cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/nzk4swk7xy
title: Amino acid repeat signatures underlying human-pathogen interactions

description: Emerging evidence suggests that amino acid homorepeats (HRs) in proteins (HRPs) contribute to protein interactability. What is the role of HRs in human-pathogen protein interactions? We find that pathogens engage physiologically important human HRPs, thereby affecting diverse host physiological processes. From the pathogen standpoint, (i) eukaryotic pathogens engage more HRPs but with host-sparse HRs, leading to disparate and discriminate interactions, (ii) prokaryotic pathogens engage less HRPs but with host-abundant non-polar HRs via host protein proxies bringing about discriminate or promiscuous interactions and (iii) viral pathogens engage more HRPs with host-abundant polar uncharged HRs affecting promiscuous interactions using host-partner HR tract mimicry. To propel further research, we introduce a resource Hi-PHI (http://hiphi.iisertirupati.ac.in/) cataloging critical information about human and pathogen HRPs and HRs. We propose mechanisms to (i) repurpose drugs targeting human HRPs engaged by pathogens for treating different infections and (ii) exploit HRs and their flanks as targets for pathogen-targeted anti-infectives.

Here, we have uploaded the assembled and curated human-pathogen protein interactome (HPI), which has 19,535 interactions between human and pathogen proteins. We have also provided the source code to facilitate repetition of this work and address other fundamental systems- and molecular-level questions. The instructions regarding usage of the codes are provided in individual scripts. All the datasets assembled, curated, generated and used in this study is available as a resource, Hi-PHI database (http://hiphi.iisertirupati.ac.in/).
DOI: 10.17632/nzk4swk7xy.1
title: Amino acid repeat signatures underlying human-pathogen interactions

description: Emerging evidence suggests that amino acid homorepeats (HRs) in proteins (HRPs) contribute to protein interactability. What is the role of HRs in human-pathogen protein interactions? We find that pathogens engage physiologically important human HRPs, thereby affecting diverse host physiological processes. From the pathogen standpoint, (i) eukaryotic pathogens engage more HRPs but with host-sparse HRs, leading to disparate and discriminate interactions, (ii) prokaryotic pathogens engage less HRPs but with host-abundant non-polar HRs via host protein proxies bringing about discriminate or promiscuous interactions and (iii) viral pathogens engage more HRPs with host-abundant polar uncharged HRs affecting promiscuous interactions using host-partner HR tract mimicry. To propel further research, we introduce a resource Hi-PHI (http://hiphi.iisertirupati.ac.in/) cataloging critical information about human and pathogen HRPs and HRs. We propose mechanisms to (i) repurpose drugs targeting human HRPs engaged by pathogens for treating different infections and (ii) exploit HRs and their flanks as targets for pathogen-targeted anti-infectives.

Here, we have uploaded the assembled and curated human-pathogen protein interactome (HPI), which has 19,535 interactions between human and pathogen proteins. We have also provided the source code to facilitate repetition of this work and address other fundamental systems- and molecular-level questions. The instructions regarding usage of the codes are provided in individual scripts. All the datasets assembled, curated, generated and used in this study is available as a resource, Hi-PHI database (http://hiphi.iisertirupati.ac.in/).
DOI: 10.17632/3d2zv5dmj6.1
title: Rational design single-atom doped Ti3C2O2 MXene as a promising catalyst for hydrogen evolution reaction

description: original date
DOI: 10.17632/25r6txd45n.5
title: Provenance Modelling of Fossil Dinosaur Bones Using Geochemistry and Machine Learning: Source Data

description: The data presented here support the research paper “Provenance Modelling of Fossil Dinosaur Bones Using Geochemistry and Machine Learning”, intended for a submission to "Paleoworld".

The dataset contains trace elements concentrations from fossil dinosaur bones from the Upper Cretaceous Nemegt and Djadokhta formations. 
For the analytical purposes, the dataset was divided into two subsets: the first one consisting of long bones (tibiae, femora, radii and humeri) and the other including trabecular bones (ribs and vertebrae) and metatarsals. Locality labels were used to train and evaluate several machine learning classifiers (logistic regression, random forest, AdaBoost, XGBoost) to assess the potential of bone geochemistry for provenance prediction. Feature selection was conducted on the best-performing models to identify the elements contributing the most to the model performance. These results were compared with those obtained using Linear Discriminant Analysis. 

