cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.h6dvsh
title: Occurrence Download

description: A dataset containing 7398 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinus carpio",
 "GadmGid is one of (USA.6_1, USA.17_1, USA.27_1, USA.28_1, USA.32_1, USA.35_1, USA.37_1, USA.42_1, USA.44_1, USA.51_1)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Machine Observation)"
 ]
}

 The dataset includes 7398 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008307-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17715141
title: Data from: How management practices shape the 'local habitat signature' that modulates bird communities in urban green spaces

description: This dataset contains the Supplementary Information files (Tables and Figures) supporting the manuscript "How management practices shape the 'local habitat signature' that modulates bird communities in urban green spaces", accepted for publication in Biotropica.





Supplementary Information I: Contains Table S1 (Sampling points), Table S2 (Predictor variables), Table S3 (Species list and traits), Table S4 (Selected species), Table S5 (Model statistics), and Figure S1.




Supplementary Information II: Contains the Distance-Based Moran’s Eigenvector Maps (dbMEM) used as spatial predictors.
DOI: 10.5281/zenodo.17715142
title: Data from: How management practices shape the 'local habitat signature' that modulates bird communities in urban green spaces

description: This dataset contains the Supplementary Information files (Tables and Figures) supporting the manuscript "How management practices shape the 'local habitat signature' that modulates bird communities in urban green spaces", accepted for publication in Biotropica.





Supplementary Information I: Contains Table S1 (Sampling points), Table S2 (Predictor variables), Table S3 (Species list and traits), Table S4 (Selected species), Table S5 (Model statistics), and Figure S1.




Supplementary Information II: Contains the Distance-Based Moran’s Eigenvector Maps (dbMEM) used as spatial predictors.
DOI: 10.6084/m9.figshare.30710549
title: CellsigN

description: Single-cell RNA sequencing provides unprecedented opportunities to investigate cellular communication. Numerous computational methods have been developed to infer ligand–receptor interactions and downstream transcription factor (TF)–target gene（TG） regulation. However, existing approaches remain limited in reconstructing the detailed signaling cascades that bridge receptors and TFs. Here, we present CellSigN, a computational framework that reconstructs complete transcellular signaling pathways from single-cell RNA sequencing data. CellSigN integrates ligand–receptor interactions, TF–TG regulation, and six types of intercellular signaling events—chemical catalysis, transport regulation, state change control, physical interactions, protein complex formation, and phosphorylation. Applied to eight cancer datasets, CellSigN achieved an average of 16.13% improvement in recall for seven categories of cancer-related interactions compared with state-of-the-art methods. A breast cancer case study further demonstrated CellSigN’s ability to uncover disease mechanisms, highlighting its potential for biomarker discovery and therapeutic target development.
DOI: 10.6084/m9.figshare.30710549.v1
title: CellsigN

description: Single-cell RNA sequencing provides unprecedented opportunities to investigate cellular communication. Numerous computational methods have been developed to infer ligand–receptor interactions and downstream transcription factor (TF)–target gene（TG） regulation. However, existing approaches remain limited in reconstructing the detailed signaling cascades that bridge receptors and TFs. Here, we present CellSigN, a computational framework that reconstructs complete transcellular signaling pathways from single-cell RNA sequencing data. CellSigN integrates ligand–receptor interactions, TF–TG regulation, and six types of intercellular signaling events—chemical catalysis, transport regulation, state change control, physical interactions, protein complex formation, and phosphorylation. Applied to eight cancer datasets, CellSigN achieved an average of 16.13% improvement in recall for seven categories of cancer-related interactions compared with state-of-the-art methods. A breast cancer case study further demonstrated CellSigN’s ability to uncover disease mechanisms, highlighting its potential for biomarker discovery and therapeutic target development.
DOI: 10.15468/dl.qyh3gs
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CatalogNumber is one of (294676423, 313231073)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008309-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4bqcvn
title: Occurrence Download

description: A dataset containing 44315 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A Bird Atlas of Kenya"
 ]
}

 The dataset includes 44315 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008308-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qvcbjv
title: Occurrence Download

description: A dataset containing 90172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "DatasetKey is iNaturalist Research-grade Observations",
 "OccurrenceStatus is Present",
 "TaxonKey is Orchidaceae"
 ]
}

 The dataset includes 90172 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008299-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17675479
title: BEAR-GRN: Benchmarking, Evaluation and Assessment Resource for GRNs

description: This directory contains  the data required to reproduce the benchmarking results as reported in BEAR-GRN. This data is also required for benchmarking new GRN inference methods utilizing multiomics. 

