cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14399501.v1
title: mRNA and DNAm references for prostate

description: The data contains a 680-marker expression reference and a 122-marker DNAm reference for Prostate, which can be used to estimate cell type fractions of basal cells, endothelial cells, fibroblasts, luminal cells, immune cells and smooth muscle cells in Prostate tissue with EpiSCORE framework.<br>Prostate_Expref.csvA scRNAseq expression reference for Prostate. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Prostate_Mref.csvA DNAm reference for Prostate. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399498.v1
title: mRNA and DNAm references for lung

description: The data contains a 1788-marker expression reference and a 261-marker DNAm reference for Lung, which can be used to estimate cell type fractions of endothelial cells, epithelial cells, granulocytes, lymphocytes, macrophages, monocytes and stromal cells in Lung tissue with EpiSCORE framework.<br>Lung_Expref.csvA scRNAseq expression reference for Lung. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Lung_Mref.csvA DNAm reference for Lung. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399489
title: mRNA and DNAm references for liver

description: The data contains a 658-marker expression reference and a 171-marker DNAm reference for Liver, which can be used to estimate cell type fractions of cholangiocytes, endothelial cells, hepatocytes, immune cells and kupffer cells (macrophages) in Liver tissue with EpiSCORE framework.<br>Liver_Expref.csvA scRNAseq expression reference for Liver. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Liver_Mref.csvA DNAm reference for Liver. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.15468/yjx6d9
title: Two new species of snailfishes of the genus Careproctus (Cottoidei: Liparidae) from the western North Pacific Ocean with a range extension of Careproctus brevipectoralis

description: This dataset contains the digitized treatments in Plazi based on the original journal article Kai, Yoshiaki, Endo, Hiromitsu, Tashiro, Fumihito, Nakayama, Naohide (2021): Two new species of snailfishes of the genus Careproctus (Cottoidei: Liparidae) from the western North Pacific Ocean with a range extension of Careproctus brevipectoralis. Zootaxa 4951 (2): 361-371, DOI: https://doi.org/10.11646/zootaxa.4951.2.9
DOI: 10.6084/m9.figshare.14399441
title: mRNA and DNAm references for breast

description: The data contains a 2907-marker expression reference and a 343-marker DNAm reference for Breast, which can be used to estimate cell type fractions of basal cells, endothelial cells, fat cells, fibroblasts, luminal cells, lymphocytes and macrophages in Breast tissue with EpiSCORE framework.<br>Breast_Expref.csvA scRNAseq expression reference for Breast. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Breast_Mref.csvA DNAm reference for Breast. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399468.v1
title: mRNA and DNAm references for heart

description: The data contains a 1180-marker expression reference and a 207-marker DNAm reference for Heart, which can be used to estimate cell type fractions of cardiac muscle cells, endothelial cells, fibroblasts, macrophages and smooth muscle cells in Heart tissue with EpiSCORE framework.<br>Heart_Expref.csvA scRNAseq expression reference for Heart. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Heart_Mref.csvA DNAm reference for Heart. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399468
title: mRNA and DNAm references for heart

description: The data contains a 1180-marker expression reference and a 207-marker DNAm reference for Heart, which can be used to estimate cell type fractions of cardiac muscle cells, endothelial cells, fibroblasts, macrophages and smooth muscle cells in Heart tissue with EpiSCORE framework.<br>Heart_Expref.csvA scRNAseq expression reference for Heart. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Heart_Mref.csvA DNAm reference for Heart. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399357
title: mRNA and DNAm references for brain

description: The data contains a 1243-marker expression reference and a 110-marker DNAm reference for Brain, which can be used to estimate cell type fractions of neurons, astrocytes, oligodendrocytes, endothelial cells, microglia and oligodendrocyte progenitor cells in Brain tissue with EpiSCORE framework.<br>Brain_Expref.csvA scRNAseq expression reference for Brain. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Brain_Mref.csvA DNAm reference for Brain. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399336
title: mRNA and DNAm references for bladder

description: The data contains a 522-marker expression reference and a 134-marker DNAm reference for bladder, which can be used to estimate cell type fractions of endothelial cells, epithelial cells, fibroblasts and immnue cells in bladder tissue with EpiSCORE framework.<br>Bladder_Expref.csvA scRNAseq expression reference for bladder. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Bladder_Mref.csvA DNAm reference for bladder. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399309
title: mRNA and DNAm references for pancreas (6ct)

description: The data contains a 821-marker expression reference and a 136-marker DNAm reference for Pancreas, which can be used to estimate cell type fractions of acinar cells, ductal cells, endothelial cells, endocrine cells, immune cells and stellate cells in Pancreas tissue with EpiSCORE framework.<br>Pancreas_Expref.csvA scRNAseq expression reference for Pancreas. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Pancreas_Mref.csvA DNAm reference for Pancreas. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399336.v1
title: mRNA and DNAm references for bladder

