cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11986287.v1
title: Additional file 1 of Ultraplexing: increasing the efficiency of long-read sequencing for hybrid assembly with k-mer-based multiplexing

description: Additional file 1. Sample summary. Names, accessions and summary statistics of all utilized reference genomes.
DOI: 10.6084/m9.figshare.11986266
title: Additional file 3 of High-Resolution Confocal Fluorescence Imaging of Serine Hydrolase Activity in Cryosections – Application to Glioma Brain Unveils Activity Hotspots Originating from Tumor-Associated Neutrophils

description: Additional file 3. Complete LC-MS/MS data of all proteins identified from the ABPP gel-pieces.
DOI: 10.6084/m9.figshare.11986266.v1
title: Additional file 3 of High-Resolution Confocal Fluorescence Imaging of Serine Hydrolase Activity in Cryosections – Application to Glioma Brain Unveils Activity Hotspots Originating from Tumor-Associated Neutrophils

description: Additional file 3. Complete LC-MS/MS data of all proteins identified from the ABPP gel-pieces.
DOI: 10.6084/m9.figshare.11986260
title: Additional file 10 of Ultraplexing: increasing the efficiency of long-read sequencing for hybrid assembly with k-mer-based multiplexing

description: Additional file 10. Sequencing data summary. Summary statistics of all generated read sets (Oxford Nanopore and Illumina).
DOI: 10.6084/m9.figshare.11986260.v1
title: Additional file 10 of Ultraplexing: increasing the efficiency of long-read sequencing for hybrid assembly with k-mer-based multiplexing

description: Additional file 10. Sequencing data summary. Summary statistics of all generated read sets (Oxford Nanopore and Illumina).
DOI: 10.6084/m9.figshare.11986206
title: Additional file 9 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 9: Table S8. Selected PgWRKYs for expression analysis and their group representation with motif conservation.
DOI: 10.6084/m9.figshare.11986200
title: Additional file 8 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 8: Table S7. List of cis-regulatory elements (CREs) present in promoter region of identified PgWRKYs.
DOI: 10.6084/m9.figshare.11986200.v1
title: Additional file 8 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 8: Table S7. List of cis-regulatory elements (CREs) present in promoter region of identified PgWRKYs.
DOI: 10.6084/m9.figshare.11986206.v1
title: Additional file 9 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 9: Table S8. Selected PgWRKYs for expression analysis and their group representation with motif conservation.
DOI: 10.6084/m9.figshare.11986191
title: Additional file 6 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 6: Table S5. List of orthologous pair of P. glaucum with S. italica, O. sativa and A. thaliana.
DOI: 10.6084/m9.figshare.11986194
title: Additional file 7 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 7: Table S6. The Ks/Ka ratio of identified collinear pairs.
DOI: 10.6084/m9.figshare.11986188
title: Additional file 5 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 5: Table S4. List of tandem and segmental duplicated PgWRKYs.
DOI: 10.6084/m9.figshare.11986194.v1
title: Additional file 7 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 7: Table S6. The Ks/Ka ratio of identified collinear pairs.
DOI: 10.6084/m9.figshare.11986191.v1
title: Additional file 6 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 6: Table S5. List of orthologous pair of P. glaucum with S. italica, O. sativa and A. thaliana.
DOI: 10.6084/m9.figshare.11986182
title: Additional file 4 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 4: Table S3. Motif distribution across all the identified 97 PgWRKYs.
DOI: 10.6084/m9.figshare.11986188.v1
title: Additional file 5 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 5: Table S4. List of tandem and segmental duplicated PgWRKYs.
DOI: 10.6084/m9.figshare.11986182.v1
title: Additional file 4 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 4: Table S3. Motif distribution across all the identified 97 PgWRKYs.
DOI: 10.6084/m9.figshare.11986167
title: Additional file 2 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 2: Table S2. Different types of WRKY variants in four groups of PgWRKY family.
DOI: 10.6084/m9.figshare.11986161
title: Additional file 1 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 1: Table S1. Protein features and chromosomal details of identified 97 PgWRKYs.
DOI: 10.6084/m9.figshare.11986167.v1
title: Additional file 2 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 2: Table S2. Different types of WRKY variants in four groups of PgWRKY family.
DOI: 10.6084/m9.figshare.11986158
title: Additional file 15 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 15: Table S10. A list of accession numbers of reference WRKYs used to access the data analyzed in this study.
DOI: 10.6084/m9.figshare.11986158.v1
title: Additional file 15 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 15: Table S10. A list of accession numbers of reference WRKYs used to access the data analyzed in this study.
DOI: 10.6084/m9.figshare.11986161.v1
title: Additional file 1 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 1: Table S1. Protein features and chromosomal details of identified 97 PgWRKYs.
DOI: 10.6084/m9.figshare.11986122
title: Additional file 10 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 10: Table S9. List of primers used in qRT-PCR analysis for selected PgWRKYs.
DOI: 10.6084/m9.figshare.11986122.v1
title: Additional file 10 of Genome-wide identification and expression analysis of WRKY transcription factors in pearl millet (Pennisetum glaucum) under dehydration and salinity stress