INFERRED.GRNS - contains the inferred GRNs from Eight GRN inference methods for eight dataset used in BEAR-GRN

GROUND.TRUTHS - contain the ground truth filtered for expressed genes in each dataset

STABILITY_GRNS - contain the inferred GRNs from mESC subsamples created for stability measument for Eight GRN inference methods

INPUT.DATA - Contains processed multiomic data used for GRN inference (Gene by Cell and Peak by Cell matrix) 

INPUT.DATA.STABILITY - Contains rds file of subsampled scRNA and scATAC data and a script that can be used to generate matrix and create subsamples directories using RDS files

GENOME_AND_ANNOTATION - contains the genome, annotation, motif annotation, PWM files used by these inference algorithms for reproducibility
DOI: 10.5683/sp3/1wjg9r
title: Données issues du projet sur la classification des milieux humides

description: Ce jeu de données provient d'un projet réalisé en collaboration avec Jean-Olivier Goyette, Audréanne Loiselle, Stéphanie Pellerin et Monique Poulin.
Le projet portait sur la végétation et les stocks de carbone de 4 classes de milieux humides dans la région de Québec : marécages, tourbières boisées, fens et bogs
description: Modifications minimes de métadonnées
DOI: 10.15468/dl.867aqh
title: Occurrence Download

description: A dataset containing 18254 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((180 -44.3,173 -44.3,173 -47.5,170 -47.5,157 -47.5,157 -45.9,150 -45.9,150 -47.5,143 -47.5,143 -45.8,140 -45.8,140 -44.5,137 -44.5,137 -43,135 -43,135 -41.7,131 -41.7,131 -40.1,115 -40.1,92 -40.1,92 -41.4,78 -41.4,78 -42.3,69 -42.3,69 -43.3,47 -43.3,47 -41.7,30 -41.7,12 -41.7,12 -40.3,10 -40.3,10 -38.3,-5 -38.3,-5 -38.9,-9 -38.9,-9 -40.2,-13 -40.2,-13 -41.4,-21 -41.4,-21 -42.5,-39 -42.5,-39 -40.7,-49 -40.7,-49 -48.6,-54 -48.6,-54 -55.7,-62.79726 -55.7,-64 -55.7,-64 -57.8,-71 -57.8,-71 -58.9,-80 -58.9,-80 -40,-125 -40,-167 -40,-167 -42.6,-171 -42.6,-171 -44.3,-180 -44.3,-180 -90,0 -90,180 -90,180 -44.3))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Channichthyidae"
 ]
}

 The dataset includes 18254 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008310-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u7n4ws
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dendroctonus ponderosae",
 "GadmGid is one of (USA.6_1, USA.17_1, USA.27_1, USA.28_1, USA.32_1, USA.35_1, USA.37_1, USA.42_1, USA.44_1, USA.51_1)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Machine Observation)"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008311-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2e9f9z
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cyperus chalaranthus"
 ]
}

 The dataset includes 6 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008312-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5683/sp3/ucfxzj
title: Efficacy of releases of Phytoseiid mites (Acari: Phytoseiidae) on spider mite control on raspberry in high tunnel production, and implication on control strategy through a population model of Tetranychus mcdanieli (Acari: Tetranychidae)

description: CSV files containing all data of article "Efficacy of releases of Phytoseiid mites (Acari: Phytoseiidae) on spider mite control on raspberry in high tunnel production, and implication on control strategy through a population model of Tetranychus mcdanieli (Acari: Tetranychidae)" submitted to Biological Control
DOI: 10.5281/zenodo.17087863
title: BEAR-GRN: Benchmarking, Evaluation and Assessment Resource for GRNs

description: This directory contains  the data required to reproduce the benchmarking results as reported in BEAR-GRN. This data is also required for benchmarking new GRN inference methods utilizing multiomics. 

INFERRED.GRNS - contains the inferred GRNs from Eight GRN inference methods for seven dataset used in BEAR-GRN

GROUND.TRUTHS - contain the ground truth filtered for expressed genes in each dataset

STABILITY_GRNS - contain the inferred GRNs from mESC subsamples created for stability measument for Eight GRN inference methods

INPUT.DATA - Contains processed multiomic data used for GRN inference (Gene by Cell and Peak by Cell matrix) 

INPUT.DATA.STABILITY - Contains rds file of subsampled scRNA and scATAC data and a script that can be used to generate matrix and create subsamples directories using RDS files

GENOME_AND_ANNOTATION - contains the genome, annotation, motif annotation, PWM files used by these inference algorithms for reproducibility
DOI: 10.5281/zenodo.17087862
title: BEAR-GRN: Benchmarking, Evaluation and Assessment Resource for GRNs

description: This directory contains  the data required to reproduce the benchmarking results as reported in BEAR-GRN. This data is also required for benchmarking new GRN inference methods utilizing multiomics. 

