cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1083752.10fu
title: SH1083752.10FU

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/sh1083754.10fu
title: SH1083754.10FU

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/sh1083758.10fu
title: SH1083758.10FU

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/sh1083762.10fu
title: SH1083762.10FU

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/sh1083763.10fu
title: SH1083763.10FU

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/sh1083767.10fu
title: SH1083767.10FU

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/sh1083768.10fu
title: SH1083768.10FU

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/sh1083770.10fu
title: SH1083770.10FU

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/sh1083774.10fu
title: SH1083774.10FU

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/sh1083781.10fu
title: SH1083781.10FU

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/dl.wjjtb4
title: Occurrence Download

description: A dataset containing 260564 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Réserves Naturelles de France (RNF) - RNF - Données de la Fédération des Réserves Catalanes"
 ]
}

 The dataset includes 260564 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081087-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.88uky3
title: Occurrence Download

description: A dataset containing 1433 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Loxia curvirostra Linnaeus, 1758",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 1433 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081106-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11489843
title: FedscGen: privacy-aware federated batch effect correction of single-cell RNA sequencing data -- Preprocessed datasets

description: This dataset accompanies the publication "FedscGen: Privacy-Aware Federated Batch Effect Correction of Single-Cell RNA Sequencing Data" and includes eight single-cell RNA sequencing (scRNA-seq) datasets used to benchmark the FedscGen and scGen methods. The datasets are provided in .h5ad format and include comprehensive metadata necessary for replication and further analysis.

Datasets

We analyze various datasets to compare FedscGen against scGen (centralized) in terms of batch correction. For simplicity, we refer to the dataset by abbreviations:





Cell Line (CL):



Derived from the 293t_jurkat experiment with three batches: Zheng et al., 2017.





Human Dendritic Cells (HDC):



scRNA-seq data of human dendritic cells across two batches: Villani et al., 2017.





Human Pancreas (HP):



Consolidated data from five sources with 14,767 cells each: Baron et al., 2016; Muraro et al., 2016; Segerstolpe et al., 2016; Wang et al., 2016; Xin et al., 2016.





Mouse Brain (MB):



Merged datasets with 691,600 and 141,606 cells: Saunders et al., 2018; Rosenberg et al., 2018.





Mouse Cell Atlas (MCA):



Data focusing on 11 cell types from various organs: Han et al., 2018; The Tabula Muris Consortium, 2018.





Mouse Hematopoietic Stem and Progenitor Cells (MHSPC):



Data from SMART-seq2 and MARS-seq protocols: Nestorowa et al., 2016; Paul et al., 2015.





Mouse Retina (MR):



Data from two unassociated laboratories with 26,830 and 44,808 cells: Macosko et al., 2015; Shekhar et al., 2016.





PBMC (human Peripheral Blood Mononuclear Cell):



scRNA-seq data with two batches: Zheng et al., 2017.




Usage Notes: Each dataset is provided in .h5ad format, compatible with common single-cell analysis tools such as Scanpy. Detailed metadata is included within each file.

Keywords: Single-cell RNA sequencing, scRNA-seq, Batch effect correction, Privacy-aware, Federated learning, scGen, FedscGen, Clinical multi-center studies, Genomics, Bioinformatics

Contact: For questions or further information, please contact Mohammad Bakhtiari at mohammad.bakhtiari@uni-hamburg.de.

License: Creative Commons Attribution 4.0 International (CC BY 4.0)
DOI: 10.5281/zenodo.11489844
title: FedscGen: privacy-aware federated batch effect correction of single-cell RNA sequencing data -- Preprocessed datasets

description: This dataset accompanies the publication "FedscGen: Privacy-Aware Federated Batch Effect Correction of Single-Cell RNA Sequencing Data" and includes eight single-cell RNA sequencing (scRNA-seq) datasets used to benchmark the FedscGen and scGen methods. The datasets are provided in .h5ad format and include comprehensive metadata necessary for replication and further analysis.

Datasets

We analyze various datasets to compare FedscGen against scGen (centralized) in terms of batch correction. For simplicity, we refer to the dataset by abbreviations:





Cell Line (CL):



Derived from the 293t_jurkat experiment with three batches: Zheng et al., 2017.





Human Dendritic Cells (HDC):



scRNA-seq data of human dendritic cells across two batches: Villani et al., 2017.





Human Pancreas (HP):



Consolidated data from five sources with 14,767 cells each: Baron et al., 2016; Muraro et al., 2016; Segerstolpe et al., 2016; Wang et al., 2016; Xin et al., 2016.





Mouse Brain (MB):



Merged datasets with 691,600 and 141,606 cells: Saunders et al., 2018; Rosenberg et al., 2018.





Mouse Cell Atlas (MCA):



Data focusing on 11 cell types from various organs: Han et al., 2018; The Tabula Muris Consortium, 2018.





Mouse Hematopoietic Stem and Progenitor Cells (MHSPC):



Data from SMART-seq2 and MARS-seq protocols: Nestorowa et al., 2016; Paul et al., 2015.





Mouse Retina (MR):



Data from two unassociated laboratories with 26,830 and 44,808 cells: Macosko et al., 2015; Shekhar et al., 2016.





