cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4393107
title: Data from: Highly efficient and comprehensive identification of ethyl methanesulfonate-induced mutations in Nicotiana tabacum L. by whole-genome and whole-exome sequencing

description: Tobacco (<em>Nicotiana tabacum </em>L.) is a complex allotetraploid species with a large 4.5-Gb genome that carries duplicated gene copies. In this study, we describe the development of a whole-exome sequencing (WES) procedure in tobacco and its application to characterize a test population of ethyl methanesulfonate (EMS)-induced mutations. A probe set covering 50.3-Mb protein coding regions was designed from a reference tobacco genome. The EMS-induced mutations in 19 individual M<sub>2</sub> lines were analyzed using our mutation analysis pipeline optimized to minimize false positives/negatives. In the target regions, the on-target rate of WES was approximately 75%, and 61,146 mutations were detected in the 19 M<sub>2</sub> lines. Most of the mutations (98.8%) were single nucleotide variants, and 95.6% of them were C/G to T/A transitions. The number of mutations detected in the target coding sequences by WES was 93.5% of the mutations detected by whole-genome sequencing (WGS). The amount of sequencing data necessary for efficient mutation detection was significantly lower in WES (11.2 Gb), which is only 6.2% of the required amount in WGS (180 Gb). Thus, WES was almost comparable to WGS in performance but is more cost effective. Therefore, the developed target exome sequencing, which could become a fundamental tool in high-throughput mutation identification, renders the genome-wide analysis of tobacco highly efficient.
DOI: 10.5519/qd.m8fcehxz
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.14703792
title: Cell atlas of the murine perinatal lung

description: Gene expression counts (raw number of reads) and cell and gene metadata for single cell transcriptomics (plate-based, SmartSeq2) on perinatal murine lungs.<br>This dataset focuses on immune, endothelial, and mesenchymal cells, but contains a few epithelial cells as well.<br>There are four time points:- E18.5: roughly one day before birth- P1: roughly 24 hours since birth- P7: 7 days since birth- P21: 21 days since birth<br>The P7 timepoints has two conditions:- normal- hyperoxia: these mice were exposed to 80% oxygen for the whole week before being euthanized.<br>Please cite the following papers if you use these data:<br>Domingo-Gonzales*, Zanini* et al. eLife (2020): https://elifesciences.org/articles/56890Zanini et al. bioRxiv (2021a): https://www.biorxiv.org/content/10.1101/2021.04.27.441649v1Zanini et al bioRxiv (2021b): https://www.biorxiv.org/content/10.1101/2021.05.19.444776v1.full<br>
DOI: 10.6084/m9.figshare.14703792.v1
title: Cell atlas of the murine perinatal lung

description: Gene expression counts (raw number of reads) and cell and gene metadata for single cell transcriptomics (plate-based, SmartSeq2) on perinatal murine lungs.<br>This dataset focuses on immune, endothelial, and mesenchymal cells, but contains a few epithelial cells as well.<br>There are four time points:- E18.5: roughly one day before birth- P1: roughly 24 hours since birth- P7: 7 days since birth- P21: 21 days since birth<br>The P7 timepoints has two conditions:- normal- hyperoxia: these mice were exposed to 80% oxygen for the whole week before being euthanized.<br>Please cite the following papers if you use these data:<br>Domingo-Gonzales*, Zanini* et al. eLife (2020): https://elifesciences.org/articles/56890Zanini et al. bioRxiv (2021a): https://www.biorxiv.org/content/10.1101/2021.04.27.441649v1Zanini et al bioRxiv (2021b): https://www.biorxiv.org/content/10.1101/2021.05.19.444776v1.full<br>
DOI: 10.5281/zenodo.4876670
title: Boutiques-execution-a6aea2

description: Boutiques execution data-set
DOI: 10.5281/zenodo.4876669
title: Boutiques-execution-a6aea2

description: Boutiques execution data-set
DOI: 10.5281/zenodo.4876676
title: Boutiques-execution-94b8e4

description: Boutiques execution data-set
DOI: 10.5281/zenodo.4876675
title: Boutiques-execution-94b8e4

description: Boutiques execution data-set
DOI: 10.18112/openneuro.ds003665.v1.0.0
title: A test-retest resting and cognitive state EEG dataset
DOI: 10.6084/m9.figshare.13076267
title: Metabolic rate and life history trait datasets (incl. phylogeny)