INFERRED.GRNS - contains the inferred GRNs from Eight GRN inference methods for eight dataset used in BEAR-GRN

GROUND.TRUTHS - contain the ground truth filtered for expressed genes in each dataset

STABILITY_GRNS - contain the inferred GRNs from mESC subsamples created for stability measument for Eight GRN inference methods

INPUT.DATA - Contains processed multiomic data used for GRN inference (Gene by Cell and Peak by Cell matrix) 

INPUT.DATA.STABILITY - Contains rds file of subsampled scRNA and scATAC data and a script that can be used to generate matrix and create subsamples directories using RDS files

GENOME_AND_ANNOTATION - contains the genome, annotation, motif annotation, PWM files used by these inference algorithms for reproducibility
DOI: 10.15468/dl.wnucuk
title: Occurrence Download

description: A dataset containing 72468 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "TaxonKey is Palicourea"
 ]
}

 The dataset includes 72468 records from 287 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008257-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p9ewq08l
title: Airborne magnetic and radiometric survey, Charleston, South Carolina and surrounds, 2019

description: This data release provides digital flight line data for a high-resolution airborne magnetic and radiometric survey over Charleston, South Carolina and the surrounding region. These data were collected to better understand earthquake hazards in the Charleston seismic zone by imaging structural features in the crystalline basement and to image heavy mineral sands containing titanium, zirconium, and rare earth elements using radiometric data (gamma spectrometry), which is sensitive to thorium in monazite. This survey represents a collaborative effort by the U.S. Geological Survey (USGS) Earthquake Hazards Program, Mineral Resources Program, National Cooperative Mapping Program, and Earth Mapping Resource Initiative (Earth MRI) effort. Data for this survey were collected by Terraquest, Ltd. under contract with the USGS using a fixed wing aircraft with magnetometers mounted in the tail stinger and each wing tip pod and a fully calibrated gamma ray spectrometer from May to July of 2019. The survey covers a 134-kilometer x 90-kilometer rectangular area parallel to the Atlantic Ocean shoreline along the long axis. Data were collected along northwest-southeast flight lines spaced 400 meters (m) apart with northeast-southwest tie lines flown every 4000 m. A mean terrain clearance of 127 m was maintained. Most of the survey data were collected at lower flying heights, except near and over the City of Charleston higher clearance was maintained due to safety considerations. A total of 32,447-line kilometers (km) of data were collected. Files that are available in this publication include flight line data for the magnetic survey in an ascii .csv file, flight line data for the radiometric survey in an ascii .csv file, geoTIFF images of the total magnetic intensity and radiometric total count, potassium, thorium, and uranium values, and a report describing the survey parameters, field operations, quality control and data reduction procedures. A zip file containing the contractor's deliverable products is also included. Binary files in this package are readable using the free software &quot;Geosoft Viewer&quot; or commercial software &quot;Oasis Montaj.&quot;
DOI: 10.15468/dl.fq6jms
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cyperus redolens"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008313-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/9f859d7bd13284f5bf51caa3a3c34ef5
title: Long-term water quality monitoring in the Altamaha River near Doctortown, Georgia from January 2013 to December 2022.

description: Water samples were collected monthly on the Atlamaha River near Doctortown, Georgia. The samples were anlayzed for dissolved organics (carbon, nitrogen, phosphorus), dissolved nutrients (ammonium, nitrite, nitrate, phosphate, silicate) and particulate carbon and nitrogen. Concentrations of the following were measured using standard analytical methods: dissolved nutrients (phosphate, nitrate+nitrite, ammonium, silicate), dissolved organics (carbon, nitrogen, phosphorus) and particulate carbon and nitrogen
DOI: 10.15468/dl.4mc2tz
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Diaphorina citri",
 "GadmGid is one of (USA.6_1, USA.17_1, USA.27_1, USA.28_1, USA.32_1, USA.35_1, USA.37_1, USA.42_1, USA.44_1, USA.51_1)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Machine Observation)"
 ]
}