description: Additional file 10: Table S9. List of primers used in qRT-PCR analysis for selected PgWRKYs.
DOI: 10.6084/m9.figshare.11986098
title: Additional file 1 of Specific humoral response in cancer patients treated with a VEGF-specific active immunotherapy procedure within a compassionate use program

description: Additional file 1. VEGF-specific IgG, IgM, IgA and IgE antibodies.
DOI: 10.6084/m9.figshare.11986098.v1
title: Additional file 1 of Specific humoral response in cancer patients treated with a VEGF-specific active immunotherapy procedure within a compassionate use program

description: Additional file 1. VEGF-specific IgG, IgM, IgA and IgE antibodies.
DOI: 10.6084/m9.figshare.11986086
title: Additional file 2 of The Brazilian Society of Rheumatology guidelines for axial spondyloarthritis – 2019

description: Additional file 2. Data used in the Confidence Intervals.
DOI: 10.6084/m9.figshare.11986086.v1
title: Additional file 2 of The Brazilian Society of Rheumatology guidelines for axial spondyloarthritis – 2019

description: Additional file 2. Data used in the Confidence Intervals.
DOI: 10.6084/m9.figshare.11986047
title: Additional file 3 of An epigenome-wide association study of posttraumatic stress disorder in US veterans implicates several new DNA methylation loci

description: Additional file 3. Replication of top EWAS resultsin the PFC of the Brain Bank Cohort.
DOI: 10.6084/m9.figshare.11986047.v1
title: Additional file 3 of An epigenome-wide association study of posttraumatic stress disorder in US veterans implicates several new DNA methylation loci

description: Additional file 3. Replication of top EWAS resultsin the PFC of the Brain Bank Cohort.
DOI: 10.6084/m9.figshare.11986032
title: Additional file 2 of An epigenome-wide association study of posttraumatic stress disorder in US veterans implicates several new DNA methylation loci

description: Additional file 2. Complete EWAS results for the Discovery Cohort.
DOI: 10.6084/m9.figshare.11986032.v1
title: Additional file 2 of An epigenome-wide association study of posttraumatic stress disorder in US veterans implicates several new DNA methylation loci

description: Additional file 2. Complete EWAS results for the Discovery Cohort.
DOI: 10.6084/m9.figshare.11985942
title: Figure 1-6.txt

description: iron database to make figures
DOI: 10.6084/m9.figshare.11985942.v1
title: Figure 1-6.txt

description: iron database to make figures
DOI: 10.6084/m9.figshare.11985990
title: data and programfor revised article.rar

description: data article
DOI: 10.6084/m9.figshare.11985912
title: Dataset and code used in the temporal seed dispersal multilayer network Costa et al. 2020 Journal of Ecology

