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

description: A dataset containing 331 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Continent is South America",
 "Country is one of (Colombia, Bolivia (Plurinational State of), Uruguay, Venezuela (Bolivarian Republic of), Ecuador, Peru, Paraguay, Argentina)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Achyrocline satureioides (Lam.) DC."
 ]
}

 The dataset includes 331 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0238563-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xve9ru
title: Occurrence Download

description: A dataset containing 252 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Artemisia frigida Willd."
 ]
}

 The dataset includes 252 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0278980-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.63sa28
title: Occurrence Download

description: A dataset containing 760 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Corylus mandshurica Maxim."
 ]
}

 The dataset includes 760 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046860-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5fgbsu
title: Occurrence Download

description: A dataset containing 2132 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-122.80336 4.27208,-59.19664 4.27208,-59.19664 29.72792,-122.80336 29.72792,-122.80336 4.27208))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Melipona beecheii Bennett, 1831"
 ]
}

 The dataset includes 2132 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0278956-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9tve4h
title: Occurrence Download

description: A dataset containing 638 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Hylobius pales C.H.Boheman, 1834"
 ]
}

 The dataset includes 638 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0185470-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.875vvb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Piper kawakamii Hayata",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0201632-220831081235567/datasets/export for details.
DOI: 10.15468/dl.arccmy
title: Occurrence Download

description: A dataset containing 146 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Artemisia dracunculus L."
 ]
}

 The dataset includes 146 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0278974-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xwb5kt
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-77.34482 -11.16712,-77.20864 -11.16712,-77.20864 -11.0546,-77.34482 -11.0546,-77.34482 -11.16712))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 24 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0185478-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rwmn65
title: Occurrence Download

description: A dataset containing 2323 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Brazil, Colombia, Ecuador, Peru, Bolivia (Plurinational State of), Argentina)",
 "TaxonKey is Panthera onca (Linnaeus, 1758)"
 ]
}

 The dataset includes 2323 records from 113 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0278958-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tv5eep
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Saussurea modesta Kitam.",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 59 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0205843-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.drqh3c
title: Occurrence Download

description: A dataset containing 79046 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Europe, Africa)",
 "TaxonKey is Nasturtium officinale R.Br."
 ]
}

 The dataset includes 79046 records from 727 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0278968-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2024-04.3082941/2547979
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082942/2547980
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082943/2547981
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082944/2547982
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082947/2547983
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082948/2547984
title: Data for EMSL Project 51287 from April 2024
DOI: 10.5281/zenodo.14997296
title: O'Hare, et al., 2025, Neuron

description: Data and code to reproduce results in O'Hare et al., 2025 (Neuron). 

Everything in this folder is self-contained. Wherever you unzip it, you should run things exclusively from within it.

 

Contents:

1. Jupyter notebook (made in Jupyter Lab) to reproduce all analytical plots

2. plotting_utils Python module to assist Jupyter notebook

3. lab Python module to illustrate operations for template-based event detection and plateau potential classification

4. Conda environment for all code. See instructions below. You'll need 1.33 GB to unpack this environment.

 

To get going:

1. Unpack conda environments (locally, no need to permanently link to your conda install!)

   a.  ohare2025 needs to be unpacked from .tar.gz file. to do so:

      i. cd /path/to/folder/OHare2025_code/envs

      ii. mkdir ohare2025

      iii. tar -xzf ohare2025-env.tar.gz -C ohare2025 #unpack into empty ohare2025 folder. may take a while.

 

2. Register the ohare2025 env as a Python kernel in your jupyter lab/notebook distribution.

   a. open whatever conda environment you normally use to run jupyter

   b. install ipykernel if you don't have it: pip install ipykernel #do NOT use conda install here!

   c. conda deactivate #unless running jupyter from base, in which case skip this command

   d. source /path/to/folder/OHare2025_code/envs/ohare2025/bin/activate #activates the conda env in-place

   e. python -m ipykernel install --prefix /path/to/jupyterlab_env --name ohare2025 --display-name "Python 2.7 (OHare2025)"

   f. exit the ohare2025 env

      deactivate #don't use conda here

      source ~/.bashrc #if you still see ohare2025 hanging around in your command prompt

   g. return to your jupyter env and verify kernel installed: 

      conda activate <env_you_use_for_jupyter>

      jupyter kernelspec list #you should see it here, located in its conda env, e.g. ~/miniconda3/envs/jupyter/share/jupyter/kernels/ohare2025

 

3. Launch jupyter lab/notebook.

   a. cd /path/to/folder/OHare2025_code #this is critical

   b. launch jupyter lab:

       jupyter lab #or jupyter notebook, if that's your jam

   c. open O'Hare_2025_Figs.ipynb from the file explorer tab and select the new OHare2025 kernel you created.

