cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13848976
title: RivFISH - An European database on fish species presence across river basins

description: The RivFISH database aggregates the available data on freshwater-dependent fish presence in Europe, validated at the river basin level and considering taxonomical synonyms for species names, thus allowing for a maximization of data usage and robustness. This database also promotes interoperability with other datasets, including the IUCN Red List of Threatened Species, FishBase and the Catchment Characterisation and Modelling (CCM2) – River and Catchment Database v2.1. It is, as far as the authors know, the most up-to-date and comprehensive database on the presence of freshwater-dependent fish species for European river basins. The structure of the database is also prepared to deal with future alterations in species taxonomy, as well as new records of species occurrence in river basins.
DOI: 10.15468/dl.tejws9
title: Occurrence Download

description: A dataset containing 35022 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lobelia siphilitica"
 ]
}

 The dataset includes 35022 records from 303 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067805-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ug5275
title: Occurrence Download

description: A dataset containing 2751 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Echis"
 ]
}

 The dataset includes 2751 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067807-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4mzfhx
title: Occurrence Download

description: A dataset containing 668 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Guaruba guarouba",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))"
 ]
}

 The dataset includes 668 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067809-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.10273.06241
title: CERTIFICAT DE PUBLICATION DE VULGARISATION SCIENTIFIQUE Espace Sciences et Société – InfosNation
DOI: 10.15468/dl.55wd2q
title: Occurrence Download

description: A dataset listing the 368 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-66.23017 48.6789,-64.58708 48.6789,-64.58708 49.17925,-66.23017 49.17925,-66.23017 48.6789))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset's 368 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067806-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5xwrhp
title: Occurrence Download

description: A dataset containing 44470 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Indicator indicator",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))"
 ]
}

 The dataset includes 44470 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067810-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ms9eg8
title: Occurrence Download

description: A dataset containing 1825 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lerwa lerwa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))"
 ]
}

 The dataset includes 1825 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067811-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ksu73e
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Eristicophis"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067812-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dfq436
title: Occurrence Download

description: A dataset containing 10805 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tamarix ramosissima"
 ]
}

 The dataset includes 10805 records from 260 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067813-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bx4npe
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Macrotermes barneyi"
 ]
}

 The dataset includes 36 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067814-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18077121
title: Dataset of bank lines

description: This Dataset provides the original bank lines that are used to analyze river width variability.
DOI: 10.5281/zenodo.18077120
title: Dataset of bank lines

description: This Dataset provides the original bank lines that are used to analyze river width variability.
DOI: 10.15468/dl.y4fm4p
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Macrotermes barneyi"
 ]
}

 The dataset includes 36 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067816-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18075809
title: Kosinusähnlichkeit ägyptischer Texte und ägyptischer Lemmata anhand der Ranglistenpositionswerte

description: Kosinusähnlichkeit für ägyptische Texte und für ägyptische Lemmata in zwei csv-Files

Datengrundlage: Schweitzer, Simon D.: "Ranglistenpositionwerte in ägyptischen Texten" (https://doi.org/10.5281/zenodo.5493680)

Zugehöriges JSON mappt die Variablen mit den üblichen IDs für die ägyptischen Texte und Lemmata, wie sie in AED (siehe: https://doi.org/10.5281/zenodo.3580939 ) und TLA verwendet werden.
DOI: 10.5281/zenodo.18075810
title: Kosinusähnlichkeit ägyptischer Texte und ägyptischer Lemmata anhand der Ranglistenpositionswerte

description: Kosinusähnlichkeit für ägyptische Texte und für ägyptische Lemmata in zwei csv-Files

Datengrundlage: Schweitzer, Simon D.: "Ranglistenpositionwerte in ägyptischen Texten" (https://doi.org/10.5281/zenodo.5493680)

Zugehöriges JSON mappt die Variablen mit den üblichen IDs für die ägyptischen Texte und Lemmata, wie sie in AED (siehe: https://doi.org/10.5281/zenodo.3580939 ) und TLA verwendet werden.
DOI: 10.34847/nkl.c1c8y2d7
title: Revue du Nord : métadonnées des articles (1910-2025)

description: Fichier CSV regroupant l’ensemble des métadonnées des articles de la Revue du Nord, numérisés sur la plateforme Persée jusqu’en 2000, puis sur Cairn à partir de 2001.