description: Dataset and code supporting the results from Costa et al. (2020) Species temporal persistence promotes the stability of fruit-frugivore interactions across a five-year multilayer network, Journal of Ecology.<br>- Dataset.xlsx: File containing the data used to calculate monolayer species- and network-level descriptors, in statistical analysis, and to create Figures 2, S1, S2, and S3. More details in the file “R script.R”.<br>- R script. R: Contains all the R code used in the study<br>- Multilayer_temporal_data.csv: Used to calculate multilayer modularity<br>- DisperserAbundanceMatrix.txt: Contains the mean number of birds captured per day in each year. It is used to calculate the interlayer link strength for each bird species between sequential networks<br>- SeedsAbundanceMatrix.txt: Contains the mean number of fruits counted in the transects in each year. It is used to calculate the interlayer link strength for each plant species between sequential networks<br>- modularity_weighted_multilayer_obs.m: Matlab code to calculate the observed multilayer modularity.<br>- modularity_weighted_multilayer_null1.m: Matlab code to calculate the multilayer modularity of the null model where observed intralayer links were randomly reshuffled while keeping marginal totals fixed. - GenLouvain2.0.zip: Contains the Matlab code to run the Generalized Louvain algorithm in order to calculate multilayer modularity. The R code used to compute multilayer modularity was adapted from Pilosof et al. (2017) and all Matlab code used here is available in Pilosof (2017). Please, if you use any of these codes, cite (when applicable) the following works:<br>Jutla, I. S., Jeub, L. G. S. & Mucha, P. J. (2014) A generalized Louvain method for community detection implemented in MATLAB, http://netwiki.amath.unc.edu/GenLouvain (2011-2014).<br>Pilosof, S., Porter, M. A., Pascual, M. & Kéfi, S. (2017) The multilayer nature of ecological networks. Nature Ecology & Evolution, 1, 0101. https://doi.org/10.1038/s41559-017-0101<br>Pilosof, Shai (2017): Matlab code for calculating of modularity in bipartite networks. Original publication: Pilosof et al. (2017), Nature Ecology & Evolution. figshare. Dataset. https://doi.org/10.6084/m9.figshare.3472679.v3
DOI: 10.6084/m9.figshare.11985990.v1
title: data and programfor revised article.rar

description: data article
DOI: 10.6084/m9.figshare.11985873
title: Cost and cost effectiveness analysis of treatment for child undernutrition in low and middle income countries: A systematic review-Dataset

description: Dataset and Data code book for "Cost and cost effectiveness analysis of treatment for child undernutrition in low and middle income countries: A systematic review"
DOI: 10.6084/m9.figshare.11985873.v2
title: Cost and cost effectiveness analysis of treatment for child undernutrition in low and middle income countries: A systematic review-Dataset

description: Dataset and Data code book for "Cost and cost effectiveness analysis of treatment for child undernutrition in low and middle income countries: A systematic review"
DOI: 10.6084/m9.figshare.11985873.v1
title: Cost and cost effectiveness analysis of treatment for child undernutrition in low and middle income countries: A systematic review

description: Dataset and Data code book for "Cost and cost effectiveness analysis of treatment for child undernutrition in low and middle income countries: A systematic review"
DOI: 10.6084/m9.figshare.11985750
title: Additional File 2.tab.gz

description: This is the dataset used in the paper Effect of Sequence Padding on the Performance of Protein-Based Deep Learning Models by Angela Lopez-del Rio, Maria Martin, Alexandre Perera-Lluna and Rabie Saidi.<br>The UniprotKB/Swiss-Prot database (version 2019_05) protein entries analysed during the current study can be accessed and downloaded through the following link: http://ftp.ebi.ac.uk/pub/databases/uniprot/previous_releases/release-2019_05/knowledgebase/uniprot_sprot-only2019_05.tar.gz. Since this data needs further filtering to get only taxonomy Archaea, we have uploaded here the data analysed in this article.<br>The code is publicly available at https://github.com/b2slab/padding_benchmark.
DOI: 10.6084/m9.figshare.11985750.v1
title: Additional File 2.tab.gz

description: This is the dataset used in the paper Effect of Sequence Padding on the Performance of Protein-Based Deep Learning Models by Angela Lopez-del Rio, Maria Martin, Alexandre Perera-Lluna and Rabie Saidi.<br>The UniprotKB/Swiss-Prot database (version 2019_05) protein entries analysed during the current study can be accessed and downloaded through the following link: http://ftp.ebi.ac.uk/pub/databases/uniprot/previous_releases/release-2019_05/knowledgebase/uniprot_sprot-only2019_05.tar.gz. Since this data needs further filtering to get only taxonomy Archaea, we have uploaded here the data analysed in this article.<br>The code is publicly available at https://github.com/b2slab/padding_benchmark.
DOI: 10.6084/m9.figshare.11985735
title: Supplementary materials

