non-plastic version is the addition of plasticity related parameters to <em>O1/S1nonbarrel_neurons__S1nonbarrel_neurons__chemical/edges.h5. </em>Extrinsic synaptic connections from the thalamus are included in this release, but for inputs from neurons in the remainder of non-barrel somatosensory cortex please see the non-plastic version of the circuit. <strong>Analyzing the model</strong> The model can be analyzed in terms of its anatomy, physiology and connectivity using the packages NeuroM, BlueBrain SNAP and ConnectomeUtilities. (see first Jupyter notebook) <strong>Simulating the model</strong> To simulate the model we'd recommend using out using our open-source simulator Neurodamus. The reference version is the branch <em>nbS1-2023</em>, which is archived under the following DOI: 10.5281/zenodo.8075202. Instructions on how to use the simulator are provided on the GitHub page linked above. Briefly, you'll first have to install Neurodamus. Next, build a <em>"special"</em> executable that include compiled versions of ion channel and synapse models. To do that, follow these instructions, where <em>mod-files-from-released-circuit </em>is replaced by the location of <em>O1/mods</em> on your system. Finally, run a simulation. The specific simulation conditions and stimuli are specified in simulation configuration files. An exemplary simulation configuration is included in this release (<em>simulation_config.zip</em>). <strong>Analyzing simulation results</strong> Simulation results can be analyzed with BlueBrain SNAP, ConnectomeUtilities, and assemblyfire. Notebooks 2-5 go though these analysis and recreate some of the panels from our article. In most cases the notebooks can be run with the shared HDF5 files and don't require running any simulations. -- <em>The development of this dataset was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.</em>
DOI: 10.5281/zenodo.12802004
title: Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

description: Dataset linked to the article with the same title

The model itself is very similar to its non-plastic counterpart under the following DOI: 10.5281/zenodo.7930275, i.e. a 1.5 mm diameter  cortical tissue comprising 211,712 neurons and their connectivity in the front limb and jaw subregions and the dysgranular zone of the Paxinos & Watson rat brain atlas. It's formatted in the open SONATA standard and contains neuron locations and their properties (such as morphological types, cortical layer, etc.), their detailed morphologies, and synaptic connectivity (with all their anatomical and physiological parameters). The main difference from the non-plastic version is the addition of plasticity related parameters to O1/S1nonbarrel_neurons__S1nonbarrel_neurons__chemical/edges.h5. Extrinsic synaptic connections from the thalamus are included in this release, but for inputs from neurons in the remainder of non-barrel somatosensory cortex please see the non-plastic version of the circuit.

Analyzing the model

The model can be analyzed in terms of its anatomy, physiology and connectivity using the packages NeuroM, BlueBrain SNAP and ConnectomeUtilities. (see first Jupyter notebook)

Simulating the model

To simulate the model we'd recommend using out using our open-source simulator Neurodamus. The reference version is the branch nbS1-2023, which is archived under the following DOI: 10.5281/zenodo.8075202. Instructions on how to use the simulator are provided on the GitHub page linked above. Briefly, you'll first have to install Neurodamus. Next, build a "special" executable that include compiled versions of ion channel and synapse models. To do that, follow these instructions, where mod-files-from-released-circuit is replaced by the location of O1/mods on your system. Finally, run a simulation. The specific simulation conditions and stimuli are specified in simulation configuration files. An exemplary simulation configuration is included in this release (simulation_config.zip).

Analyzing simulation results

Simulation results can be analyzed with BlueBrain SNAP, ConnectomeUtilities, and assemblyfire. Notebooks 2-5 go though these analysis and recreate some of the panels from our article. In most cases the notebooks can be run with the shared HDF5 files and don't require running any simulations.

Version 2

Bug fix in simulation_config.json and therefore new version of results (and corresponding notebooks). The underlying circuit model (O1.xz) did not change from v1.

--

The development of this dataset was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
DOI: 10.5281/zenodo.8158471
title: Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

description: Dataset linked to the article with the same title

The model itself is very similar to its non-plastic counterpart under the following DOI: 10.5281/zenodo.7930275, i.e. a 1.5 mm diameter  cortical tissue comprising 211,712 neurons and their connectivity in the front limb and jaw subregions and the dysgranular zone of the Paxinos & Watson rat brain atlas. It's formatted in the open SONATA standard and contains neuron locations and their properties (such as morphological types, cortical layer, etc.), their detailed morphologies, and synaptic connectivity (with all their anatomical and physiological parameters). The main difference from the non-plastic version is the addition of plasticity related parameters to O1/S1nonbarrel_neurons__S1nonbarrel_neurons__chemical/edges.h5. Extrinsic synaptic connections from the thalamus are included in this release, but for inputs from neurons in the remainder of non-barrel somatosensory cortex please see the non-plastic version of the circuit.