The data are provided in CSV format in the “Data” folder. The folder “Plots and figures” contains the figures used in the manuscript, including the plots. The folder “Supplementary files” contains additional files. These files are:
- interactive HTML plot ("Element profiles.html") showing the all the concentration profiles across each analysed sample, including the ones measured along several profiles
- concentration profiles presented in a PDF file ("All profiles.pdf")
- XLSX file with the statistical summary of the data ("Data description WK.xlsx")
- LDA scalings in CSV file ("LDA scalings.csv")
- The tables comparing predictions and performance of the algorithms using test part of each subset ("Predictions and accuracy.xlsx")
Besides that, the Jupyter Notebook with data analysis is also provided ("Bones from Gobi - loc prediction.ipynb").
DOI: 10.15468/dl.mdfjw5
title: Occurrence Download

description: A dataset listing the 4 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Murciélagos de la isla de Providencia. Expedición Seaflower 2019 proyecto Colombia BIO"
 ]
}

 The dataset's 4 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014264-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17752057
title: Text data (with sound file) of Irabu Ryukyuan (Japonic, Miyako) _4

description: Fully annotated narrative text with sound files: 継子台 (Mamakodai)

Meta data:

data recorded 20060122

data recorded and annotated by Michinori Shimoji

data from KS (born in 1916, female, Nagahama, Irabu)
DOI: 10.5281/zenodo.16614597
title: Text data (with sound file) of Irabu Ryukyuan (Japonic, Miyako) _4

description: Fully annotated narrative text with sound files: 継子台 (Mamakodai)

Meta data:

data recorded 20060122

data recorded and annotated by Michinori Shimoji

data from KS (born in 1916, female, Nagahama, Irabu)
DOI: 10.15468/dl.j8d5f4
title: Occurrence Download

description: A dataset containing 2890 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Diversidad taxonómica de las lianas de la cuenca del río Sinú en Córdoba (Colombia)"
 ]
}

 The dataset includes 2890 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014276-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17751636
title: GMR™ - MASTER - DATASET - FINAL 3.0

description:  

 

GRM™ MASTER DATASET 3.0 is a complete, multi-layered and fully deterministic dataset designed as a reference implementation of the GRM™ / UCA™ temporal–resonance framework.

 

The dataset integrates several analytical domains that are usually processed separately:

- physical time-series signals

- derivative-based transformations (TMap)

- phase and amplitude dynamics

- multi-layer coherence analysis (MLCI)

- temporal-flow reconstruction (TFR)

- time-localized resonance event detection

 

Together, these components form a coherent and structured view of temporal–resonance dynamics across multiple system layers.

 

All data are deterministic, reproducible, ASCII-compatible and suitable for scientific analysis, modelling, simulation and comparison with other classical or AI-based systems.

 

DATASET CONTENTS:

- Canonical TSV data (8-dimensional temporal embedding)

- TMap layer (first/second derivatives, variance, curvature, energy density)

- Phase–Temporal Metrics (phase, drift, harmonicity, envelope, resonance index)

- Multilayer Coherence (MLCI) – static and time-resolved

- Temporal Flow Reconstruction (TFR)

- Resonance Event Map

- Validation results (V1–V8)

- Release manifest + integrity hash for auditability

 

INTENDED USE:

- temporal and phase-based dynamics

- nonlinear dynamical systems

- multi-layer coherence and resonance modelling

- signal processing research

- GNSS-related phase/temporal modelling

- systems and theoretical physics

- development of AI models inspired by temporal structures

 

The dataset provides a complete, structured and reproducible pipeline that can serve as a foundation for further research, analysis and comparative studies.
DOI: 10.5281/zenodo.17751635
title: GMR™ - MASTER - DATASET - FINAL 3.0

description:  

 

GRM™ MASTER DATASET 3.0 is a complete, multi-layered and fully deterministic dataset designed as a reference implementation of the GRM™ / UCA™ temporal–resonance framework.

