cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17823713
title: Main data repository for Comparative mitochondrial proteomics across the tree of life reveals evolutionary, functional, and therapeutic insights

description: This repository contains the input and processed datasets used in the study “Comparative mitochondrial proteomics across the tree of life reveals evolutionary, functional, and therapeutic insights”, part of the MitoCarta Tree of Life (MitoTOL) project. The dataset spans 673 eukaryotic species and 34 downsampled prokaryotic groups and supports analyses of mitochondrial protein evolution, orthogroup inference, phylogenetic profiling, ancestral reconstructions, and eukaryogenesis timing.

The archive includes:

data.tar.gz — Primary datasets organized by analysis type, including orthogroup inference, phylogenetically-resolved orthogroup inference, DeepLoc retraining and prediction, phylogenetic profiling, taxonomic metadata, HGT, and reconstruction outputs.

alignments_and_initial_trees.tar.gz — Protein FASTA files, multiple sequence alignments, and maximum-likelihood phylogenies for each orthogroup.

pruned_rooted_trees.tar.gz — Pruned and rooted trees used for downstream reconciliation and timing analyses.

reconciled_consensus_trees_with_supports.tar.gz — Reconciled consensus protein trees with optimized branch lengths and node support values, along with pruned MSAs used to infer branch lengths.

reconciled_consensus_trees_for_Archaeplastida_timing.tar.gz — Reconciled consensus protein trees with optimized branch lengths for Archaeplastida-level timing inferences.

reconciled_consensus_trees_for_LECA_timing.tar.gz — Reconciled consensus protein trees with optimized branch lengths for LECA-level timing analyses.

reconciled_consensus_trees_branch_length_optimization_with_supports.tar.gz — AleRax reconciliation outputs, including samples of reconciled trees and majority-rule consensus trees.

species_fastas.tar.gz — Protein FASTA files for all eukaryotic species and prokaryotic groups included in the study.

All datasets follow consistent naming conventions (e.g., [Orthogroup_ID], [PhROG_ID], [TAXONOMY_ID]). Detailed documentation of file contents is provided in the accompanying README.txt.

The full computational workflow, including scripts for alignment, tree inference, reconciliation, phylogenetic profiling, and ancestral reconstructions, is available at:https://github.com/michaelzhuchen/mito-evolution

Please cite this dataset using 10.5281/zenodo.17823714.
DOI: 10.15468/dl.5j7f6m
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Orbiniella minuta",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046048-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dba2sb
title: Occurrence Download

description: A dataset containing 2169296 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Pheucticus ludovicianus)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1951",
 "Year is less than or equal to 2024",
 "Month is greater than or equal to April",
 "Month is less than or equal to July",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2169296 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046025-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zr68jy
title: Occurrence Download

description: A dataset containing 333 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phylo felix",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 333 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046050-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k9f5yj
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Protoariciella uncinata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046052-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/fnfcrd2scz
title: mydataset

description: 데이터셋이다
DOI: 10.17632/fnfcrd2scz.1
title: mydataset

description: 데이터셋이다
DOI: 10.6084/m9.figshare.29367797
title: Global change effects on nitrogen loss processes

description: Our analysis shows that N addition treatment significantly enhances both denitrification and anammox rates, while warming treatment also promotes denitrification.We searched the Web of Science database, Google Scholar, and the China National Knowledge Infrastructure for publications reporting the effects of experimental elevated CO<sub>2</sub>, N addition, warming, and altered precipitation manipulations on denitrification and/or anammox in the field. Here, we compiled a global dataset comprising 682 observations from 127 manipulative field experiments across the main terrestrial ecosystems.
DOI: 10.6084/m9.figshare.29367797.v2
title: Global change effects on nitrogen loss processes

description: Our analysis shows that N addition treatment significantly enhances both denitrification and anammox rates, while warming treatment also promotes denitrification.We searched the Web of Science database, Google Scholar, and the China National Knowledge Infrastructure for publications reporting the effects of experimental elevated CO<sub>2</sub>, N addition, warming, and altered precipitation manipulations on denitrification and/or anammox in the field. Here, we compiled a global dataset comprising 682 observations from 127 manipulative field experiments across the main terrestrial ecosystems.
DOI: 10.6084/m9.figshare.29367797.v3
title: Global change effects on nitrogen loss processes