PBMC (human Peripheral Blood Mononuclear Cell):



scRNA-seq data with two batches: Zheng et al., 2017.




Usage Notes: Each dataset is provided in .h5ad format, compatible with common single-cell analysis tools such as Scanpy. Detailed metadata is included within each file.

Keywords: Single-cell RNA sequencing, scRNA-seq, Batch effect correction, Privacy-aware, Federated learning, scGen, FedscGen, Clinical multi-center studies, Genomics, Bioinformatics

Contact: For questions or further information, please contact Mohammad Bakhtiari at mohammad.bakhtiari@uni-hamburg.de.

License: Creative Commons Attribution 4.0 International (CC BY 4.0)
DOI: 10.15468/dl.6chknt
title: Occurrence Download

description: A dataset containing 150435 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is CEDaR Online Recording"
 ]
}

 The dataset includes 150435 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081086-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f72ub8
title: Occurrence Download

description: A dataset containing 1007039 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "DatasetKey is EOD – eBird Observation Dataset",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Haliaeetus leucocephalus (Linnaeus, 1766)",
 "Year 2015-2025"
 ]
}

 The dataset includes 1007039 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081071-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a9pd5q
title: Occurrence Download

description: A dataset containing 181846 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Miscellaneous records held by BIS"
 ]
}

 The dataset includes 181846 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081088-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2c9ebn
title: Occurrence Download

description: A dataset containing 2478 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Xylocarpus rumphii (Kostel.) Mabb., Xylocarpus moluccensis (Lam.) M.Roem., Xylocarpus granatum J.Koenig)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2478 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081108-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cf88by
title: Occurrence Download

description: A dataset containing 48298 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Elaeagnus umbellata Thunb."
 ]
}

 The dataset includes 48298 records from 424 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081107-250525065834625/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.29435822
title: diffResults from GPSAdb2.0

description: diffResults from GPSAdb2.0
DOI: 10.6084/m9.figshare.29435822.v1
title: diffResults from GPSAdb2.0

description: diffResults from GPSAdb2.0
DOI: 10.6084/m9.figshare.29437550
title: Datasets for Fig.2

description: band_data_for_fig2a.npz: Band structure data for 3L MBT. Opened in pythondata_for_fig2b.txt: well-quantized layer Chern numbers for 3L,6L,9L MBT
DOI: 10.6084/m9.figshare.29437550.v1
title: Datasets for Fig.2

description: band_data_for_fig2a.npz: Band structure data for 3L MBT. Opened in pythondata_for_fig2b.txt: well-quantized layer Chern numbers for 3L,6L,9L MBT
DOI: 10.15468/dl.3vv8ja
title: Occurrence Download

description: A dataset containing 28976 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ostrya virginiana (Mill.) K.Koch"
 ]
}

 The dataset includes 28976 records from 364 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081111-250525065834625/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.29432150.v1
title: Supplemental information for the manuscript submitted to Horticulture Research (HR-2025-375) Title: Haplotype resolved genome of a citronella provides insights into the evolution of citronelloid biogenesis pathway

description: Supplementary information for the submitted manuscript to Horticulture ResearchFigure S1. Phylogenetic trees of the TPS involved in the terpenoids biosynthetic pathway.Figure S2. Phylogenetic trees of the ADH/GeDH/CAD involved in the terpenoids biosynthetic pathway.Figure S3. Phylogenetic trees of the GER/CIR involved in the terpenoids biosynthetic pathway.Figure S4. Phylogenetic trees of the OPR involved in the terpenoids biosynthetic pathway.Figure S5. Phylogenetic trees of the PAR/CAR involved in the terpenoids biosynthetic pathway.Figure S6. Relative expression levels of candidate genes in root, shoot and leaves of <i>C. winterianus</i> by RT-qPCR.Table S1. The relative contents of metabolites in terpenoids biosynthesis by HS-SPME/GC-MS in C. winterianus.Table S2. Reported genes involved in the citronellal synthesis pathways of other species. Table S3. Expression analysis of citronelloid biogenesis genes in Cymbopogon. Table S4. Co-expression analysis result between citronellol synthesis pathway genes and geraniol contents. Table S5. The list of each cluster genes.Table S6. List of cluster-enriched genes with an adjusted pct.1 &gt; 0.3 in target cluster and pct.2 &lt; 0.1 in other 11 clusters.Table S7. Expression of candidate genes involved in the citronellol biosynthesis pathway of C. winterianus.Table S8. Primers for real-time PCR.Materials and methods
DOI: 10.25574/29622
title: Chandra X-ray Observatory ObsId 29622

description: AO-26 Calibration Observations of A1795
DOI: 10.5281/zenodo.11667072
title: Asian elephants are associated with a more robust mammalian community in tropical forests
DOI: 10.5281/zenodo.14994541
title: Asian elephants are associated with a more robust mammalian community in tropical forests
DOI: 10.15468/dl.u3d8c2
title: Occurrence Download

description: A dataset containing 740 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Lullula arborea (Linnaeus, 1758)",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 740 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081112-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.