description: The supplementary materials include the illustrative example data used to demonstrate the usefulness of latent interdependence model, Table 8, and the report for effective sample size from Bayesian estimations.
DOI: 10.6084/m9.figshare.11985747
title: Dataset with photos of the wings and description of the diet of the bat Pteronotus parnellii

description: Wing photos and the description of the diet (in fasta files) from 20 individuals of the bat Pteronotus mesoamericanus.<br>
DOI: 10.6084/m9.figshare.11985747.v1
title: Dataset with photos of the wings and description of the diet of the bat Pteronotus parnellii

description: Wing photos and fasta files with data from diet of the bat Pteronotus mesoamericanus.<br>
DOI: 10.6084/m9.figshare.11985339
title: SGC Data.xlsx

description: Content retrieved from web pages of local operators.
DOI: 10.6084/m9.figshare.11985354
title: S7: Magnetite bearing quartzite with no calibration

description: 3D mineral texture quantification method<br>
DOI: 10.6084/m9.figshare.11985324
title: Supplemental Data. Sharp et al. 2020. PFAS in ducks and the environment, ETCJ, https://doi.org/10.1002/etc.4818

description: Concentrations of PFAS measured in ducks, water, sediment and soils from wetlands across Victoria, south-east Australia and equation for calculating risk form tolerable daily intake for determining threshold concentration advice in game ducks.
DOI: 10.6084/m9.figshare.11985324.v1
title: Supplemental Data. Sharp et al. 2020. PFAS in ducks and the environment, ETCJ, https://doi.org/10.1002/etc.4818

description: Concentrations of PFAS measured in ducks, water, sediment and soils from wetlands across Victoria, south-east Australia and equation for calculating risk form tolerable daily intake for determining threshold concentration advice in game ducks.
DOI: 10.6084/m9.figshare.11985354.v1
title: S7: Magnetite bearing quartzite with no calibration

description: 3D mineral texture quantification method<br>
DOI: 10.6084/m9.figshare.11985294
title: Teaching Survey Public

description: Survey of higher education instructors and professors about classroom policies, syllabus design, and expectations of students.
DOI: 10.6084/m9.figshare.11985258
title: database: Discrimination of oil contaminants using supervised Kohonen network and unconventional steady state fluorescence spectroscopy: a comparative evaluation

description: Six types of oil were chosen as the experiment samples: diesel (0#), gasoline (92#), gasoline (95#), jet fuel, mineral oil (industrial grade) and lubricating oil. A solvent with a concentration of 0.1 mol / L was obtained by dissolving sodium dodecyl sulfate (SDS) in seawater (Bohai Sea, China). Each oil was weighed by using the precision electronic scale (FA1004, Tianjin Tianma Weighing Apparatus Co., Ltd., China). The primary solution was obtained by dissolving the oils in SDS solvent and fixing it in 100 ml volumetric flasks. 15 samples covered the concentration range from 0.2 mg/mL to 3 mg/mL were obtained by further diluting the primary solution with SDS solvent. Finally, 90 (6×15) samples were obtained.
DOI: 10.6084/m9.figshare.11985234
title: Untitled Item

description: Previous studies reported the chemotherapy (CT) was not associated with improved survival in metaplastic cancer of breast (MBC). The role of hormonal receptor (HR) status in CT is unclear. We hypothesized that patients receiving CT had better survival for early and locally advanced MBC in different HR status
DOI: 10.6084/m9.figshare.11985234.v1
title: Untitled Item

description: Previous studies reported the chemotherapy (CT) was not associated with improved survival in metaplastic cancer of breast (MBC). The role of hormonal receptor (HR) status in CT is unclear. We hypothesized that patients receiving CT had better survival for early and locally advanced MBC in different HR status
DOI: 10.6084/m9.figshare.11985258.v1
title: database: Discrimination of oil contaminants using supervised Kohonen network and unconventional steady state fluorescence spectroscopy: a comparative evaluation