 

The dataset integrates several analytical domains that are usually processed separately:

- physical time-series signals

- derivative-based transformations (TMap)

- phase and amplitude dynamics

- multi-layer coherence analysis (MLCI)

- temporal-flow reconstruction (TFR)

- time-localized resonance event detection

 

Together, these components form a coherent and structured view of temporal–resonance dynamics across multiple system layers.

 

All data are deterministic, reproducible, ASCII-compatible and suitable for scientific analysis, modelling, simulation and comparison with other classical or AI-based systems.

 

DATASET CONTENTS:

- Canonical TSV data (8-dimensional temporal embedding)

- TMap layer (first/second derivatives, variance, curvature, energy density)

- Phase–Temporal Metrics (phase, drift, harmonicity, envelope, resonance index)

- Multilayer Coherence (MLCI) – static and time-resolved

- Temporal Flow Reconstruction (TFR)

- Resonance Event Map

- Validation results (V1–V8)

- Release manifest + integrity hash for auditability

 

INTENDED USE:

- temporal and phase-based dynamics

- nonlinear dynamical systems

- multi-layer coherence and resonance modelling

- signal processing research

- GNSS-related phase/temporal modelling

- systems and theoretical physics

- development of AI models inspired by temporal structures

 

The dataset provides a complete, structured and reproducible pipeline that can serve as a foundation for further research, analysis and comparative studies.
DOI: 10.15468/dl.qy29bg
title: Occurrence Download

description: A dataset containing 2890 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Diversidad taxonómica de las lianas de la cuenca del río Sinú en Córdoba (Colombia)"
 ]
}

 The dataset includes 2890 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014277-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17752113
title: Supplementary Information of Chapter 3 Ecological risk characterization of organic micropollutants in Flanders wastewater treatment plant effluents using a five-year monitoring database

description: This repository contains the supplementary datasets that support Chapter 3 of the PhD thesis entitled Ecological Risk Characterization of Organic Micropollutants in Flanders Wastewater Treatment Plant Effluents Using a Five Year Monitoring Database. This chapter is a redraft of:

 

Leekitratanapisan, W., and De Schamphelaere, K. A. C. (2025). Risk characterization of organic micropollutants in public wastewater treatment plant effluents in Flanders, Belgium. Integrated Environmental Assessment and Management, 21(4), 882 to 894. https://doi.org/10.1093/inteam/vjaf012

 

The chapter applies a substance specific ecological risk assessment to identify high priority organic micropollutants (OMPs) present in treated effluent from public wastewater treatment plants (WWTPs) in Flanders. The analysis uses a five year monitoring dataset from the Flanders Environment Agency (VMM) covering 2017 to 2021.

 

The supplementary tables included in this repository provide the complete numerical datasets underlying the occurrence analysis, ecological threshold value compilation, risk quotient calculations, and prioritization outcomes presented in Chapter 3. These datasets are made publicly available to ensure transparency and reproducibility, and to support further research in wastewater pollution assessment, mixture toxicity, and water quality management.

 

The repository contains the following supplementary tables:

 





Table S2. Limit of quantification (LOQ) values for all quantified OMPs included in the VMM monitoring dataset.




Table S3. Compilation of ecological threshold values (ETVs) used for risk characterization, including PNECfw, HC5 SSD chronic, PNECAlgae, PNECCrustacean, PNECFish, CEC, and PNECmic.




Table S4. Overview of all measured OMPs assigned to Exposure Groups 1 to 4 based on monitoring frequency and detection frequency across the 45 WWTPs.




Table S5. Summary of quantified OMPs with measured environmental concentrations (MEC) above LOQ, including median and site specific values used to derive MECregion.




Table S6. RQregion values for all quantified OMPs, calculated from the lowest available ecological threshold value for each compound. These values support the identification of high priority OMPs relevant to the updated EU Urban Wastewater Treatment Directive (2024).