 

Enjoy!

Code is shown exactly as used to produce each data figure in our manuscript. Feel free to explore the datasets further - they are stored as Pandas DataFrames in .pkl files and are thoroughly annotated, e.g. with animal ID, dendrite type, dendrite order, dendrite path distance to soma, dendrite parent soma, ROI genotype, etc. Enjoy!

*Note: The Jupyter notebook was created in JupyterLab to enable toggling by figure. It may also function in a classical Jupyter notebook with nbextensions enabled. Without toggling, these notebooks will be unwieldy.
DOI: 10.25582/data.2024-04.3082950/2547985
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082951/2547986
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082952/2547987
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082953/2547988
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082954/2547989
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3082955/2547990
title: Data for EMSL Project 51287 from April 2024
DOI: 10.15468/xed9sz
title: ZRU sediment metagenome Metagenome

description: To investigate the influence of wetland types on the composition and structure of microbial communities.
DOI: 10.15468/e1qkik
title: Gulf Oil Spill underwater oil plume samples Targeted Locus (Loci)

description: During late spring and summer of 2010, the Northern Gulf of Mexico (GoM) was exposed to an oil spill different in magnitude and scope from any previous spill. The Deepwater Horizon, an ultra-deep, offshore drilling platform, began working GoM oil fields in 2001. While working a well in Mississippi Canyon on April 20, 2010, a bolus of methane gas ascended the drill pipe and exploded at the surface. Two days later the platform sank and since then, substantial quantities of oil and gas have leaked from the damaged wellhead. This work addressed the offshore oceanic impacts of the BP spill. Sediment microbial mediated processes are capable of oxidizing oil and methane in the environment. The PI''s examined the impacts of the Deepwater Horizon Oil Spill on microbially mediated processes in the deep waters and sediments in the vicinity of the spill site. The work complemented several funded or planned geochemical and microbiological sampling programs focused on the oil spill response. PI''s evaluated rates of water column methane oxidation and sediment sulfate reduction and methanogenesis at multiple sites around the spill site. Additional experiments quantified the impact of nutrients, oxygen and substrate concentrations on these important microbially mediated processes. The Joye group participated in six research cruises during 2010 and received samples from another six cruises from the study area. On all cruises, water samples were collected using a CTD rosette and Niskin or Go-Flo bottles. Sediment samples were obtained by box coring, multi-coring, or using the manned submersible ALVIN. The PI''s extended the monitoring/assessment program that was initiated through the NOAA National Institute of Undersea Science and Technology (NIUST) funded cruise and further leveraged by NOAA/NIUST (cruises in July 2010, October 2010) by conducting three major expeditions in 2010. This RAPID project directly supported the PI''s efforts for cruises in May/June 2010 (NSF Joye chief scientist); August 2010 (NSF Montoya, chief scientist); November/December 2010 (NSF Joye chief scientist); and July 2011 (NSF Montoya, chief scientist)
DOI: 10.6084/m9.figshare.30196591
title: Next-Gen Systemic Rabbit Breeding

description: Stop juggling isolated fixes and start steering an integrated organism–environment ecosystem. Written by a field zoologist who has logged two decades between genome sequencers and hay bales, this monograph stitches molecular genetics, precision nutrition, sensor-rich housing and circular-economy waste loops into a single, actionable framework. Every concept is laboratory-vetted, barn-piloted and cost-benchmarked—so you can replicate, not merely admire.
DOI: 10.6084/m9.figshare.30196591.v1
title: Next-Gen Systemic Rabbit Breeding

description: Stop juggling isolated fixes and start steering an integrated organism–environment ecosystem. Written by a field zoologist who has logged two decades between genome sequencers and hay bales, this monograph stitches molecular genetics, precision nutrition, sensor-rich housing and circular-economy waste loops into a single, actionable framework. Every concept is laboratory-vetted, barn-piloted and cost-benchmarked—so you can replicate, not merely admire.
DOI: 10.15468/kxcqmw
title: Coastal eutrophication controls the bacterial community composition in different reef habitats of the Spermonde Archipelago, Indonesia.