description: Our analysis shows that N addition treatment significantly enhances both denitrification and anammox rates, while warming treatment also promotes denitrification.We searched the Web of Science database, Google Scholar, and the China National Knowledge Infrastructure for publications reporting the effects of experimental elevated CO<sub>2</sub>, N addition, warming, and altered precipitation manipulations on denitrification and/or anammox in the field. Here, we compiled a global dataset comprising 682 observations from 127 manipulative field experiments across the main terrestrial ecosystems.
DOI: 10.17632/bg6j8h8j7y
title: X-SIAGA pilot dataset

description: This dataset contains pilot data from the X-SIAGA study, a household-level Disease X and outbreak preparedness intervention for Orang Asli (Indigenous) households in Selangor, Malaysia. The aim of this dataset is to demonstrate the preliminary effectiveness of X-SIAGA on household outbreak preparedness.

Data were collected using the Household Outbreak Preparedness Evaluation (HOPE) questionnaire administered to adult household representatives at two time points: before and immediately after the intervention. Each row represents one household, with variables indicating household characteristics and scores at both time points.
DOI: 10.17632/bg6j8h8j7y.1
title: X-SIAGA pilot dataset

description: This dataset contains pilot data from the X-SIAGA study, a household-level Disease X and outbreak preparedness intervention for Orang Asli (Indigenous) households in Selangor, Malaysia. The aim of this dataset is to demonstrate the preliminary effectiveness of X-SIAGA on household outbreak preparedness.

Data were collected using the Household Outbreak Preparedness Evaluation (HOPE) questionnaire administered to adult household representatives at two time points: before and immediately after the intervention. Each row represents one household, with variables indicating household characteristics and scores at both time points.
DOI: 10.15468/dl.x5huup
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scoloplella capensis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046054-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/cgwjshkx5k
title: Monthly Division-Level Dengue Cases & Mortality with Climate and Environmental Indicators in Bangladesh (2020–2025)

description: This dataset compiles monthly dengue surveillance statistics and associated environmental conditions for all eight administrative divisions of Bangladesh (Barishal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur and Sylhet) covering January 2020 through December 2025. Each record represents a specific division–month pair and includes:

-Division, Year and Month: Administrative division and the month/year of observation.
-Pollution: Qualitative level of ambient air pollution (“High,” “Medium,” “Low”).
-Density: Qualitative population density category for the division (“High,” “Medium,” “Low”).
-Infected and Death: Number of laboratory-confirmed dengue cases and associated deaths in the given month.
-Temperature: Average monthly air temperature (°C).
-Humidity: Average monthly relative humidity (fractional values between 0 and 1).
-Pressure: Average monthly atmospheric pressure (mbar).
-Class: A derived dengue alert level (“High,” “Medium,” “Low” or “Very Low”), calculated using infection and death rates.

The dataset contains 574 rows and 11 columns. It can be used to explore correlations between dengue incidence and environmental factors, develop predictive models for dengue outbreaks, and examine regional differences in disease burden. The inclusion of the “Class” label enables supervised learning for classification tasks (e.g., forecasting dengue alert levels for upcoming months), while raw counts and environmental variables support regression and correlation analyses.
Data were collated from government health bulletins, meteorological reports and publicly available environmental datasets, then aggregated by division and month. Researchers may reuse or adapt this dataset for epidemiological modelling, climate–health studies or public health decision support.
DOI: 10.17632/cgwjshkx5k.2
title: Monthly Division-Level Dengue Cases & Mortality with Climate and Environmental Indicators in Bangladesh (2020–2025)

description: This dataset compiles monthly dengue surveillance statistics and associated environmental conditions for all eight administrative divisions of Bangladesh (Barishal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur and Sylhet) covering January 2020 through December 2025. Each record represents a specific division–month pair and includes:

-Division, Year and Month: Administrative division and the month/year of observation.
-Pollution: Qualitative level of ambient air pollution (“High,” “Medium,” “Low”).
-Density: Qualitative population density category for the division (“High,” “Medium,” “Low”).
-Infected and Death: Number of laboratory-confirmed dengue cases and associated deaths in the given month.
-Temperature: Average monthly air temperature (°C).
-Humidity: Average monthly relative humidity (fractional values between 0 and 1).
-Pressure: Average monthly atmospheric pressure (mbar).
-Class: A derived dengue alert level (“High,” “Medium,” “Low” or “Very Low”), calculated using infection and death rates.

