cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0182596.10fu
title: SH0182596.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0182597.10fu
title: SH0182597.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/f8hfez
title: Collected and observed Noctuoidea specimens from Mizoram

description: Samples collected from a survey in Mizoram in the year 2024 from the month of April-July.
DOI: 10.15468/dl.sfe87g
title: Occurrence Download

description: A dataset containing 13053 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Mesembryanthemum crystallinum L.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 13053 records from 160 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015288-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15189215
title: Analyse comparative de trois algorithmes d'optimisation sur les fonctions BBOB

description: Ce dépôt contient les scripts Python utilisés pour analyser les performances des algorithmes BAYEDA, ALPS et RANDOMSEARCH-5 sur cinq fonctions BBOB (F1, F7, F12, F18, F24).  Les figures et statistiques sont générées automatiquement à partir des fichiers de données.  Les scripts sont reproductibles : il suffit d’ajuster les chemins vers les données selon votre environnement local.  Voir README.md pour plus de détails.
DOI: 10.5281/zenodo.15189216
title: Analyse comparative de trois algorithmes d'optimisation sur les fonctions BBOB

description: Ce dépôt contient les scripts Python utilisés pour analyser les performances des algorithmes BAYEDA, ALPS et RANDOMSEARCH-5 sur cinq fonctions BBOB (F1, F7, F12, F18, F24).  Les figures et statistiques sont générées automatiquement à partir des fichiers de données.  Les scripts sont reproductibles : il suffit d’ajuster les chemins vers les données selon votre environnement local.  Voir README.md pour plus de détails.
DOI: 10.15468/dl.5ur543
title: Occurrence Download

description: A dataset containing 215 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Lonicera splendida Boiss.",
 "Year 1950-2025"
 ]
}

 The dataset includes 215 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015290-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cpnhnb
title: Occurrence Download

description: A dataset containing 1501 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Japan",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Carex siderosticta Hance"
 ]
}

 The dataset includes 1501 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015291-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15186871
title: filanesib-hepatoblastoma

description: CellProfiler extracted single-cell features analysed in paper: "Nousiainen et al. (2025). Functional screening identifies kinesin spindle protein inhibitor filanesib as a potential treatment option for hepatoblastoma".
DOI: 10.5281/zenodo.15186872
title: filanesib-hepatoblastoma

description: CellProfiler extracted single-cell features analysed in paper: "Nousiainen et al. (2025). Functional screening identifies kinesin spindle protein inhibitor filanesib as a potential treatment option for hepatoblastoma".
DOI: 10.5281/zenodo.15181488
title: Raw data for "Blue or far-red light supplementation induced pre-hardening in the leaves of the Rht12 wheat dwarfing line: hormonal changes and freezing tolerance"

description: Excel raw data for Figure 4 and 5 in a publication: "Blue or far-red light supplementation induced pre-hardening in the leaves of the Rht12 wheat dwarfing line: hormonalchanges and freezing tolerance"
DOI: 10.5281/zenodo.15181489
title: Raw data for "Blue or far-red light supplementation induced pre-hardening in the leaves of the Rht12 wheat dwarfing line: hormonal changes and freezing tolerance"

description: Excel raw data for Figure 4 and 5 in a publication: "Blue or far-red light supplementation induced pre-hardening in the leaves of the Rht12 wheat dwarfing line: hormonalchanges and freezing tolerance"
DOI: 10.5281/zenodo.14753832
title: Abnormal Mutations: Evolution Strategies Don't Require Gaussianity

description: # Requirements

In order to run the algorithms and create all the figures for the paper `Abnormal Mutations`, we need the following Python packages installed. The Python version that was used to generate the data is Python 3.10.12.


    - iohinspector==0.0.1

    - numpy==1.26.4

    - matplotlib==3.8.3

    - modcma==1.0.9

    - pandas==2.2.2

    - polars==1.17.1

    - seaborn==0.13.2

    - scipy==1.12.0


# Scripts

All scripts and notebooks used to generate the data can be found in the repository: https://github.com/IOHprofiler/ModularCMAES. To get the version that was used here, please use the v1.0.9 tag, or download the corresponding release. Specific scrips are also included here for convinience.


# Collecting data

All the data can be collected by runnning the `run.sh` script, found in the directory scripts/distributions. This calles the script `run.py`, which executes the algorithms, and stores performance data in the `data` folder. This folder is also uploaded as a zipped directory on zenodo.


# Creating figures

The notebook `plots.ipynb` can be used to generate all the non-ecdf plots in the paper. The notebook `ecdf_plots.ipynb` can be used to generate all the performance plots used in the paper. The second notebook requires the installation of the `iohinspector` library, currently in pre-release. It can be downloaded and installed via github: https://github.com/IOHprofiler/IOHinspector. The version used here can be accessed via the commit: 8e6bb06. All figures from the paper, included a few additional ones, are included on zenodo.
DOI: 10.5281/zenodo.14753833
title: Abnormal Mutations: Evolution Strategies Don't Require Gaussianity

description: # Requirements

In order to run the algorithms and create all the figures for the paper `Abnormal Mutations`, we need the following Python packages installed. The Python version that was used to generate the data is Python 3.10.12.