description: Coastal eutrophication is a key driver of shifts in bacterial communities, but related knowledge is very scarce. With fringing and patch reefs at varying distances from the coast the Spermonde Archipelago in southern Sulawesi, Indonesia offers ideal conditions to study the effects of coastal eutrophication along a spatially defined gradient. The present study investigated bacterial community composition of three coral reef habitats: the water column, sediments and mucus of the hard coral genus Fungia, along that cross-shelf environmental and water quality gradient. The main research questions were: (1) How do bacterial communities respond to changes in water quality along a spatial gradient? (2) Which water quality parameters influence the bacterial community composition? (3) Are there bacteria community differences between the different investigated microbial habitats? For this purpose a range of key water parameters were measured at 8 stations in distances from 2 to 55 km from urban Makassar. This was supplemented by sampling of bacterial communities of important microbial habitats using 454 pyrosequencing. Findings revealed that the population center Makassar had a strong effect on the concentrations of Chlorophyll a, suspended particulate matter (SPM) and transparent exopolymer particles (TEP), which were all significantly elevated at the inshore compared the other 7 sites. Shifts in the bacterial communities were specific to each sampled habitat. In the water column, the relative abundance of Gammaproteobacteria increased with distance from Makassar, while that of Alphaproteobacteria decreased.In the sediments, there was a pronounced dominance of Gammaproteobacteria at the inshore site, which decreased along the gradient. There was no gradual shift in bacterial classes for samples obtained from the Fungia mucus. We observed a strong positive correlation between Bacteroidia, Chlamydiia and Acidobacteria_Gp6 and chlorophyll a, TEP and SPM. Deinocooci, Verrumicrobiae and Alphaproteobacteria were, on the other hand, positively correlated to DOC concentrations. In addition, we observed very distinct communities between the investigated habitats. Our data shows strong changes in the bacterial community composition at the inshore site for water column and sediment samples. Alarmingly, this led to a much higher prevalence of potentially pathogenic bacteria at the chronically impacted site closest to Makassar.
DOI: 10.15468/tx2ebq
title: Particulate methane monooxygenase diversity on an Arctic shelf

description: Analysis of particulate methane monooxygenase diversity from natural seawater and methane-ammended sea water incubations via amplicon sequencing of the pmoA subunit.
DOI: 10.5281/zenodo.17190704
title: Data source
DOI: 10.5281/zenodo.17190703
title: Data source
DOI: 10.15468/dl.4b4965
title: Occurrence Download

description: A dataset containing 104 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Allium ochroleucum)"
 ]
}

 The dataset includes 104 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011419-250920141307145/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.29947784
title: Phytochemical Interventions from <i>Withania somnifera</i>: An Approach to Inhibit mPGES-1 and Proteins Involved in Rheumatoid Arthritis

description: Rheumatoid arthritis (RA) is aninflammatory disorder, with treatments, particularly cyclooxygenase (COX) inhibitors linked to cardiovascular complications. This study explores <i>Withania somnifera</i> (WS) as potential alternative by targeting microsomal prostaglandin E synthase-1 (mPGES-1). <i>In silico</i> analysis revealed binding affinity of WS phytochemical Withanolide D (−9.8 kcal mol−1) with mPGES-1, and has drug-like properties. Five key targets (STAT1, MIF, MMP12, PAD4, and CDK6) were identified, with strong binding to STAT1 (−10.2 kcal mol<sup>−1</sup>). <i>In vitro</i> validation using WS roots extract in SW982 cells revealed targeting of NFκB pathway, mPGES-1 and the five genes. Results suggest WS and Withanolide D as alternatives to COX inhibitors.
DOI: 10.6084/m9.figshare.29947784.v1
title: Phytochemical Interventions from <i>Withania somnifera</i>: An Approach to Inhibit mPGES-1 and Proteins Involved in Rheumatoid Arthritis

description: Rheumatoid arthritis (RA) is aninflammatory disorder, with treatments, particularly cyclooxygenase (COX) inhibitors linked to cardiovascular complications. This study explores <i>Withania somnifera</i> (WS) as potential alternative by targeting microsomal prostaglandin E synthase-1 (mPGES-1). <i>In silico</i> analysis revealed binding affinity of WS phytochemical Withanolide D (−9.8 kcal mol−1) with mPGES-1, and has drug-like properties. Five key targets (STAT1, MIF, MMP12, PAD4, and CDK6) were identified, with strong binding to STAT1 (−10.2 kcal mol<sup>−1</sup>). <i>In vitro</i> validation using WS roots extract in SW982 cells revealed targeting of NFκB pathway, mPGES-1 and the five genes. Results suggest WS and Withanolide D as alternatives to COX inhibitors.
DOI: 10.5281/zenodo.15491763
title: Stretching Beyond the Obvious: A Gradient-Free Framework to Unveil the Hidden Landscape of Visual Invariance

description: Data for replicating the experiments performed in the paper : Stretching Beyond the Obvious: A Gradient-Free Framework to Unveil the Hidden Landscape of Visual Invariance.