N.B. : Ce tableur est le produit d’un script Python de web scraping visant à récupérer les métadonnées minimales nécessaires à l’identification des articles. Nous garantissons l’intégrité des données produites par ce processus, mais non la qualité des métadonnées telle qu’elle résulte de l’indexation initiale sur Persée et/ou Cairn. Ce fichier a pour seule vocation de fournir une aide à l’état de l’art pour les historien·ne·s s’intéressant à l’histoire du nord de la France, de l’Antiquité à nos jours.
Ce fichier contient uniquement les métadonnées et ne traite nullement du texte des articles. Nous respectons donc pleinement la politique éditoriale de la Revue du Nord (voir https://revue-du-nord.univ-lille.fr/index.php/autorisatios-mise-en-ligne-hors-serie/)

Structure du fichier CSV (colonnes) : titre, auteur, URL du numéro de la revue, titre du numéro (lorsqu’il a été possible de le récupérer par scraping), URL de l’article, date (année de publication), DOI (identifiant pérenne), pagination.
Nous recommandons fortement l'usage des DOIs lorsqu'ils sont disponibles pour accéder aux articles.

Lors de l’ouverture du fichier, veiller à indiquer le caractère " comme délimiteur de chaînes de caractères si celui-ci n’est pas détecté automatiquement par votre logiciel de tableur.

Script Python de récupération des métadonnées disponible ici : https://github.com/ValentinDeCraene/revue_du_nord_web_scrapping
description: Coverage: Nord de la France
description: coverage: Nord de la France
DOI: 10.48726/6yn8k-y6755
title: Structural Capacity Assessment of Precast Concrete Sandwich Panels of Existing Multi-Storey Buildings
DOI: 10.48726/v84rz-rx320
title: Structural Capacity Assessment of Precast Concrete Sandwich Panels of Existing Multi-Storey Buildings
DOI: 10.15468/dl.tn6kmq
title: Occurrence Download

description: A dataset containing 58193 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Monarda fistulosa"
 ]
}

 The dataset includes 58193 records from 354 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067808-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14323445
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.5rm9cq
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Garthius"
 ]
}

 The dataset includes 32 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067818-251120083545085/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.30958301
title: Fig1 from "Hyperglycemia Promotes SIRT3-Mediated Deacetylation of SARM1 to Exacerbate Diabetic Peripheral Neuropathy in Mice"

description: Fig1 from "Hyperglycemia Promotes SIRT3-Mediated Deacetylation of SARM1 to Exacerbate Diabetic Peripheral Neuropathy in Mice"<br>
DOI: 10.6084/m9.figshare.30958301.v2
title: Fig1 from "Hyperglycemia Promotes SIRT3-Mediated Deacetylation of SARM1 to Exacerbate Diabetic Peripheral Neuropathy in Mice"

description: Fig1 from "Hyperglycemia Promotes SIRT3-Mediated Deacetylation of SARM1 to Exacerbate Diabetic Peripheral Neuropathy in Mice"<br>
DOI: 10.15468/dl.zpvh69
title: Occurrence Download

description: A dataset containing 9992 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Panthera onca"
 ]
}

 The dataset includes 9992 records from 308 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067820-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.16983.94880
title: Villes et territoires durables. Méthodes et outils pour passer à l'action (ADEME - CNFPT) - Badge de réussite
DOI: 10.15468/dl.4m7jyj
title: Occurrence Download

description: A dataset containing 4069 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tapirus bairdii"
 ]
}

 The dataset includes 4069 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067821-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g45pa2
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Eutriorchis astur"
 ]
}