Analyzing the model

The model can be analyzed in terms of its anatomy, physiology and connectivity using the packages NeuroM, BlueBrain SNAP and ConnectomeUtilities. (see first Jupyter notebook)

Simulating the model

To simulate the model we'd recommend using out using our open-source simulator Neurodamus. The reference version is the branch nbS1-2023, which is archived under the following DOI: 10.5281/zenodo.8075202. Instructions on how to use the simulator are provided on the GitHub page linked above. Briefly, you'll first have to install Neurodamus. Next, build a "special" executable that include compiled versions of ion channel and synapse models. To do that, follow these instructions, where mod-files-from-released-circuit is replaced by the location of O1/mods on your system. Finally, run a simulation. The specific simulation conditions and stimuli are specified in simulation configuration files. An exemplary simulation configuration is included in this release (simulation_config.zip).

Analyzing simulation results

Simulation results can be analyzed with BlueBrain SNAP, ConnectomeUtilities, and assemblyfire. Notebooks 2-5 go though these analysis and recreate some of the panels from our article. In most cases the notebooks can be run with the shared HDF5 files and don't require running any simulations.

Version 2

Bug fix in simulation_config.json and therefore new version of results (and corresponding notebooks). The underlying circuit model (O1.xz) did not change from v1.

--

The development of this dataset was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
DOI: 10.15468/dl.zjsfkn
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ethiopia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Commiphora myrrha (T.Nees) Engl."
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034000-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zjc26w
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ethiopia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Commiphora myrrha (T.Nees) Engl."
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034001-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-1751/2
title: DSC09117.ARW

description: :unav
DOI: 10.18419/darus-1751/3
title: DSC09112.ARW

description: :unav
DOI: 10.18419/darus-1751/5
title: DSC09118.JPG

description: :unav
DOI: 10.18419/darus-1751/7
title: DSC09107.JPG

description: :unav
DOI: 10.18419/darus-1751/12
title: DSC09114.ARW

description: :unav
DOI: 10.18419/darus-1751/14
title: DSC09110.JPG

description: :unav
DOI: 10.18419/darus-1751/16
title: DSC09116.ARW

description: :unav
DOI: 10.18419/darus-1751/22
title: DSC09113.ARW

description: :unav
DOI: 10.18419/darus-1751/23
title: DSC09108.ARW

description: :unav
DOI: 10.18419/darus-1751/27
title: DSC09115.ARW

description: :unav
DOI: 10.18419/darus-1751/29
title: DSC09111.JPG

description: :unav
DOI: 10.18419/darus-1751/32
title: DSC09115.JPG

description: :unav
DOI: 10.5066/p1hyegvy
title: Cenozoic Coccolith Collection of David Bukry in Oregon and Washington, USA

description: Micropaleontological data have provided essential stratigraphic age control for geologic investigations in the Cascadia forearc, such as the Coast Range-Olympic Mountains and Puget-Willamette Lowland west of the Cascade Range. Foraminiferal assemblages and, later, coccoliths (calcareous nanoplankton) have been the most abundant microfossils recovered from the Cenozoic sequence. The usefulness of coccolith assemblages for establishing the Cenozoic stratigraphic framework (especially the Paleogene) in western Oregon was brought to the attention of Parke D. Snavely, Jr. in the 1960s by a letter from Dr. M. N. Bramlette of the Scripps Institution of Oceanography. Dr. Bramlette reported to Snavely that coccoliths in the Tyee Formation of western Oregon are correlative to “Laiming’s A2 zone of the Canoas Member” of the Kreyenhagen Formation in California (Bukry and Snavely, 1988). Dr. David Bukry, also of the USGS, joined Snavely’s geologic investigation team in the mid-1960s and provided the coccolith zonal assignments for many of the Cenozoic units in the Cascadia forearc. Coccolith information was originally reported to the collector in written form. Report sheets, accumulated over the past 30 years, served as the source of the data entered in the coccolith database.