cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0890616.10fu
title: SH0890616.10FU

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/sh0890617.10fu
title: SH0890617.10FU

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/sh0890618.10fu
title: SH0890618.10FU

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/sh0890619.10fu
title: SH0890619.10FU

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: 10.5281/zenodo.13374667
title: Underlying data for "A deep mutational scanning platform to characterize the fitness landscape  of anti-CRISPR proteins"

description: Underlying data for the manuscript "A deep mutational scanning platform to characterize the fitness landscape  of anti-CRISPR proteins".

Contains FACS and NGS read data for the deep mutational scanning experiments carried out on the anti-CRISPR proteins AcrIIA4 and AcrIIA5.

The included tar.gz archive has the following directory structure:



fractions_a4/rep_1, rep_2 and rep_3: contains .fastq.gz files for 3 biological replicates of the 4 fractions sequenced for deep mutational scanning analysis of AcrIIA4

fractions_a5/rep_1, rep_2 and rep_3: contains .fastq.gz files for 3 biological replicates of the 4 fractions sequenced for deep mutational scanning analysis of AcrIIA5

library_a4/: contains .fastq.gz files for 2 replicates of the initial AcrIIA4 library

library_a5/: contains .fastq.gz files for 2 replicates of the inital AcrIIA5 library

count_matrices/: contains CSV-format count matrices with the number of reads per single-amino-acid variant for both sequenced fractions and the initial library

facs/ : contains .fcs files for the set of measured benchmark single mutants of AcrIIA4 and AcrIIA5, which were used for model training.
description: Funding: D.N. is grateful for funding by the German Research Foundation (DFG, Projektnummer 453202693) and the Aventis foundation. T.S. and D.H. were partially funded via scholarships from the German Academic Scholarship Foundation. B.E.C. is a grantee from the European Research Council (Starting grant - 716058), the Swiss National Science Foundation and the Biltema Foundation. S.R. is supported by a grant of the National Center of Competence in Research in Chemical Biology. Funding for open access publication is provided by the German Research Foundation (DFG, Projektnummer 453202693).

Competing interests: D.N. is inventor on several patent applications related to the use and engineering of anti-CRISPR proteins.
DOI: 10.5281/zenodo.5221559
title: Underlying data for "A deep mutational scanning platform to characterize the fitness landscape  of anti-CRISPR proteins"

description: Underlying data for the manuscript "A deep mutational scanning platform to characterize the fitness landscape  of anti-CRISPR proteins".

Contains FACS and NGS read data for the deep mutational scanning experiments carried out on the anti-CRISPR proteins AcrIIA4 and AcrIIA5.

The included tar.gz archive has the following directory structure:



fractions_a4/rep_1, rep_2 and rep_3: contains .fastq.gz files for 3 biological replicates of the 4 fractions sequenced for deep mutational scanning analysis of AcrIIA4

fractions_a5/rep_1, rep_2 and rep_3: contains .fastq.gz files for 3 biological replicates of the 4 fractions sequenced for deep mutational scanning analysis of AcrIIA5

library_a4/: contains .fastq.gz files for 2 replicates of the initial AcrIIA4 library

library_a5/: contains .fastq.gz files for 2 replicates of the inital AcrIIA5 library

count_matrices/: contains CSV-format count matrices with the number of reads per single-amino-acid variant for both sequenced fractions and the initial library

facs/ : contains .fcs files for the set of measured benchmark single mutants of AcrIIA4 and AcrIIA5, which were used for model training.
description: Funding: D.N. is grateful for funding by the German Research Foundation (DFG, Projektnummer 453202693) and the Aventis foundation. T.S. and D.H. were partially funded via scholarships from the German Academic Scholarship Foundation. B.E.C. is a grantee from the European Research Council (Starting grant - 716058), the Swiss National Science Foundation and the Biltema Foundation. S.R. is supported by a grant of the National Center of Competence in Research in Chemical Biology. Funding for open access publication is provided by the German Research Foundation (DFG, Projektnummer 453202693).