 The dataset includes 42 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067822-251120083545085/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.30958283
title: Fig3 from "Hyperglycemia Promotes SIRT3-Mediated Deacetylation of SARM1 to Exacerbate Diabetic Peripheral Neuropathy in Mice"

description: Fig3 from "Hyperglycemia Promotes SIRT3-Mediated Deacetylation of SARM1 to Exacerbate Diabetic Peripheral Neuropathy in Mice"
DOI: 10.6084/m9.figshare.30958283.v2
title: Fig3 from "Hyperglycemia Promotes SIRT3-Mediated Deacetylation of SARM1 to Exacerbate Diabetic Peripheral Neuropathy in Mice"

description: Fig3 from "Hyperglycemia Promotes SIRT3-Mediated Deacetylation of SARM1 to Exacerbate Diabetic Peripheral Neuropathy in Mice"
DOI: 10.5281/zenodo.18059900
title: scPhase: Exploring phenotype-related single-cells through attention-enhanced representation learning

description: The analysis of single-cell RNA-seq (scRNA-seq) data is pivotal for linking cellular heterogeneity to disease phenotypes, yet current methods often struggle with data sparsity, batch effects, and limited interpretability. Here, we present scPhase (phenotype prediction with attention mechanisms for single-cell exploring), a unified deep learning framework designed to predict clinical phenotypes directly from raw scRNA-seq profiles. To ensure robustness and scalability, scPhase integrates an efficient LinFormer-attention module to capture complex inter-cellular dependencies, a Mixture-of-Experts (MoE)-based Attention Multiple Instance Learning (AMIL) module to aggregate cellular information into patient-level representations, and an adversarial domain adaptation component to effectively mitigate batch effects across cohorts. Unlike existing approaches, scPhase does not rely on pre-defined cell type labels and offers multi-level interpretability at both the gene and cellular levels. We validated scPhase on five large-scale public datasets spanning COVID-19, aging, Alzheimer's disease, non-small cell lung cancer, and colorectal cancer. The results demonstrate that scPhase not only achieves superior predictive accuracy but also reveals critical biological insights into disease mechanisms.
description: Repository Contents & Output Structure This repository contains the output results, trained models, and interpretability metrics generated by the scPhase framework. All results are organized within the directory specified by RESULTS_DIR.

1. Trained Models





BestModel_{MODEL_NAME}_Fold{N}.pt: The best-performing model checkpoint from each Cross-Validation (CV) fold, saved in PyTorch format.



2. Performance Metrics





AllFolds_{MODEL_NAME}.csv: Contains detailed performance metrics for each validation fold, allowing for granular analysis of model stability.




Summary_{MODEL_NAME}.csv: Provides the aggregated performance metrics (mean ± standard deviation) across all folds to summarize overall model accuracy.



3. Interpretability Results scPhase provides multi-level interpretability outputs to assist in biological discovery:





ensemble_gene_attributions_{phenotype}.csv : Tables displaying the top-ranked genes associated with each specific phenotype.




sample_gene_attribution_mean.csv: A sample-by-gene matrix representing the mean attribution scores across folds, useful for downstream gene analysis.




ensemble_adata_with_attention.h5ad: An AnnData object containing the preprocessed data augmented with mean cell attention scores (saved in .obs['attention_weight_mean']).Note: This file encapsulates all information from the preprocessed dataset—making it directly usable for model training—plus the added attention weights. To avoid redundancy and comply with Zenodo's 50GB storage limit, we uploaded only this comprehensive file rather than the preprocessed data separately.
DOI: 10.5281/zenodo.18059899
title: scPhase: Exploring phenotype-related single-cells through attention-enhanced representation learning

description: The analysis of single-cell RNA-seq (scRNA-seq) data is pivotal for linking cellular heterogeneity to disease phenotypes, yet current methods often struggle with data sparsity, batch effects, and limited interpretability. Here, we present scPhase (phenotype prediction with attention mechanisms for single-cell exploring), a unified deep learning framework designed to predict clinical phenotypes directly from raw scRNA-seq profiles. To ensure robustness and scalability, scPhase integrates an efficient LinFormer-attention module to capture complex inter-cellular dependencies, a Mixture-of-Experts (MoE)-based Attention Multiple Instance Learning (AMIL) module to aggregate cellular information into patient-level representations, and an adversarial domain adaptation component to effectively mitigate batch effects across cohorts. Unlike existing approaches, scPhase does not rely on pre-defined cell type labels and offers multi-level interpretability at both the gene and cellular levels. We validated scPhase on five large-scale public datasets spanning COVID-19, aging, Alzheimer's disease, non-small cell lung cancer, and colorectal cancer. The results demonstrate that scPhase not only achieves superior predictive accuracy but also reveals critical biological insights into disease mechanisms.
description: Repository Contents & Output Structure This repository contains the output results, trained models, and interpretability metrics generated by the scPhase framework. All results are organized within the directory specified by RESULTS_DIR.

