cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6325891
title: Datasets for the Carpentry-style RNA-seq lesson

description: <strong>Lesson files</strong> For all compressed files, go to the Shell and uncompress using `tar -xzvf myarchive.tar.gz`. <strong>1) Bioinformatic files: </strong>bioinformatic_tutorial_files.tar.gz This archive contains the following datasets: FASTQ files from Arabidopsis leaf RNA-seq: Arabidopsis_sample3.fq.gz Arabidopsis_sample1.fq.gz Arabidopsis_sample4.fq.gz Arabidopsis_sample2.fq.gz Arabidopsis thaliana genome assembly and genome annotation: AtChromosome1.fa.gz ath_annotation.gff3.gz The sequence of sequencing adapters in adapters.fasta. <strong>2) Gene counts usable with DESeq2 and R: </strong>tutorial.tar.gz This archive contains the following datasets: <strong>raw_counts.csv</strong>: a dataframe of the sample raw counts. It is a comma-separate values file therefore data are separated by commas ','. <strong>samples_to_conditions.csv</strong>: a dataframe that indicates the correspondence between samples and experimental conditions (e.g. control, treated). <strong>differential_genes.csv: </strong>a dataframe that contains the result of the DESeq2 analysis specifying this contrast in `DESEq2::results()` function: `<code class="language-plaintext">contrast = c("infected", "Pseudomonas_syringae_DC3000", "mock")</code> The<strong> raw_counts.csv </strong>file was obtained by running the `v0.1.1` version of a RNA-Seq bioinformatic pipeline on the mRNA-Seq sequencing files from Vogel et al. (2016): https://www.ebi.ac.uk/ena/data/view/PRJEB13938. Please read the original study (Vogel et al. 2016): https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.14036 ==== <strong>Exercise files</strong> <strong>1) NASA spaceflight</strong> The NASA GeneLab experiment GLDS-38 performed transcriptomics and proteomics of Arabidopsis seedlings in microgravity by sending seedlings to the International Space Station (ISS). The raw counts, scaled counts and sample to conditions files are available in the ZIP archive <strong>2) Deforges 2019 hormone-treatments: </strong>deforges_2019.tar.gz This archive contains: arabidopsis_root_hormones_raw_counts.csv arabidopsis_shoot_hormones_raw_counts.csv arabidopsis_root_hormones_sample2condition.csv arabidopsis_shoot_hormones_sample2condition.csv dataset01_IAA_arabidopsis_root_raw_counts.csv dataset02_ABA_arabidopsis_root_raw_counts.csv dataset03_ACC_arabidopsis_root_raw_counts.csv dataset04_MeJA_arabidopsis_root_raw_counts.csv The <em>arabidopsis_root_hormones_raw_counts.csv</em> file contains all gene counts from all hormones. Separate datasets were made for each hormone for convenience.
DOI: 10.5281/zenodo.3804519
title: Datasets for the Carpentry-style RNA-seq lesson

description: <strong>Lesson files</strong> For all compressed files, go to the Shell and uncompress using `tar -xzvf myarchive.tar.gz`. <strong>1) Bioinformatic files: </strong>bioinformatic_tutorial_files.tar.gz This archive contains the following datasets: FASTQ files from Arabidopsis leaf RNA-seq: Arabidopsis_sample3.fq.gz Arabidopsis_sample1.fq.gz Arabidopsis_sample4.fq.gz Arabidopsis_sample2.fq.gz Arabidopsis thaliana genome assembly and genome annotation: AtChromosome1.fa.gz ath_annotation.gff3.gz The sequence of sequencing adapters in adapters.fasta. <strong>2) Gene counts usable with DESeq2 and R: </strong>tutorial.tar.gz This archive contains the following datasets: <strong>raw_counts.csv</strong>: a dataframe of the sample raw counts. It is a comma-separate values file therefore data are separated by commas ','. <strong>samples_to_conditions.csv</strong>: a dataframe that indicates the correspondence between samples and experimental conditions (e.g. control, treated). <strong>differential_genes.csv: </strong>a dataframe that contains the result of the DESeq2 analysis specifying this contrast in `DESEq2::results()` function: `<code class="language-plaintext">contrast = c("infected", "Pseudomonas_syringae_DC3000", "mock")</code> The<strong> raw_counts.csv </strong>file was obtained by running the `v0.1.1` version of a RNA-Seq bioinformatic pipeline on the mRNA-Seq sequencing files from Vogel et al. (2016): https://www.ebi.ac.uk/ena/data/view/PRJEB13938. Please read the original study (Vogel et al. 2016): https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.14036 ==== <strong>Exercise files</strong> <strong>1) NASA spaceflight</strong> The NASA GeneLab experiment GLDS-38 performed transcriptomics and proteomics of Arabidopsis seedlings in microgravity by sending seedlings to the International Space Station (ISS). The raw counts, scaled counts and sample to conditions files are available in the ZIP archive <strong>2) Deforges 2019 hormone-treatments: </strong>deforges_2019.tar.gz This archive contains: arabidopsis_root_hormones_raw_counts.csv arabidopsis_shoot_hormones_raw_counts.csv arabidopsis_root_hormones_sample2condition.csv arabidopsis_shoot_hormones_sample2condition.csv dataset01_IAA_arabidopsis_root_raw_counts.csv dataset02_ABA_arabidopsis_root_raw_counts.csv dataset03_ACC_arabidopsis_root_raw_counts.csv dataset04_MeJA_arabidopsis_root_raw_counts.csv The <em>arabidopsis_root_hormones_raw_counts.csv</em> file contains all gene counts from all hormones. Separate datasets were made for each hormone for convenience.
DOI: 10.25747/grge-rr56
title: An urban synthetic electricity distribution network from Spain, first version – ATTEST project
DOI: 10.25625/izszbl/sn7zdq
title: 2022-3-IZSZBL_Lustrino_data.xlsx