description: Datasets containing estimates of resting metabolic rate (RMR), the body masses and temperatures associated with the RMR measurements, and various life history traits. RMR data was selected for inclusion into the dataset using three criteria; (1) selecting RMR data based upon the largest sample size, (2) selecting RMR data based upon the largest average measurement body mass, and (3) selecting RMR data based upon the measurement temperature closest to 20˚C, resulting in the 'sample size' dataset, the 'mass' dataset, and the 'temperature' dataset, respectively. <br>We also calculated a weight-based measure of growth performance (phi) using both species-specific and group-specific length-weight regressions (the phi 44 dataset) or species-specific but not group-specific length-weight regressions (the phi 84 dataset.<br>"SpeciesWithoutProxies.csv" is a list of species for which life history trait data from 'proxy' species was not used. <br>"TeleostElasmoPhylogeny.tre" is a supertree of teleosts and elasmobranchs constructed from phylogenies from Rabosky et al. 2018 (Nature) and Stein et al. 2018 (Nature Ecology & Evolution).
DOI: 10.5281/zenodo.4817420
title: Posterior data release for the paper "Constraining scalar-tensor gravitational theories by GW190426_152155"

description: This data release corresponds to the paper "Constraining scalar-tensor gravitational theories by GW190426_152155" (arXiv:2105.13644). In this paper, we consider three specific models of scalar-tensor theories, including the Brans-Dicke theory (BD), the theory with scalarization phenomena proposed by Damour and Esposito-Far\`{e}se (DEF), and Screened Modified Gravity (SMG). We use the public GW data of a possible neutron star-black hole binary event, GW190426_152155, to place the constraints. Four equations of state (EoSs), <em>sly</em>, <em>alf2</em>, <em>H4</em> and <em>mpa1</em>, are used to derive the scalar charges of neutron stars for BD and DEF. The constraints are obtained by performing the full Bayesian inference with the help of the open source software Bilby. This dataset contains all posterior samples of the runs discussed in the paper. The models and EoSs can be read form the filenames for the runs of BD and DEF. The files of "<em>*_half_dipole.json</em>" correspond to the runs for constraining the dipole radiation without considering specific model parameters. All files are JSON format which is the default output format of Bilby. They are human readable and also can be processed or visualized by Bilby or PESummary conveniently.
description: This work is supported by NSFC No.11773028, 11633001, 11653002, 11603020, 11903030, 12003029, 11903033, the Fundamental Research Funds for the Central Universities under Grant No.WK2030000036, WK3440000004 and WK2030000044, the Strategic Priority Research Program of the Chinese Academy of Sciences Grant No. XDB23010200, Key Research Program of the Chinese Academy of Sciences, Grant No. XDPB15, and the China Manned Space Program through its Space Application System, and the China Postdoctoral Science Foundation grant No.2019M662168. This research has made use of data, software and/or web tools obtained from the Gravitational Wave Open Science Center (https://www.gw-openscience.org/ ), a service of LIGO Laboratory, the LIGO Scientific Collaboration and the Virgo Collaboration. LIGO Laboratory and Advanced LIGO are funded by the United States National Science Foundation (NSF) as well as the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max-Planck-Society (MPS), and the State of Niedersachsen/Germany for support of the construction of Advanced LIGO and construction and operation of the GEO600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. Virgo is funded, through the European Gravitational Observatory (EGO), by the French Centre National de Recherche Scientifique (CNRS), the Italian Istituto Nazionale di Fisica Nucleare (INFN) and the Dutch Nikhef, with contributions by institutions from Belgium, Germany, Greece, Hungary, Ireland, Japan, Monaco, Poland, Portugal, Spain.
DOI: 10.6084/m9.figshare.14452401
title: raw_data_Scheuffele_et_al.xlsx

description: This data set compiles data on body mass, gill surface area and standard metabolic rate of fishes from literature resources. The data selected spanned at least one order of magnitude. <br>
DOI: 10.6084/m9.figshare.14452401.v1
title: raw_data_Scheuffele_et_al.xlsx

description: This data set compiles data on body mass, gill surface area and standard metabolic rate of fishes from literature resources. The data selected spanned at least one order of magnitude. <br>
DOI: 10.34740/kaggle/dsv/2287636
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.4841035
title: Evaluation of a numerically efficient aerosol activation scheme by using cloud data from multiple aircraft campaigns in continental and marine regions