 

 

Together, these tables provide the complete data foundation for Exposure Group classification, ecological threshold value selection, MECregion derivation, RQregion estimation, and prioritization of OMPs in Flemish WWTP effluents. The datasets are provided in machine readable formats to facilitate reuse in environmental risk assessment, regulatory evaluation, and model development.
DOI: 10.5281/zenodo.17752114
title: Supplementary Information of Chapter 3 Ecological risk characterization of organic micropollutants in Flanders wastewater treatment plant effluents using a five-year monitoring database

description: This repository contains the supplementary datasets that support Chapter 3 of the PhD thesis entitled Ecological Risk Characterization of Organic Micropollutants in Flanders Wastewater Treatment Plant Effluents Using a Five Year Monitoring Database. This chapter is a redraft of:

 

Leekitratanapisan, W., and De Schamphelaere, K. A. C. (2025). Risk characterization of organic micropollutants in public wastewater treatment plant effluents in Flanders, Belgium. Integrated Environmental Assessment and Management, 21(4), 882 to 894. https://doi.org/10.1093/inteam/vjaf012

 

The chapter applies a substance specific ecological risk assessment to identify high priority organic micropollutants (OMPs) present in treated effluent from public wastewater treatment plants (WWTPs) in Flanders. The analysis uses a five year monitoring dataset from the Flanders Environment Agency (VMM) covering 2017 to 2021.

 

The supplementary tables included in this repository provide the complete numerical datasets underlying the occurrence analysis, ecological threshold value compilation, risk quotient calculations, and prioritization outcomes presented in Chapter 3. These datasets are made publicly available to ensure transparency and reproducibility, and to support further research in wastewater pollution assessment, mixture toxicity, and water quality management.

 

The repository contains the following supplementary tables:

 





Table S2. Limit of quantification (LOQ) values for all quantified OMPs included in the VMM monitoring dataset.




Table S3. Compilation of ecological threshold values (ETVs) used for risk characterization, including PNECfw, HC5 SSD chronic, PNECAlgae, PNECCrustacean, PNECFish, CEC, and PNECmic.




Table S4. Overview of all measured OMPs assigned to Exposure Groups 1 to 4 based on monitoring frequency and detection frequency across the 45 WWTPs.




Table S5. Summary of quantified OMPs with measured environmental concentrations (MEC) above LOQ, including median and site specific values used to derive MECregion.




Table S6. RQregion values for all quantified OMPs, calculated from the lowest available ecological threshold value for each compound. These values support the identification of high priority OMPs relevant to the updated EU Urban Wastewater Treatment Directive (2024).



 

 

Together, these tables provide the complete data foundation for Exposure Group classification, ecological threshold value selection, MECregion derivation, RQregion estimation, and prioritization of OMPs in Flemish WWTP effluents. The datasets are provided in machine readable formats to facilitate reuse in environmental risk assessment, regulatory evaluation, and model development.
DOI: 10.15468/dl.yph6ws
title: Occurrence Download

description: A dataset containing 857 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia hilliana",
 "HasCoordinate is true"
 ]
}

 The dataset includes 857 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014278-251120083545085/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.29967553
title: Supplementary data for "<b>Unconventional components complement the cryptic kinetochore of the ciliate </b><b><i>Tetrahymena thermophila</i></b>"

description: Supplementary data for Ali, Raas <i>et al.</i> (2025) "<b>Unconventional components complement the cryptic kinetochore of the ciliate </b><b><i>Tetrahymena thermophila</i></b>"Supplementary files related to Fig. 2A --&gt; fig2a_supplementary_files.tar.gzContent: PDB files of predicted structures as displayed.Supplementary files related to Fig 3. --&gt; fig3_supplementary_files.tar.gzContent: HHsearch output of searches related to Fig. 3A, PDB files of predicted structures as displayed.Supplementary files related to Fig. 4B --&gt; fig4b_supplementary_files.tar.gzContent: Newick files of rooted phylogenetic trees as used for analysis in Fig. 4B.Supplementary files related to Fig. 5C --&gt; fig5_supplementary_data.xlsxContent: Excel file with data as plotted in Fig. 5C.Supplementary data related to Fig 6 --&gt; fig6_supplementary_data.tar.gzContent: PDB files of predicted structures shown in Fig. 6A, 6B as displayed, HHsearch output file of search of KiTT11 SANT domain profile against in-house database. The description of the in-house sequence database can be found in PMID: 37949928Supplementary data related to Fig 7 --&gt; Supplementary_data_figure7.tar.gzContent: Alignment underlying phylogenetic tree in figure 7A, Cellprofiler pipeline used for quantifications plottted in figure 7C-D and Excel files with the data underlying plots 7C-D.Alignment underlying phylogenetic tree as shown in Supplementary Figure 7 --&gt; figureS7_alignment.fasta<br>
DOI: 10.6084/m9.figshare.29967553.v1
title: Supplementary data for "<b>Unconventional components complement the cryptic kinetochore of the ciliate </b><b><i>Tetrahymena thermophila</i></b>"