description: :unav
DOI: 10.5281/zenodo.6325902
title: Atmospheric visibility inferred from continuous-wave Doppler wind lidar, data set

description: Visibility data from Pershore, UK, between 2018 and 2020
DOI: 10.5281/zenodo.6325901
title: Atmospheric visibility inferred from continuous-wave Doppler wind lidar, data set

description: Visibility data from Pershore, UK, between 2018 and 2020
DOI: 10.25747/4j3a-0b53
title: An urban synthetic electricity distribution network from Spain, second version- ATTEST project
DOI: 10.7935/38s2-7g84
title: GEO KAGRA strain data from observing run O3b (April 7th 2020 - April 21st 2020)
DOI: 10.6073/pasta/6708b04137da4487d0f832976fe0afa0
title: Year 2015, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth in the upper Parker River Estuary near Middle Road Bridge, Newbury, MA.

description: Year 2015, water quality sonde data.15 minute readings of water column temperature, salinity, oxygen and depth in the upper Parker River Estuary near Middle Rd Bridge, Newbury, MA
DOI: 10.5281/zenodo.6322976
title: Glacier thickness maps for Ecuador and Colombia

description: Upload associated with Scientific Data submission: Glacier thickness and ice volume of the inner tropical Andes. The dataset includes: -Ice velocity maps for all 11 glacier regions (5 in Ecuador and 6 in Colombia) -Ice thickness maps for all 11 glacier regions generated using the 6 different thickness calculation methods -Multi-model ensemble mean glacier thickness maps for all 11 glacier regions -Basin-divided ice volumes for each glacier region, with a 1 km, 5 km, and 20 km buffer -Results of a full parameter sensitivity test for the thickness calculation All data are saved in 32-bit floating-point geotiff format. The data are freely available under the Creative Commons Attribution Licence, CC BY 4.0. The feature-tracking code used to derive ice velocities, GIV, is available on github and Zenodo (https://doi.org/10.5281/zenodo.4904544). All other code, including Google Earth Engine download scripts and the ice-thickness inversion code is available on zenodo (https://doi.org/10.5281/zenodo.6323069).
DOI: 10.5517/ccdc.csd.cc29j6xz
title: CCDC 2130751: Experimental Crystal Structure Determination

description: Related Article: Rou Wang, Yaqian Wu, Jinglan Wang, Huade Huang, Yibo Wang, Shengxian Xu, Feng Zhao|2022|J.Mol.Struct.|1257|132642|doi:10.1016/j.molstruc.2022.132642
DOI: 10.6084/m9.figshare.19300100
title: Landscape Change.zip

description: This data is about land cover classfication of Greater Accra Region from 1986 to 2017.
DOI: 10.6084/m9.figshare.19300100.v1
title: Landscape Change.zip

description: This data is about land cover classfication of Greater Accra Region from 1986 to 2017.
DOI: 10.25405/data.ncl.17136182
title: Stimulus dependence of directed information exchange between cortical layers in macaque V1

description: Dataset of the findings reported in https://doi.org/10.1101/2020.07.10.197566<br><br>Dataset are postprocessed binary files in the "Cortex" and "Neuralynx" data formats. Each zipfile contains the data of different paradigms tested in individual recording session.
DOI: 10.25405/data.ncl.17136182.v1
title: Stimulus dependence of directed information exchange between cortical layers in macaque V1

description: Dataset of the findings reported in https://doi.org/10.1101/2020.07.10.197566<br><br>Dataset are postprocessed binary files in the "Cortex" and "Neuralynx" data formats. Each zipfile contains the data of different paradigms tested in individual recording session.
DOI: 10.25810/v575-3r57.39
title: Japanese Newspaper Coverage of Climate Change or Global Warming, 2000-2022 - January 2022

description: The Media and Climate Change Observatory Data monitors 126 sources (across newspapers, radio and TV) in 58 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.48324/dandi.000221/0.220303.1653
title: A midbrain-thalamus-cortex circuit reorganizes cortical dynamics to initiate movement