description: 选择了六种类型的油作为实验样品：柴油（0＃），汽油（92＃），汽油（95＃），喷气燃料，矿物油（工业级）和润滑油。将十二烷基硫酸钠（SDS）溶解在海水中（中国渤海），制得浓度为0.1 mol / L的溶剂。使用精密电子秤（中国天津天马衡器有限公司FA1004）称量每种油。通过将油溶解在SDS溶剂中并将其固定在100 ml容量瓶中获得初级溶液。通过进一步用SDS溶剂稀释一次溶液，获得15个样品，其浓度范围从0.2 mg / mL到3 mg / mL。最终，获得90（6×15）个样本。 用FS920稳态荧光光谱仪测量了油样的激发发射矩阵荧光（EEMF）光谱，同步荧光光谱（SFS）和总同步荧光光谱（TSFS）。
DOI: 10.6084/m9.figshare.11985258.v3
title: database: Discrimination of oil contaminants using supervised Kohonen network and unconventional steady state fluorescence spectroscopy: a comparative evaluation

description: Six types of oil were chosen as the experiment samples: diesel (0#), gasoline (92#), gasoline (95#), jet fuel, mineral oil (industrial grade) and lubricating oil. A solvent with a concentration of 0.1 mol / L was obtained by dissolving sodium dodecyl sulfate (SDS) in seawater (Bohai Sea, China). Each oil was weighed by using the precision electronic scale (FA1004, Tianjin Tianma Weighing Apparatus Co., Ltd., China). The primary solution was obtained by dissolving the oils in SDS solvent and fixing it in 100 ml volumetric flasks. 15 samples covered the concentration range from 0.2 mg/mL to 3 mg/mL were obtained by further diluting the primary solution with SDS solvent. Finally, 90 (6×15) samples were obtained.
DOI: 10.6084/m9.figshare.11985258.v2
title: database: Discrimination of oil contaminants using supervised Kohonen network and unconventional steady state fluorescence spectroscopy: a comparative evaluation

description: Six types of oil were chosen as the experiment samples: diesel (0#), gasoline (92#), gasoline (95#), jet fuel, mineral oil (industrial grade) and lubricating oil. A solvent with a concentration of 0.1 mol / L was obtained by dissolving sodium dodecyl sulfate (SDS) in seawater (Bohai Sea, China). Each oil was weighed by using the precision electronic scale (FA1004, Tianjin Tianma Weighing Apparatus Co., Ltd., China). The primary solution was obtained by dissolving the oils in SDS solvent and fixing it in 100 ml volumetric flasks. 15 samples covered the concentration range from 0.2 mg/mL to 3 mg/mL were obtained by further diluting the primary solution with SDS solvent. Finally, 90 (6×15) samples were obtained.
DOI: 10.6084/m9.figshare.11984940
title: Additional file 2 of Histological correlates of postmortem ultra-high-resolution single-section MRI in cortical cerebral microinfarcts

description: Additional file 2.
DOI: 10.6084/m9.figshare.11984940.v1
title: Additional file 2 of Histological correlates of postmortem ultra-high-resolution single-section MRI in cortical cerebral microinfarcts

description: Additional file 2.
DOI: 10.6084/m9.figshare.11984847
title: Additional file 9 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. 3b Dataset
DOI: 10.6084/m9.figshare.11984841
title: Additional file 7 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. 2d Dataset
DOI: 10.6084/m9.figshare.11984847.v1
title: Additional file 9 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. 3b Dataset
DOI: 10.6084/m9.figshare.11984838
title: Additional file 6 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. 2c and S2c Dataset
DOI: 10.6084/m9.figshare.11984838.v1
title: Additional file 6 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. 2c and S2c Dataset
DOI: 10.6084/m9.figshare.11984841.v1
title: Additional file 7 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. 2d Dataset
DOI: 10.6084/m9.figshare.11984829
title: Additional file 3 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. S1c and S1d Dataset
DOI: 10.6084/m9.figshare.11984829.v1
title: Additional file 3 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. S1c and S1d Dataset
DOI: 10.6084/m9.figshare.11984835
title: Additional file 5 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. S2b Dataset
DOI: 10.6084/m9.figshare.11984835.v1
title: Additional file 5 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. S2b Dataset
DOI: 10.6084/m9.figshare.11984823
title: Additional file 2 of A heat-sensitive Osh protein controls PI4P polarity

description: Fig. 1c and 1d Dataset