description: The data contains a 522-marker expression reference and a 134-marker DNAm reference for bladder, which can be used to estimate cell type fractions of endothelial cells, epithelial cells, fibroblasts and immnue cells in bladder tissue with EpiSCORE framework.<br>Bladder_Expref.csvA scRNAseq expression reference for bladder. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Bladder_Mref.csvA DNAm reference for bladder. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399357.v1
title: mRNA and DNAm references for brain

description: The data contains a 1243-marker expression reference and a 110-marker DNAm reference for Brain, which can be used to estimate cell type fractions of neurons, astrocytes, oligodendrocytes, endothelial cells, microglia and oligodendrocyte progenitor cells in Brain tissue with EpiSCORE framework.<br>Brain_Expref.csvA scRNAseq expression reference for Brain. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Brain_Mref.csvA DNAm reference for Brain. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.6084/m9.figshare.14399309.v1
title: mRNA and DNAm references for pancreas (6ct)

description: The data contains a 821-marker expression reference and a 136-marker DNAm reference for Pancreas, which can be used to estimate cell type fractions of acinar cells, ductal cells, endothelial cells, endocrine cells, immune cells and stellate cells in Pancreas tissue with EpiSCORE framework.<br>Pancreas_Expref.csvA scRNAseq expression reference for Pancreas. Each row is a marker gene (in gene symbol) and each column is a cell type. For each marker gene, the value of the reference matrix is the median expression level for each type of cells in scRNAseq data.<br>Pancreas_Mref.csvA DNAm reference for Pancreas. Each row is a marker gene (in entrezID) and each column is a cell type. The last column is the weight for each marker. The value of the matrix is the imputed DNAm level from expression reference.
DOI: 10.5281/zenodo.4675704
title: Entradas Exemplo Cholesky - MC-7 - ERAD/RS 2021

description: Este depósito contém arquivos de entrada para a Fatoração Cholesky no contexto do capítulo de livro publicado na ERAD/RS 2021 entitulado: Desenvolvimento de Aplicações Baseadas em Tarefas com OpenMP Tasks. Cada arquivo compactado contém uma matriz simétrica positiva definida. A primeira linha indica o total de elementos da matriz enquanto as demais linhas contêm os elementos e si.
DOI: 10.5281/zenodo.4675703
title: Entradas Exemplo Cholesky - MC-7 - ERAD/RS 2021

description: Este depósito contém arquivos de entrada para a Fatoração Cholesky no contexto do capítulo de livro publicado na ERAD/RS 2021 entitulado: Desenvolvimento de Aplicações Baseadas em Tarefas com OpenMP Tasks. Cada arquivo compactado contém uma matriz simétrica positiva definida. A primeira linha indica o total de elementos da matriz enquanto as demais linhas contêm os elementos e si.
DOI: 10.5281/zenodo.4683395
title: teokem/project-work-2021-dorotea1808: Second version

description: project-work-2021-dorotea1808 created by GitHub Classroom
DOI: 10.5281/zenodo.4680250
title: teokem/project-work-2021-dorotea1808: Second version

description: project-work-2021-dorotea1808 created by GitHub Classroom
DOI: 10.6084/m9.figshare.14381507.v1
title: Additional file 2-analysis-results

description: Additional File 2: MS Excel file containing all results from the network analyses.<br>Table S1: Homologues-based transcript-phenotype listTable S2-S3:Analysis results for the modules in the middle network and moulting network respectively, includingmodule size, enriched GO terms with smallest p-values, p-values of enrichment analyses based onhomologues, module preservation Z_summary, number of known moulting-associated genes,proportion of TF and DE genes.Table S4:Analysis results for the modules in the global network, including module size, enriched GO terms withsmallest p-values, p-values of enrichment analyses based on homologues, regularized logisticregression coefficients, number of known moulting-associated genes, proportion of TF and DE genes.Table S5-S7:Module assignment results for the known moulting-associated transcripts in the middle, moulting andglobal network; the ranks of these transcripts based on three types of centrality measurements withinmodules; whether they were intramodular hubs or not.Table S8:Two types of RIF scores for the transcripts annotated as transcription factorsTable S9-S11:Centrality measurements, average ranks and annotations for the nodes in three selected modules(yellowgreen, steelblue and violet).Table S12:Annotations of the nodes with highest average ranks from the selected modules.Table S13:Available RNAi results for nodes from the eight selected important modules and nodes with highaverage ranks from modules without passing any criteria.
DOI: 10.6084/m9.figshare.14381507
title: Additional file 2-analysis-results