description: Data from "A midbrain-thalamus-cortex circuit reorganizes cortical dynamics to initiate movement" Inagaki & Chen et al
Example codes to plot data is at https://github.com/hidehikoinagaki/InagakiAndChenEtAl2022
DOI: 10.6084/m9.figshare.19300142.v1
title: Biernacki-et-al.Real-world-data-on-the-efficacy-and-long-term-use-of-fingolimod-in-Hungary.xlsx

description: <b>Background:</b> Fingolimod was approved and reimbursed by the healthcare provider in Hungary for the treatment of highly active relapsing-remitting multiple sclerosis (RRMS) in 2012. The present study aimed to assess the effectiveness, safety profile, and persistence to fingolimod in a real-life setting in Hungary in RRMS patients who were either therapy naïve before enrollment or have changed to fingolimod from another disease-modifying therapy (DMT) for any reason. <b>Methods:</b> This cross-sectional, observational study with prospective data collection was performed nationwide at 21 sites across Hungary. To avoid selection bias, sites were asked to document eligible patients in consecutive chronological order. Demographic, clinical, safety and efficacy data were analysed for up to 5 years from 570 consenting adult patients with RRMS who had received treatment with fingolimod for at least one year. <b>Results:</b> 69.6% of patients remained free from relapses for the whole study duration; in the first year, 85.1% of patients did not experience a relapse, which rose to 94.6% seen in the 5th year. Compared to baseline at study end, 62.7% of the patients had stable, 28.2% had higher, and 9.1% had lower EDSS scores. Overall, the annualized relapse rate decreased from 0.804 observed at baseline to 0.185, 0.149, 0.122, 0.091, and 0.097 (77.0%, 82.1%, 85.2%, 89.7%, and 89.0% relative reduction, respectively) after 1, 2, 3, 4, and 5 years of treatment. The greatest reduction rate was seen in the group of therapy naïve patients. Treatment persistence on fingolimod after 60 months was 73.4%. <b>Conclusion:</b> In this nationwide Hungarian cohort, most patients under fingolimod treatment were free from relapses and disability progression. In addition, fingolimod has proven to be a well-tolerated DMT that has sustained its manageable safety profile, high efficacy, and positive benefit/risk ratio for up to 5 years in a real-life setting.
DOI: 10.6084/m9.figshare.19300142
title: Biernacki-et-al.Real-world-data-on-the-efficacy-and-long-term-use-of-fingolimod-in-Hungary.xlsx

description: <b>Background:</b> Fingolimod was approved and reimbursed by the healthcare provider in Hungary for the treatment of highly active relapsing-remitting multiple sclerosis (RRMS) in 2012. The present study aimed to assess the effectiveness, safety profile, and persistence to fingolimod in a real-life setting in Hungary in RRMS patients who were either therapy naïve before enrollment or have changed to fingolimod from another disease-modifying therapy (DMT) for any reason. <b>Methods:</b> This cross-sectional, observational study with prospective data collection was performed nationwide at 21 sites across Hungary. To avoid selection bias, sites were asked to document eligible patients in consecutive chronological order. Demographic, clinical, safety and efficacy data were analysed for up to 5 years from 570 consenting adult patients with RRMS who had received treatment with fingolimod for at least one year. <b>Results:</b> 69.6% of patients remained free from relapses for the whole study duration; in the first year, 85.1% of patients did not experience a relapse, which rose to 94.6% seen in the 5th year. Compared to baseline at study end, 62.7% of the patients had stable, 28.2% had higher, and 9.1% had lower EDSS scores. Overall, the annualized relapse rate decreased from 0.804 observed at baseline to 0.185, 0.149, 0.122, 0.091, and 0.097 (77.0%, 82.1%, 85.2%, 89.7%, and 89.0% relative reduction, respectively) after 1, 2, 3, 4, and 5 years of treatment. The greatest reduction rate was seen in the group of therapy naïve patients. Treatment persistence on fingolimod after 60 months was 73.4%. <b>Conclusion:</b> In this nationwide Hungarian cohort, most patients under fingolimod treatment were free from relapses and disability progression. In addition, fingolimod has proven to be a well-tolerated DMT that has sustained its manageable safety profile, high efficacy, and positive benefit/risk ratio for up to 5 years in a real-life setting.
DOI: 10.25747/8ykt-3a79
title: An urban synthetic electricity distribution network from Spain, third version - ATTEST project
DOI: 10.15156/bio/sh665898.07fu
title: SH665898.07FU

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/sh665899.07fu
title: SH665899.07FU

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/sh1185058.08fu
title: SH1185058.08FU

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/sh1185059.08fu
title: SH1185059.08FU

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/sh1185060.08fu
title: SH1185060.08FU

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/sh665900.07fu
title: SH665900.07FU

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/sh665901.07fu
title: SH665901.07FU

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/sh1185061.08fu
title: SH1185061.08FU

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.