The dataset contains 574 rows and 11 columns. It can be used to explore correlations between dengue incidence and environmental factors, develop predictive models for dengue outbreaks, and examine regional differences in disease burden. The inclusion of the “Class” label enables supervised learning for classification tasks (e.g., forecasting dengue alert levels for upcoming months), while raw counts and environmental variables support regression and correlation analyses.
Data were collated from government health bulletins, meteorological reports and publicly available environmental datasets, then aggregated by division and month. Researchers may reuse or adapt this dataset for epidemiological modelling, climate–health studies or public health decision support.
DOI: 10.17632/rtn8t47t6j
title: Online housing search dataset: Information flows of real estate platform users

description: The information flow data are generated from user-generated data of Funda.nl, the largest online housing market platform of the Netherlands. The datasets contain the inflow and outflow of hits (mouse clicks, opening of webpages, etc.) from one municipality to another, where the municipality of the user defines the origin and the municipality of the property that is viewed defines the destination. The data capture real behavior of the platform users. The flow data are based on 1.1 billion hits that are made by the users of the website in the first six months of 2018. The underlying data are collected by Google Analytics, Google's web analytics service. Funda uses these data for statistics to gain insights in the platform's usage, to maintain platform stability, and for product development. These proprietary data of Funda are used to generate the information flows between municipalities. In the full sample we have 148,216 information flows between municipalities in the Netherlands, among which 313 zero flows. The data include subsamples for different types of platform users as user search intentions range from serious to fully recreational. The data enable researchers to analyse housing search behavior from a novel perspective. The data are, for instance, relevant for housing market researchers, digital economists, and economic geographers.
DOI: 10.17632/rtn8t47t6j.3
title: Online housing search dataset: Information flows of real estate platform users

description: The information flow data are generated from user-generated data of Funda.nl, the largest online housing market platform of the Netherlands. The datasets contain the inflow and outflow of hits (mouse clicks, opening of webpages, etc.) from one municipality to another, where the municipality of the user defines the origin and the municipality of the property that is viewed defines the destination. The data capture real behavior of the platform users. The flow data are based on 1.1 billion hits that are made by the users of the website in the first six months of 2018. The underlying data are collected by Google Analytics, Google's web analytics service. Funda uses these data for statistics to gain insights in the platform's usage, to maintain platform stability, and for product development. These proprietary data of Funda are used to generate the information flows between municipalities. In the full sample we have 148,216 information flows between municipalities in the Netherlands, among which 313 zero flows. The data include subsamples for different types of platform users as user search intentions range from serious to fully recreational. The data enable researchers to analyse housing search behavior from a novel perspective. The data are, for instance, relevant for housing market researchers, digital economists, and economic geographers.
DOI: 10.17632/8w7jrp324p
title: SPSS raw data

description: attachment #1: 305 cases of raw SPSS data.
attachment #2: SPSS analysis results based on the raw data.
attachment #3: AMOS measurement model.
attachment #4: AMOS structural (research) model.
attachment #5, #6: AMOS multi-group analysis.
DOI: 10.17632/8w7jrp324p.1
title: SPSS raw data

description: attachment #1: 305 cases of raw SPSS data.
attachment #2: SPSS analysis results based on the raw data.
attachment #3: AMOS measurement model.
attachment #4: AMOS structural (research) model.
attachment #5, #6: AMOS multi-group analysis.
DOI: 10.15468/dl.tf2gef
title: Occurrence Download

description: A dataset containing 113556 species occurrences available in GBIF matching the query:
{
 "and" : [
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Lynx lynx"
 ]
}

 The dataset includes 113556 records from 258 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046038-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/77gp6jr7fh
title: LFQ Quantitative Proteomics Testing Report（Supplementary File S1）

description: The TLs group's liver tissues were gathered, and Shanghai Biotree Biomedical Technology Co., Ltd. (Shanghai, China) developed a label-free quantitative proteomics technique. After combining the liver tissue samples with the proper quantity of RIPA working solution, they were crushed on ice for five minutes. Following a 15-minute centrifugation at 12,000 rpm at 4 ℃, the supernatant was moved to a fresh EP tube. The BCA technique was used to determine the extracted protein content. Following acetone precipitation, redissolving, reduction, alkylation, protein digestion, SDC cleanup, and peptide desalting, the protein was ready for detection. Relevant supporting data (including SDS-PAGE images, peptide yield quantification results, and LC-MS/MS total ion current plots) are provided in Supplementary File S1.
DOI: 10.17632/77gp6jr7fh.1
title: LFQ Quantitative Proteomics Testing Report（Supplementary File S1）