1. Trained Models





BestModel_{MODEL_NAME}_Fold{N}.pt: The best-performing model checkpoint from each Cross-Validation (CV) fold, saved in PyTorch format.



2. Performance Metrics





AllFolds_{MODEL_NAME}.csv: Contains detailed performance metrics for each validation fold, allowing for granular analysis of model stability.




Summary_{MODEL_NAME}.csv: Provides the aggregated performance metrics (mean ± standard deviation) across all folds to summarize overall model accuracy.



3. Interpretability Results scPhase provides multi-level interpretability outputs to assist in biological discovery:





ensemble_gene_attributions_{phenotype}.csv : Tables displaying the top-ranked genes associated with each specific phenotype.




sample_gene_attribution_mean.csv: A sample-by-gene matrix representing the mean attribution scores across folds, useful for downstream gene analysis.




ensemble_adata_with_attention.h5ad: An AnnData object containing the preprocessed data augmented with mean cell attention scores (saved in .obs['attention_weight_mean']).Note: This file encapsulates all information from the preprocessed dataset—making it directly usable for model training—plus the added attention weights. To avoid redundancy and comply with Zenodo's 50GB storage limit, we uploaded only this comprehensive file rather than the preprocessed data separately.
DOI: 10.15468/dl.tv9yfg
title: Occurrence Download

description: A dataset containing 69 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Venezuela (Bolivarian Republic of)",
 "OccurrenceStatus is Present",
 "TaxonKey is Thysanoptera"
 ]
}

 The dataset includes 69 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067823-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17617/3.obn9by
title: Data for "Machine Learning the Energetics of Electrified Solid/Liquid Interfaces"

description: This Dataset contains the data required to reproduce the publication "Machine Learning the Energetics of Electrified Solid/Liquid Interfaces" (Phys. Rev. Lett. 135, 146201, DOI: https://doi.org/10.1103/lm64-m3bn, preprint: https://doi.org/10.48550/arXiv.2505.19745)
It contains: Training structures for the Cu(100)-OH and H2O example Machine-Learned interatomic potentials (MLIPs); training files for the Cu(100)-OH and H2O examples; molecular dynamics trajectories, including the potential energies and work functions, from the Cu(100)-OH example in the publication.
DOI: 10.15468/dl.tbpvrx
title: Occurrence Download

description: A dataset containing 5148 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Colección de Reptiles - Museo de Herpetología de la Universidad de Antioquia"
 ]
}

 The dataset includes 5148 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067824-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cpq3sq
title: Occurrence Download

description: A dataset listing the 2420 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is BRA.9.144_2",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 2420 records were derived from 155 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067819-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5519/qd.vl84gxqa
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1001 records)
DOI: 10.15468/dl.utbp8e
title: Occurrence Download

description: A dataset containing 902 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cubiceps gracilis (Lowe, 1843)"
 ]
}

 The dataset includes 902 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030348-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14210264
title: Hydraulic geometry and whitewater coverage for a steep proglacial stream -- data sets and scripts

description: Data sets and scripts used in the analyses for the following article:

Dufficy, A.L., Eaton, B.C. and Moore, R.D. Quantifying hydraulic geometry and whitewater coverage for steep proglacial streams to support stream temperature modelling. Hydrological Processes, DOI: 10.1002/hyp.70003.

The number in the file names for the R scripts indicates the order in which the scripts should be run.

The study was funded by the Natural Sciences and Engineering Research Council of Canada and the Faculty of Arts, University of British Columbia.
DOI: 10.5281/zenodo.14210265
title: Hydraulic geometry and whitewater coverage for a steep proglacial stream -- data sets and scripts

description: Data sets and scripts used in the analyses for the following article:

Dufficy, A.L., Eaton, B.C. and Moore, R.D. Quantifying hydraulic geometry and whitewater coverage for steep proglacial streams to support stream temperature modelling. Hydrological Processes, DOI: 10.1002/hyp.70003.

The number in the file names for the R scripts indicates the order in which the scripts should be run.

The study was funded by the Natural Sciences and Engineering Research Council of Canada and the Faculty of Arts, University of British Columbia.