description: Supplementary data for Ali, Raas <i>et al.</i> (2025) "<b>Unconventional components complement the cryptic kinetochore of the ciliate </b><b><i>Tetrahymena thermophila</i></b>"Supplementary files related to Fig. 2A --&gt; fig2a_supplementary_files.tar.gzContent: PDB files of predicted structures as displayed.Supplementary files related to Fig 3. --&gt; fig3_supplementary_files.tar.gzContent: HHsearch output of searches related to Fig. 3A, PDB files of predicted structures as displayed.Supplementary files related to Fig. 4B --&gt; fig4b_supplementary_files.tar.gzContent: Newick files of rooted phylogenetic trees as used for analysis in Fig. 4B.Supplementary files related to Fig. 5C --&gt; fig5_supplementary_data.xlsxContent: Excel file with data as plotted in Fig. 5C.Supplementary data related to Fig 6 --&gt; fig6_supplementary_data.tar.gzContent: PDB files of predicted structures shown in Fig. 6A, 6B as displayed, HHsearch output file of search of KiTT11 SANT domain profile against in-house database. The description of the in-house sequence database can be found in PMID: 37949928Supplementary data related to Fig 7 --&gt; Supplementary_data_figure7.tar.gzContent: Alignment underlying phylogenetic tree in figure 7A, Cellprofiler pipeline used for quantifications plottted in figure 7C-D and Excel files with the data underlying plots 7C-D.Alignment underlying phylogenetic tree as shown in Supplementary Figure 7 --&gt; figureS7_alignment.fasta<br>
DOI: 10.15468/dl.rassdh
title: Occurrence Download

description: A dataset containing 2436 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Epifitos vasculares y no vasculares en 11 remanentes de bosque seco tropical en el Valle del Cauca"
 ]
}

 The dataset includes 2436 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014279-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17739603
title: Interplay of Confinement and Localization in a Programmable Rydberg Atom Chain

description: Notebook with lines of code for producing the plots for the paper : "Interplay of Confinement and Localization in a Programmable Rydberg Atom Chain"
DOI: 10.5281/zenodo.17739602
title: Interplay of Confinement and Localization in a Programmable Rydberg Atom Chain

description: Notebook with lines of code for producing the plots for the paper : "Interplay of Confinement and Localization in a Programmable Rydberg Atom Chain"
DOI: 10.15468/dl.r645qh
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-93.40328 48.6201,-93.36616 48.6201,-93.36616 48.64498,-93.40328 48.64498,-93.40328 48.6201))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Insecta"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014281-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/xcrzrk
title: Thorbeckestraat 6, Arnhem, gemeente Arnhem: een bureauonderzoek

description: Bureau voor Archeologie heeft een bureauonderzoek uitgevoerd voor bouwwerkzaamheden aan de Thorbeckestraat 6 te Arnhem.
DOI: 10.15468/dl.gpfb75
title: Occurrence Download

description: A dataset containing 287 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "TaxonKey is Billbergia euphemiae"
 ]
}

 The dataset includes 287 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014280-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17722981
title: Exchange interaction in gate-defined quantum dots beyond the Hubbard model
DOI: 10.5281/zenodo.17722982
title: Exchange interaction in gate-defined quantum dots beyond the Hubbard model