description: This research introduces a numerically efficient aerosol activation scheme and evaluates it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The scheme employs a Quasi-steady state approximation of the cloud Droplet Growth Equation (QDGE) to efficiently simulate aerosol activation, the vertical profile of supersaturation, and the activated cloud droplet number concentration (CDNC) near the cloud base. We evaluate the QDGE scheme by specifying observed environmental thermodynamic variables and aerosol information from 31 cloud cases as input and comparing the simulated CDNC with cloud observations. The average of mean relative error (MRE) of the simulated CDNC for cloud cases in each campaign ranges from 17.30 % in Brazil to 25.90 % in China, indicating that the QDGE scheme successfully reproduces observed variations in CDNC over a wide range of different meteorological conditions and aerosol regimes. Additionally, we carried out an error analysis by calculating the Maximum Information Coefficient (MIC) between the MRE and input variables for the individual campaigns and all cloud cases. MIC values are then sorted by aerosol properties, pollution level, environmental humidity, and dynamic condition according to their relative importance to MRE. Based on the error analysis we found that the magnitude of MRE is more relevant to the specification of input aerosol pollution level in marine regions and aerosol hygroscopicity in continental regions than to other variables in the simulation.
description: This code is distributed under the Open Government License - Canada version 2.0, which has no conflict with the license required by Geoscientific Model Development. This work is supported by the National Important Project of the Ministry of Science and Technology in China (grant no. 2017YFC1501404) and the National Natural Science Foundation of China (grant nos. 41775137 and 71690243).
DOI: 10.5281/zenodo.4841034
title: Evaluation of a numerically efficient aerosol activation scheme by using cloud data from multiple aircraft campaigns in continental and marine regions

description: This research introduces a numerically efficient aerosol activation scheme and evaluates it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The scheme employs a Quasi-steady state approximation of the cloud Droplet Growth Equation (QDGE) to efficiently simulate aerosol activation, the vertical profile of supersaturation, and the activated cloud droplet number concentration (CDNC) near the cloud base. We evaluate the QDGE scheme by specifying observed environmental thermodynamic variables and aerosol information from 31 cloud cases as input and comparing the simulated CDNC with cloud observations. The average of mean relative error (MRE) of the simulated CDNC for cloud cases in each campaign ranges from 17.30 % in Brazil to 25.90 % in China, indicating that the QDGE scheme successfully reproduces observed variations in CDNC over a wide range of different meteorological conditions and aerosol regimes. Additionally, we carried out an error analysis by calculating the Maximum Information Coefficient (MIC) between the MRE and input variables for the individual campaigns and all cloud cases. MIC values are then sorted by aerosol properties, pollution level, environmental humidity, and dynamic condition according to their relative importance to MRE. Based on the error analysis we found that the magnitude of MRE is more relevant to the specification of input aerosol pollution level in marine regions and aerosol hygroscopicity in continental regions than to other variables in the simulation.
description: This code is distributed under the Open Government License - Canada version 2.0, which has no conflict with the license required by Geoscientific Model Development. This work is supported by the National Important Project of the Ministry of Science and Technology in China (grant no. 2017YFC1501404) and the National Natural Science Foundation of China (grant nos. 41775137 and 71690243).
DOI: 10.6084/m9.figshare.14579697.v5
title: Figures_Tables_Supplementary materials-MDPI

description: Molecular characteristics and minimum inhibitory concentration values of C. difficile clinical isolates in Thailand
DOI: 10.34740/kaggle/dsv/2287755
title: Twitter: Trending Tweets per week (updated weekly)
DOI: 10.6084/m9.figshare.14579697.v6
title: Figures_Tables_Supplementary materials-MDPI

description: Molecular characteristics and minimum inhibitory concentration values of C. difficile clinical isolates in Thailand
DOI: 10.25919/eqmv-5h17
title: Southern HII Region Discovery Survey (SHRDS): Dataset 12

description: The Southern HII Region Discovery Survey is an Australia Telescope Compact Array 4-6 and 8-10 GHz radio continuum and radio recombination line survey of Milky Way HII regions (Wenger et al., 2021). This data archive contains all relevant intermediate data products from the final SHRDS data release (the Full Catalog). For each observed HII region and calibrator field, this archive contains (1) a 4 GHz bandwidth, full-Stokes, multi-scale, multi-frequency synthesis (MS-MFS) continuum FITS image, (2) up to sixteen 256 MHz bandwidth, full-Stokes, MS-MFS continuum FITS images covering the full 4 GHz bandwidth, (3) a Stokes I MS-MFS FITS image of each RRL transition, (4) a Stokes I multi-scale FITS data cube of each RRL transition, and (5) a FITS image containing the watershed segmentation region for each identified HII region at each observed frequency. The archive also includes the relevant residual images/cubes and primary beam images for all of these data products, as well as all of the images and cubes smoothed to a common angular resolution.
DOI: 10.6084/m9.figshare.14703953.v1
title: Additional file 8 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 8: Table S6. COG functions in SAPHO and HC samples by predicting the function of 16S rDNA gene.
DOI: 10.6084/m9.figshare.14703950.v1
title: Additional file 7 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 7: Table S5. OTUs as biomarkers of SAPHO syndrome and their taxonomy.
DOI: 10.6084/m9.figshare.14703947.v1
title: Additional file 6 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 6: Table S4. OTUs with significant difference between HC and SAPHO groups in Wilcoxon rank-sum test.
DOI: 10.6084/m9.figshare.14703944.v1
title: Additional file 5 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 5: Table S3. OTUs with significant difference between HC and SAPHO groups in MetagenomeSeq analysis.
DOI: 10.6084/m9.figshare.14703941.v1
title: Additional file 4 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 4: Table S2. Alpha indexes between HC and SAPHO groups in Wilcoxon rank-sum test.
DOI: 10.6084/m9.figshare.14703938.v1
title: Additional file 3 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 3: Table S1. Characteristics of the subjects included in this study.
DOI: 10.6084/m9.figshare.14703912.v1
title: Additional file 1 of Evaluation of the surgical and prosthetic success of All-on-4 restorations: a retrospective cohort study of provisional vs. definitive immediate restorations