Competing interests: D.N. is inventor on several patent applications related to the use and engineering of anti-CRISPR proteins.
DOI: 10.5281/zenodo.5221560
title: Underlying data for "A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins"

description: Underlying data for the manuscript "A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins". Contains FACS and NGS read data for the deep mutational scanning experiments carried out on the anti-CRISPR proteins AcrIIA4 and AcrIIA5. The included tar.gz archive has the following directory structure: data/ ngs-a4/ : contains .fasta.gz files for the 8 fractions sequenced for deep mutational scanning analysis for AcrIIA4. ngs-a5/ : contains .fasta.gz files for the 8 fractions sequenced for deep mutational scanning analysis for AcrIIA5. FACS/ : contains .fcs files for the set of measured benchmark single mutants of AcrIIA4 and AcrIIA5, which were used for model trainng.
description: Funding: D.N. is grateful for funding by the German Research Foundation (DFG, Projektnummer 453202693) and the Aventis foundation. T.S. and D.H. were partially funded via scholarships from the German Academic Scholarship Foundation. B.E.C. is a grantee from the European Research Council (Starting grant - 716058), the Swiss National Science Foundation and the Biltema Foundation. S.R. is supported by a grant of the National Center of Competence in Research in Chemical Biology. Funding for open access publication is provided by the German Research Foundation (DFG, Projektnummer 453202693). Competing interests: D.N. is inventor on several patent applications related to the use and engineering of anti-CRISPR proteins.
DOI: 10.15156/bio/sh0890620.10fu
title: SH0890620.10FU

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/sh0890621.10fu
title: SH0890621.10FU

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/sh0890622.10fu
title: SH0890622.10FU

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/sh0890623.10fu
title: SH0890623.10FU

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/sh0890624.10fu
title: SH0890624.10FU

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.67wbph
title: Occurrence Download

description: A dataset containing 2089 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Dictyna uncinata Thorell, 1856",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 2089 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0096562-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.7785393
title: Intergenic RNAPII Atlas : input data

description: This Zenodo record refers to the <strong>"input data" </strong>used in the manuscript titled "Characterising intergenic transcription at RNA polymerase II binding sites in normal and cancer tissues" by de Langen <em>et al.</em> This Zenodo record allows to replicate the results presented in the manuscript, please refer to the instructions available on Github at https://github.com/benoitballester/Pol2Atlas. The results presented in the manuscript can be accessed at https://zenodo.org/record/8091826. <strong>In short :</strong> <strong>Data "in" :</strong> this record <strong>Data "out"</strong> : https://zenodo.org/record/8091826 <strong>Github Code</strong> : https://github.com/benoitballester/Pol2Atlas <pre><code class="language-bash"># uncompress the gz files $ cat repro_data.gz.part* | gunzip -c &gt; repro_data.gz</code></pre>
description: {"references": ["de Langen, Pierre; et al. (2023) https://doi.org/10.1101/2023.03.24.534112"]}
DOI: 10.5281/zenodo.7785392
title: Intergenic RNAPII Atlas : input data

description: This Zenodo record refers to the <strong>"input data" </strong>used in the manuscript titled "Characterising intergenic transcription at RNA polymerase II binding sites in normal and cancer tissues" by de Langen <em>et al.</em> This Zenodo record allows to replicate the results presented in the manuscript, please refer to the instructions available on Github at https://github.com/benoitballester/Pol2Atlas. The results presented in the manuscript can be accessed at https://zenodo.org/record/8091826. <strong>In short :</strong> <strong>Data "in" :</strong> this record <strong>Data "out"</strong> : https://zenodo.org/record/8091826 <strong>Github Code</strong> : https://github.com/benoitballester/Pol2Atlas <pre><code class="language-bash"># uncompress the gz files $ cat repro_data.gz.part* | gunzip -c &gt; repro_data.gz</code></pre>
description: {"references": ["de Langen, Pierre; et al. (2023) https://doi.org/10.1101/2023.03.24.534112"]}
DOI: 10.5281/zenodo.8366283
title: Wykaz 2. Wykaz stanowisk Anthocoris butleri wykorzystanych podczas modelowania niszy ekologicznej

description: Zielińska, Anna. Ocena warunków siedliskowych dla inwazyjnych gatunków pluskwiaków różnoskrzydłych (Hemiptera: Heteroptera) na terenie Europy, ze szczególnym uwzględnieniem Polski (praca doktorska). Wykaz 2. Wykaz stanowisk Anthocoris butleri wykorzystanych podczas modelowania niszy ekologicznej (dane na dzień: 08.06.2022).
DOI: 10.5281/zenodo.8366282
title: Wykaz 2. Wykaz stanowisk Anthocoris butleri wykorzystanych podczas modelowania niszy ekologicznej