It includes:



unified MEI references for SnS experiments

unified natural image statistics

weights of the Deepsim image generator

Data of the behavioral experiments of both humans and other observer networks

Results of multiexperiments used in the paper

Imagenet labels
DOI: 10.15468/95top8
title: Microbial associations in temperate marine copepods from the Gulf of Maine

description: 16S rRNA amplicon sequencing with the Illumina MiSeq platform on seawater and copepods from the Gulf of Maine.
DOI: 10.5281/zenodo.15348779
title: Computational Modeling and Validation Data for Trans-spinal Direct Current Stimulation (tsDCS) in SOD1 Mice

description: This dataset provides a multimodal collection of data acquired and generated in the context of an investigation that aims to provide a comprehensive computational model that predicts the electric fields (EF) induced by tsDCS intervention in SOD1 mice.

It includes a .zip archive for each of the following:





Full-body MRI data in DICOM format




3D anatomical models and simulation files related to tsDCS




Electrophysiological recordings and analysis scripts validating model predictions



1. Magnetic Resonance Imaging (MRI) Data- Format: DICOM (.dcm)- Modality: MRI, T2-weighted- Acquisition Sequence: FLASH- Anatomical Region: Full-body (mouse)- Slices: 165 axial slices- Includes README file with more detailed information

2. Computational Simulation & Anatomical Models

- Formats:  >*.mph and .mphtxt COMSOL model files (mesh and simulation setup)  > STL-format 3D anatomical models for computational modeling

- Anatomical Structures in STL Files:  > Heart, Intestines, Kidneys, Liver, Lungs, Pancreas, Spleen, Stomach  > Skull and Brain  > Full spine (including GM, WM, CSF, dura mater, vertebrae, IVDs, and surrounding fat)

- Includes README file with more detailed information

3. Electrophysiological Validation Data

- Formats:  > Spike Recordings (.smr): Raw electrophysiological recordings (openable in Spike2)  > RStudio Script (.R): For statistical analysis and visualization of electrophysiological results  > Voltage Deflection Measurements (.xlsx): Tabulated results of evoked voltage by electrode distance, depth, tsDCS configuration, and current intensity
DOI: 10.5281/zenodo.15348780
title: Computational Modeling and Validation Data for Trans-spinal Direct Current Stimulation (tsDCS) in SOD1 Mice

description: This dataset provides a multimodal collection of data acquired and generated in the context of an investigation that aims to provide a comprehensive computational model that predicts the electric fields (EF) induced by tsDCS intervention in SOD1 mice.

It includes a .zip archive for each of the following:





Full-body MRI data in DICOM format




3D anatomical models and simulation files related to tsDCS




Electrophysiological recordings and analysis scripts validating model predictions



1. Magnetic Resonance Imaging (MRI) Data- Format: DICOM (.dcm)- Modality: MRI, T2-weighted- Acquisition Sequence: FLASH- Anatomical Region: Full-body (mouse)- Slices: 165 axial slices- Includes README file with more detailed information

2. Computational Simulation & Anatomical Models

- Formats:  >*.mph and .mphtxt COMSOL model files (mesh and simulation setup)  > STL-format 3D anatomical models for computational modeling

- Anatomical Structures in STL Files:  > Heart, Intestines, Kidneys, Liver, Lungs, Pancreas, Spleen, Stomach  > Skull and Brain  > Full spine (including GM, WM, CSF, dura mater, vertebrae, IVDs, and surrounding fat)

- Includes README file with more detailed information

3. Electrophysiological Validation Data

- Formats:  > Spike Recordings (.smr): Raw electrophysiological recordings (openable in Spike2)  > RStudio Script (.R): For statistical analysis and visualization of electrophysiological results  > Voltage Deflection Measurements (.xlsx): Tabulated results of evoked voltage by electrode distance, depth, tsDCS configuration, and current intensity
DOI: 10.15468/dl.ctsq4s
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Balaenoptera omurai"
 ]
}

 The dataset includes 133 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011420-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.