description: The TLs group's liver tissues were gathered, and Shanghai Biotree Biomedical Technology Co., Ltd. (Shanghai, China) developed a label-free quantitative proteomics technique. After combining the liver tissue samples with the proper quantity of RIPA working solution, they were crushed on ice for five minutes. Following a 15-minute centrifugation at 12,000 rpm at 4 ℃, the supernatant was moved to a fresh EP tube. The BCA technique was used to determine the extracted protein content. Following acetone precipitation, redissolving, reduction, alkylation, protein digestion, SDC cleanup, and peptide desalting, the protein was ready for detection. Relevant supporting data (including SDS-PAGE images, peptide yield quantification results, and LC-MS/MS total ion current plots) are provided in Supplementary File S1.
DOI: 10.17632/6wzn6pxjsc.1
title: Automated Detection and Site-scale Vegetation Shift Analysis for Individual Heritage Buildings along the Great Wall

description: This dataset comprises the training and testing samples utilized for developing the IHBSegNet model. Furthermore, it includes the quantitative results of site-scale vegetation density dynamics across the Fugu, Shenmu, and Yuyang sections of the Great Wall. These results are archived in CSV format, where the 2nd and 5th columns correspond to the Net Class Shift and Mean Class Shift metrics, respectively. Additionally, the associated scripts are provided to facilitate statistical analysis and data visualization.
DOI: 10.15468/4gyj8d
title: Dalodesmid millipedes from alpine and subalpine habitats in New South Wales and Victoria, Australia (Diplopoda, Polydesmida, Dalodesmidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Mesibov, Robert (2025): Dalodesmid millipedes from alpine and subalpine habitats in New South Wales and Victoria, Australia (Diplopoda, Polydesmida, Dalodesmidae). ZooKeys 1262: 303-333, DOI: 10.3897/zookeys.1262.176273AbstractEleven new species of Dalodesmidae (Diplopoda, Polydesmida) are described: Araneopedis porchi gen. nov. et sp. nov. (type species), A. bogong sp. nov., A. buffalo sp. nov., A. dargo sp. nov., A. gibbae sp. nov.; Cernethia dysmica sp. nov.; Dibologonus sladei gen. nov. et sp. nov. (type species), D. major sp. nov., D. minor sp. nov., D. oedipus sp. nov.; Polydactylogonus sanctogwinear gen. nov. et sp. nov. (type and only species). Males of D. oedipus sp. nov. have modified legpairs 13, 15 or 17, with reduced prefemur, femur and postfemur, and fused, swollen tibia and tarsus. New locality records are presented for the dalodesmids Cernethia inopinata Mesibov, 2015, Lissodesmus milledgei Mesibov, 2006 and Orthorhachis durabilis Mesibov, 2008.
DOI: 10.17632/sf7fs2gjgh.1
title: Critical remarks on the report "THE SCATTERING INTEGRALS: INTEGRATION AND ACCURACY'" by H.G. Schlager and W. Eckstein

description: The scattering integrals and related quantities for the Molière, the ZBL, and the Kr-C interatomic interaction potentials, calculated using a 10,000-point Gauss-Mehler procedure. 
Naming convention for the scattering integral files is as follows:
"potential_the reduced energy_Nthe number of points in the Gauss-Mehler procedure_table.dat".
E.g., "krc_0.3000E-5_N10000_table.dat" provides a data table for the Kr-C potential of the reduced energy of 3 times 10 to the minus 6th power, calculated with 10000 points.
"mol" denotes the Molière potential, and "zbl" denotes the universal Ziegler-Biersack-Littmark (ZBL) potential. 
Files "mistaken_krc_*.dat" provide the calculation results for the Kr-C potential with the mistaken constant c3=0.355, which was used in the report by Schlager and Eckstein (1989).
Mostly, column names in the files are self-explanatory. The 6th column gives the values of the time integral in the formulation by Leibfried (see G. Leibfried, Brstrahlungseelzte in Festkörpern (Teubner, Stuttgart, 1965), pp. 43-44), which is not discussed in the paper. The 9th column shows the values of the absolute error in the value of the differential scattering cross-section.
DOI: 10.15468/dl.rcp2xr
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Neanthes zonata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 19 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046055-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/czcgb83v6f
title: Distinct Glucose Profiles with Daily and Weekly Growth Hormone Therapy Revealed by Continuous Glucose Monitoring

description: Supplementary data supporting the findings of the study "Distinct Glucose Profiles with Daily and Weekly Growth Hormone Therapy Revealed by Continuous Glucose Monitoring"
It contains anonymized participant-level CGM data and additional statistics.