    - iohinspector==0.0.1

    - numpy==1.26.4

    - matplotlib==3.8.3

    - modcma==1.0.9

    - pandas==2.2.2

    - polars==1.17.1

    - seaborn==0.13.2

    - scipy==1.12.0


# Scripts

All scripts and notebooks used to generate the data can be found in the repository: https://github.com/IOHprofiler/ModularCMAES. To get the version that was used here, please use the v1.0.9 tag, or download the corresponding release. Specific scrips are also included here for convinience.


# Collecting data

All the data can be collected by runnning the `run.sh` script, found in the directory scripts/distributions. This calles the script `run.py`, which executes the algorithms, and stores performance data in the `data` folder. This folder is also uploaded as a zipped directory on zenodo.


# Creating figures

The notebook `plots.ipynb` can be used to generate all the non-ecdf plots in the paper. The notebook `ecdf_plots.ipynb` can be used to generate all the performance plots used in the paper. The second notebook requires the installation of the `iohinspector` library, currently in pre-release. It can be downloaded and installed via github: https://github.com/IOHprofiler/IOHinspector. The version used here can be accessed via the commit: 8e6bb06. All figures from the paper, included a few additional ones, are included on zenodo.
DOI: 10.5281/zenodo.15189142
title: Abnormal Mutations: Evolution Strategies Don't Require Gaussianity

description: # Requirements

In order to run the algorithms and create all the figures for the paper `Abnormal Mutations`, we need the following Python packages installed. The Python version that was used to generate the data is Python 3.10.12.


    - iohinspector==0.0.1

    - numpy==1.26.4

    - matplotlib==3.8.3

    - modcma==1.0.9

    - pandas==2.2.2

    - polars==1.17.1

    - seaborn==0.13.2

    - scipy==1.12.0


# Scripts

All scripts and notebooks used to generate the data can be found in the repository: https://github.com/IOHprofiler/ModularCMAES. To get the version that was used here, please use the v1.0.9 tag, or download the corresponding release. Specific scrips are also included here for convinience.


# Collecting data

All the data can be collected by runnning the `run.sh` script, found in the directory scripts/distributions. This calles the script `run.py`, which executes the algorithms, and stores performance data in the `data` folder. This folder is also uploaded as a zipped directory on zenodo.


# Creating figures

The notebook `plots.ipynb` can be used to generate all the non-ecdf plots in the paper. The notebook `ecdf_plots.ipynb` can be used to generate all the performance plots used in the paper. The second notebook requires the installation of the `iohinspector` library, currently in pre-release. It can be downloaded and installed via github: https://github.com/IOHprofiler/IOHinspector. The version used here can be accessed via the commit: 8e6bb06. All figures from the paper, included a few additional ones, are included on zenodo.
DOI: 10.7289/v56h4fg9
title: Marine Biogeographic Assessment of the Main Hawaiian Islands: Synthesized physical and biological data offshore of the Main Hawaiian Islands from 1891-01-01 to 2015-03-01 (NCEI Accession 0155189)

description: This dataset contains analyses and data products used in a marine biogeographic assessment of the main Hawaiian Islands. The Bureau of Ocean Energy Management (BOEM) regulates the leasing, construction and operation of renewable energy projects in federal waters, and is required to evaluate potential human, coastal and marine impacts from these projects. In 2013, the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) partnered with BOEM to support their review of renewable energy lease requests offshore of the Main Hawaiian Islands (MHI). Collaborations with a variety of local federal, state, academic and non-governmental organizations were crucial for this work. NCCOS compiled existing, readily-available spatial data and synthesized new products around the MHI, describing the physical and biological marine environment, benthic habitats, fishes, sea turtles, marine mammals, and seabirds. Analyses and data products were specifically tailored to meet BOEM’s needs, and to fit within BOEM’s framework of offshore lease blocks. Data products range from simple animal distribution maps to mathematical models depicting the predicted distributions of animals. For some animals, this assessment marks the first time that their space-use patterns were mapped or modeled in the MHI, and made available online. These datasets are one component of the larger BOEM and State of Hawai‘i processes to evaluate offshore renewable energy proposals around the MHI.
DOI: 10.15468/dl.kbq57w
title: Occurrence Download

description: A dataset containing 4032 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acer granatense Boiss.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4032 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015295-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fsjbgk
title: Occurrence Download

description: A dataset containing 343 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Miscanthus nepalensis (Trin.) Hack.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 343 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015296-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15187847
title: Improved 8-day version 6.1 Terra–Aqua MODIS cloud-free snow cover and Randolph Glacier Inventory 6.0 product for high-mountain Asia between 2002 and 2022