description: Zielińska, Anna. Ocena warunków siedliskowych dla inwazyjnych gatunków pluskwiaków różnoskrzydłych (Hemiptera: Heteroptera) na terenie Europy, ze szczególnym uwzględnieniem Polski (praca doktorska). Wykaz 2. Wykaz stanowisk Anthocoris butleri wykorzystanych podczas modelowania niszy ekologicznej (dane na dzień: 08.06.2022).
DOI: 10.5281/zenodo.7079326
title: Maternal and infant NR3C1 and SLC6A4 epigenetic signatures of the COVID-19 pandemic lockdown: When timing matters

description: This database includes the raw data linked with the paper “Maternal and infant NR3C1 and SLC6A4 epigenetic signatures of the COVID-19 pandemic lockdown: When timing matters” published on Translational Psychiatry, doi: 10.1038/s41398-022-02160-0. This publication is part of the longitudinal and multi-centric “Measuring the outcomes of maternal COVID-19-related prenatal exposure (MOM-COPE)” research project. In this paper, we report data on NR3C1 and SLC6A4 methylation status in Italian mothers and infants who were exposed to the COVID-19 pandemic lockdown during different trimesters of pregnancy. <strong>Procedures: </strong>283 mother-infant dyads were enrolled at delivery. Within 24 hours from delivery, buccal cells were collected to assess NR3C1 (44 CpG sites) and SLC6A4 (13 CpG sites) methylation status. Mothers self-reported on depressive symptoms and anxiety by replying to an online adapted version of the well-validated Beck Depression Inventory and State-Trait Anxiety questionnaires, respectively. <strong>Analytical plan: </strong>Principal component (PC) analyses were used to reduce methylation data dimension to one PC per maternal and infant gene methylation. Mother-infant dyads were split into three groups based on the pregnancy trimester during which they were exposed to the COVID-19 lockdown. To assess the presence of significant differences in maternal and infant methylation of SLC6A4 and NR3C1 genes by pregnancy trimester of exposure to the COVID-19 pandemic lockdown, four separate one-way ANOVAs were carried out with Trimester (levels: third, second, first) as the between-subject variable and each of the methylation PCs. <strong>Findings in brief: </strong>Mothers and infants who were exposed to the lockdown during the first trimester of pregnancy had lower NR3C1 and SLC6A4 methylation when compared to counterparts exposed during the second or third trimesters. The effect remained significant after controlling for confounders.
DOI: 10.5281/zenodo.7079325
title: Maternal and infant NR3C1 and SLC6A4 epigenetic signatures of the COVID-19 pandemic lockdown: When timing matters

description: This database includes the raw data linked with the paper “Maternal and infant NR3C1 and SLC6A4 epigenetic signatures of the COVID-19 pandemic lockdown: When timing matters” published on Translational Psychiatry, doi: 10.1038/s41398-022-02160-0. This publication is part of the longitudinal and multi-centric “Measuring the outcomes of maternal COVID-19-related prenatal exposure (MOM-COPE)” research project. In this paper, we report data on NR3C1 and SLC6A4 methylation status in Italian mothers and infants who were exposed to the COVID-19 pandemic lockdown during different trimesters of pregnancy. <strong>Procedures: </strong>283 mother-infant dyads were enrolled at delivery. Within 24 hours from delivery, buccal cells were collected to assess NR3C1 (44 CpG sites) and SLC6A4 (13 CpG sites) methylation status. Mothers self-reported on depressive symptoms and anxiety by replying to an online adapted version of the well-validated Beck Depression Inventory and State-Trait Anxiety questionnaires, respectively. <strong>Analytical plan: </strong>Principal component (PC) analyses were used to reduce methylation data dimension to one PC per maternal and infant gene methylation. Mother-infant dyads were split into three groups based on the pregnancy trimester during which they were exposed to the COVID-19 lockdown. To assess the presence of significant differences in maternal and infant methylation of SLC6A4 and NR3C1 genes by pregnancy trimester of exposure to the COVID-19 pandemic lockdown, four separate one-way ANOVAs were carried out with Trimester (levels: third, second, first) as the between-subject variable and each of the methylation PCs. <strong>Findings in brief: </strong>Mothers and infants who were exposed to the lockdown during the first trimester of pregnancy had lower NR3C1 and SLC6A4 methylation when compared to counterparts exposed during the second or third trimesters. The effect remained significant after controlling for confounders.