description: Additional file 1:. Raw data
DOI: 10.6084/m9.figshare.14703911.v1
title: Additional file 1 of Knowledge, attitudes, practices, and the effects of COVID-19 among the youth in Kenya

description: Additional file 1.
DOI: 10.6084/m9.figshare.14703899.v1
title: Additional file 9 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 9: Table S7. OS analysis of TNBC and Breast cancer.
DOI: 10.6084/m9.figshare.14703890.v1
title: Additional file 6 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 6: Table S6. The clinical data and the result of Cox regression analysis in DFI and PFI models.
DOI: 10.6084/m9.figshare.14703887.v1
title: Additional file 5 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 5: Table S5. Related information of all genes involved in univariate Cox regression analysis.
DOI: 10.6084/m9.figshare.14703884.v1
title: Additional file 4 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 4: Table S4. Related information of all genes involved in GO and KEGG analysis.
DOI: 10.6084/m9.figshare.14703878.v1
title: Additional file 3 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 3: Table S3. ROC analysis of DEGs based on TCGA samples.
DOI: 10.6084/m9.figshare.14703875.v1
title: Additional file 2 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 2: Table S2. The DEGs in GEO and TCGA datasets.
DOI: 10.6084/m9.figshare.14703872.v1
title: Additional file 1 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 1: Table S1. Statistics of microarray datasets from GEO and TCGA.
DOI: 10.6084/m9.figshare.14703953
title: Additional file 8 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 8: Table S6. COG functions in SAPHO and HC samples by predicting the function of 16S rDNA gene.
DOI: 10.6084/m9.figshare.14703950
title: Additional file 7 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 7: Table S5. OTUs as biomarkers of SAPHO syndrome and their taxonomy.
DOI: 10.6084/m9.figshare.14703947
title: Additional file 6 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 6: Table S4. OTUs with significant difference between HC and SAPHO groups in Wilcoxon rank-sum test.
DOI: 10.6084/m9.figshare.14703944
title: Additional file 5 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 5: Table S3. OTUs with significant difference between HC and SAPHO groups in MetagenomeSeq analysis.
DOI: 10.6084/m9.figshare.14703941
title: Additional file 4 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 4: Table S2. Alpha indexes between HC and SAPHO groups in Wilcoxon rank-sum test.
DOI: 10.6084/m9.figshare.14703938
title: Additional file 3 of Abundance alteration of nondominant species in fecal-associated microbiome of patients with SAPHO syndrome

description: Additional file 3: Table S1. Characteristics of the subjects included in this study.
DOI: 10.6084/m9.figshare.14703912
title: Additional file 1 of Evaluation of the surgical and prosthetic success of All-on-4 restorations: a retrospective cohort study of provisional vs. definitive immediate restorations

description: Additional file 1:. Raw data
DOI: 10.6084/m9.figshare.14703911
title: Additional file 1 of Knowledge, attitudes, practices, and the effects of COVID-19 among the youth in Kenya

description: Additional file 1.
DOI: 10.6084/m9.figshare.14703899
title: Additional file 9 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 9: Table S7. OS analysis of TNBC and Breast cancer.
DOI: 10.6084/m9.figshare.14703890
title: Additional file 6 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 6: Table S6. The clinical data and the result of Cox regression analysis in DFI and PFI models.
DOI: 10.6084/m9.figshare.14703887
title: Additional file 5 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 5: Table S5. Related information of all genes involved in univariate Cox regression analysis.
DOI: 10.6084/m9.figshare.14703884
title: Additional file 4 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 4: Table S4. Related information of all genes involved in GO and KEGG analysis.
DOI: 10.6084/m9.figshare.14703878
title: Additional file 3 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 3: Table S3. ROC analysis of DEGs based on TCGA samples.
DOI: 10.6084/m9.figshare.14703875
title: Additional file 2 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 2: Table S2. The DEGs in GEO and TCGA datasets.
DOI: 10.6084/m9.figshare.14703872
title: Additional file 1 of Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

description: Additional file 1: Table S1. Statistics of microarray datasets from GEO and TCGA.