 The dataset includes 9 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008314-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2mydcc
title: CCDC 2441323: Experimental Crystal Structure Determination

description: Related Article: Xinjuan Wang|2025|CSD Communication|||
description: Related Article: Xin-Juan Wang, Yao-Hang Cheng, Xin-Yan Lv, Li-Ye Liang, Guang-Hui An, Guang-Ming Li|2025|Chin.Chem.Lett.||112154|doi:10.1016/j.cclet.2025.112154
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34740/kaggle/dsv/13868456
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5066/p9jxop0u
title: Airborne magnetic and radiometric survey, Columbia, South Carolina and surrounds, 2020

description: This data release provides digital flight line data for a high-resolution airborne magnetic and radiometric survey over Columbia, South Carolina, and the surrounding region. The airborne data collection was funded by the U.S. Geological Survey (USGS) Earth Mapping Resource Initiative (Earth MRI) with goals of better understanding placer deposits containing critical mineral resources titanium, zirconium, and rare earth elements and of imaging the crystalline basement partly buried beneath Atlantic Coastal Plain sediments. The survey was flown northwest of and slightly overlapping an airborne magnetic and radiometric survey collected in 2019 (Shah, 2020).  The northwestern boundary of the 2020 survey lies within the metamorphic and igneous [...]
DOI: 10.15468/dl.taqqfx
title: Occurrence Download

description: A dataset containing 454 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Digitaria",
 "GadmGid is one of (USA.6_1, USA.17_1, USA.27_1, USA.28_1, USA.32_1, USA.35_1, USA.37_1, USA.42_1, USA.44_1, USA.51_1)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Machine Observation)"
 ]
}

 The dataset includes 454 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008315-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p97vuijs
title: Airborne magnetic and radiometric survey, Munsungun region in northern Maine, 2021

description: This data release provides digital flight line data for a high-resolution airborne magnetic and radiometric survey over parts of northern Maine. The airborne data collection was funded by the U.S. Geological Survey (USGS) Earth Mapping Resource Initiative (Earth MRI) with goals of better understanding volcanogenic massive sulfide mineral deposits, sediment hosted manganese deposits, and their surrounding geologic framework. Data for this survey were collected and processed by Sander Geophysics under contract with the USGS. The airborne survey took place June-July 2021. Using a fixed wing aircraft with a magnetometer mounted in a tail stinger and a fully calibrated gamma ray spectrometer, data were collected along northwest-southeast [...]
DOI: 10.5281/zenodo.17714613
title: Simulation outputs for "Individual and collective gains from cooperation and reciprocity in a dynamic-network Prisoner's Dilemma driven by extraversion, openness, and agreeableness"

description: This record contains the full set of simulation outputs used in the article:



Abián, D., Bernad, J., & Ilarri, S. (2025).Individual and collective gains from cooperation and reciprocity in a dynamic-network Prisoner’s Dilemma driven by extraversion, openness, and agreeableness.Journal / preprint server, volume(issue), pages.DOI: TODO_INSERT_ARTICLE_DOI


The dataset comes from an agent-based model of a dynamic-network Prisoner’s Dilemma in which three continuous personality traits shape social behaviour: Extraversion sets each agent’s target number of concurrent partners; Openness controls how often agents search beyond friends-of-friends for new partners; and Agreeableness sets a baseline tendency to cooperate. At each interaction, agents blend this baseline with partner-specific history, and network ties are endogenously formed and cut as agents adjust their neighbourhoods.

The ZIP archive includes:





README_dataset.md – human-readable documentation of the dataset and file structure.




run_simulations_output.log – console log from running the main grid script (run_simulations.sh) in the bigthree-dynet-pd repository.




grid_bigthree_dynet_pd/ – top-level directory with all simulation outputs:





grid_runs_summary.csv – master index of all runs, with parameter settings, seeds, and run tags.




aggregate/ – condition-level summaries across seeds (aggregated correlations, assortativity, network statistics, and panel metrics) organised in one folder per parameter combination.




<run_tag>/ – one folder per simulation run (e.g. N100_T300_seed101_beta0.5_...), each containing:





parameters.json – full configuration and library versions for that run.




agents.csv – static agent traits and ideal degrees.




agent_timeseries.csv – per-agent time series (behaviour, payoffs, network degree, etc.).




correlations.csv – per-run Spearman correlations between cumulative payoff and key metrics.




assortativity.csv – assortativity coefficients over time (traits, degree, and other attributes).







All simulations were generated by running ./run_simulations.sh from the root of the bigthree-dynet-pd code repository, using Python (NumPy, pandas, NetworkX, SciPy). Each parameters.json file records the exact configuration and library versions needed to reproduce a given run.

If you use any part of this dataset, you must cite the associated article above. You are also encouraged to cite this dataset record using the DOI and citation information provided by Zenodo:



Abián, D. (2025). Simulation outputs for “Individual and collective gains from cooperation and reciprocity in a dynamic-network Prisoner’s Dilemma driven by extraversion, openness, and agreeableness” [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17714612