description: The product contains improved MODIS 8-day Terra (MOD10A2) and Aqua (MYD10A2) collection 6.1 snow-cover composite product merged with Randolph Glacier Inventory (RGI6.0). The product is generated using MODIS Terra and Aqua 8-day snow cover products MOD10A2 and MYD10A2 collection 6.1 (C61), respectively. The data covers High Mountain Asia (HMA) covering latitude 24.32 − 49.19 N and Longitude 58.22 − 122.48 E. The data is available with eight-day temporal resolution and 500 m spatial resolution covering the period between 2002 and 2022. The name of the product is derived from MODIS Terra (MOD) MODIS Aqua (MYD), and Glacier (GL), Version 6.1 (61) as M*D10A2V61GL. The product is described in ordinal date and each year has 46 eight-day composite images in GeoTIFF file format. The data is described by the values 25, 50, 198, 199, 200, 238, 239, 240, 242, 248, 249, 250, and 252. Following is the description of values in the improved combined snow product 25: No Snow classes 50: Cloud 198: Snow only in Terra 199: Snow only in Aqua 200: Snow in both Terra and Aqua 238: Debris-covered ice with Terra Snow 239: Debris-covered ice with Aqua Snow 240: Exposed debris-covered ice 242: Debris-covered ice with Snow in both Terra and Aqua 248: Debris-free ice with Terra Snow 249: Debris-free ice with Aqua Snow 250: Exposed debris-free ice 252: Debris-free ice with snow in both Terra and Aqua.
DOI: 10.5281/zenodo.15187848
title: Improved 8-day version 6.1 Terra–Aqua MODIS cloud-free snow cover and Randolph Glacier Inventory 6.0 product for high-mountain Asia between 2002 and 2022

description: The product contains improved MODIS 8-day Terra (MOD10A2) and Aqua (MYD10A2) collection 6.1 snow-cover composite product merged with Randolph Glacier Inventory (RGI6.0). The product is generated using MODIS Terra and Aqua 8-day snow cover products MOD10A2 and MYD10A2 collection 6.1 (C61), respectively. The data covers High Mountain Asia (HMA) covering latitude 24.32 − 49.19 N and Longitude 58.22 − 122.48 E. The data is available with eight-day temporal resolution and 500 m spatial resolution covering the period between 2002 and 2022. The name of the product is derived from MODIS Terra (MOD) MODIS Aqua (MYD), and Glacier (GL), Version 6.1 (61) as M*D10A2V61GL. The product is described in ordinal date and each year has 46 eight-day composite images in GeoTIFF file format. The data is described by the values 25, 50, 198, 199, 200, 238, 239, 240, 242, 248, 249, 250, and 252. Following is the description of values in the improved combined snow product 25: No Snow classes 50: Cloud 198: Snow only in Terra 199: Snow only in Aqua 200: Snow in both Terra and Aqua 238: Debris-covered ice with Terra Snow 239: Debris-covered ice with Aqua Snow 240: Exposed debris-covered ice 242: Debris-covered ice with Snow in both Terra and Aqua 248: Debris-free ice with Terra Snow 249: Debris-free ice with Aqua Snow 250: Exposed debris-free ice 252: Debris-free ice with snow in both Terra and Aqua.
DOI: 10.15468/dl.jj6ynn
title: Occurrence Download

description: A dataset containing 3640 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Mosla dianthera (Buch.-Ham. ex Roxb.) Maxim.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 3640 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015299-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cr2c6n
title: Occurrence Download

description: A dataset containing 76330 records in GBIF matching the query:
SELECT speciesKey, MIN(decimalLatitude) AS minLatitude, MAX(decimalLatitude) AS maxLatitude, MIN(decimalLongitude) AS minLongitude, MAX(decimalLongitude) AS maxLongitude, MIN("year") AS minYear, MAX("year") AS maxYear FROM occurrence WHERE speciesKey IS NOT NULL AND occurrenceStatus = 'PRESENT' AND countryCode = 'DE' AND hasCoordinate = TRUE AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE') GROUP BY speciesKey

 The dataset's 76330 records were derived from 2874 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015293-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zcortv
title: Occurrence Download

description: A dataset containing 738 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Salvia lanigera Poir.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 738 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004474-180412121330197/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.iusxbu
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Marmosops bishopi (Pine, 1981)",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 14 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007344-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vj8oik
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Barbula majuscula Müll.Hal.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022983-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bp4tzm
title: Occurrence Download

description: A dataset containing 2605 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Crax fasciolata Spix, 1825"
 ]
}

 The dataset includes 2605 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007344-180730143533302/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6dbjq4
title: Occurrence Download

description: A dataset containing 1908 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Michelia compressa (Maxim.) Sarg."
 ]
}

 The dataset includes 1908 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004474-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qg3bwv
title: Occurrence Download

description: A dataset containing 323 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-5050.0",
 "TaxonKey is Carcharodon carcharias (Linnaeus, 1758)",
 "Year 2000-2021"
 ]
}

 The dataset includes 323 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023308-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.phfp3i
title: Occurrence Download

description: A dataset containing 15103 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Actinotia polyodon (Clerck, 1759)"
 ]
}

 The dataset includes 15103 records from 99 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007344-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zawx1m
title: Occurrence Download

description: A dataset containing 181 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pilea glabra S.Watson"
 ]
}

 The dataset includes 181 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004474-180730143533302/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.