description: Additional File 2: MS Excel file containing all results from the network analyses.<br>Table S1: Homologues-based transcript-phenotype listTable S2-S3:Analysis results for the modules in the middle network and moulting network respectively, includingmodule size, enriched GO terms with smallest p-values, p-values of enrichment analyses based onhomologues, module preservation Z_summary, number of known moulting-associated genes,proportion of TF and DE genes.Table S4:Analysis results for the modules in the global network, including module size, enriched GO terms withsmallest p-values, p-values of enrichment analyses based on homologues, regularized logisticregression coefficients, number of known moulting-associated genes, proportion of TF and DE genes.Table S5-S7:Module assignment results for the known moulting-associated transcripts in the middle, moulting andglobal network; the ranks of these transcripts based on three types of centrality measurements withinmodules; whether they were intramodular hubs or not.Table S8:Two types of RIF scores for the transcripts annotated as transcription factorsTable S9-S11:Centrality measurements, average ranks and annotations for the nodes in three selected modules(yellowgreen, steelblue and violet).Table S12:Annotations of the nodes with highest average ranks from the selected modules.Table S13:Available RNAi results for nodes from the eight selected important modules and nodes with highaverage ranks from modules without passing any criteria.
DOI: 10.25318/3310032301-eng
title: Contributions to the community due to COVID-19, by business characteristics

description: Contributions to the community due to COVID-19, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership.
DOI: 10.5281/zenodo.4681114
title: BIOPLAT-EU: Marginal, underutilized and contaminated land database

description: This database on marginal, underutilized and contaminated lands (MUC) was compiled based on multiple sources. The sources include: results from related EU and international projects that have already produced valuable tools, maps, and information, which addresses sustainable bioenergy production on MUC lands; data provided by governments as well as public and private stakeholders and; results of remote sensing-based classification of underutilised lands in terms of time series analysis to complete the gaps. The mapping of underutilized lands was conducted on two levels: TIER-1: Pan-European mapping of underutilized lands. More information on this approach can be found here: https://doi.org/10.3390/land10020102 TIER-2: Mapping of underutilized lands in case study areas in six different countries (Germany, Hungary, Italy, Romania, Spain and Ukraine). More detailed delineation of underutilized land patches based on input data with higher spatial and temporal resolution that used within the TIER-1 approach and additional local data. Data sets for the six case study countries published on Zenodo combine TIER-1 and TIER-2 mapping results, e.g TIER-1 results of case study areas are replaced by TIER-2 results. More information on the generation of the contaminated lands data set can be found here https://doi.org/10.3390/en14061566 <em><strong>Terms of use:</strong></em> These data are provided "as is". <em>The authors make <strong>no </strong></em><strong><em>warranty</em></strong><em>, representation, or guaranty of any type as to the completeness, accuracy, content or fitness for any particular purpose or use of any </em><strong><em>open data</em></strong><em> set made available here</em><em>, nor shall any </em><strong><em>warranties</em></strong><em> be implied with respec</em><em>t to the data provided.</em>
DOI: 10.5281/zenodo.4681113
title: BIOPLAT-EU: Marginal, underutilized and contaminated land database

description: This database on marginal, underutilized and contaminated lands (MUC) was compiled based on multiple sources. The sources include: results from related EU and international projects that have already produced valuable tools, maps, and information, which addresses sustainable bioenergy production on MUC lands; data provided by governments as well as public and private stakeholders and; results of remote sensing-based classification of underutilised lands in terms of time series analysis to complete the gaps. The mapping of underutilized lands was conducted on two levels: TIER-1: Pan-European mapping of underutilized lands. More information on this approach can be found here: https://doi.org/10.3390/land10020102 TIER-2: Mapping of underutilized lands in case study areas in six different countries (Germany, Hungary, Italy, Romania, Spain and Ukraine). More detailed delineation of underutilized land patches based on input data with higher spatial and temporal resolution that used within the TIER-1 approach and additional local data. Data sets for the six case study countries published on Zenodo combine TIER-1 and TIER-2 mapping results, e.g TIER-1 results of case study areas are replaced by TIER-2 results. More information on the generation of the contaminated lands data set can be found here https://doi.org/10.3390/en14061566 <em><strong>Terms of use:</strong></em> These data are provided "as is". <em>The authors make <strong>no </strong></em><strong><em>warranty</em></strong><em>, representation, or guaranty of any type as to the completeness, accuracy, content or fitness for any particular purpose or use of any </em><strong><em>open data</em></strong><em> set made available here</em><em>, nor shall any </em><strong><em>warranties</em></strong><em> be implied with respec</em><em>t to the data provided.</em>
DOI: 10.17632/3f3n59n4xs.1
title: Perceptions and attitudes of pharmacy students toward patient safety in interprofessional environment of hospitals- a cross-sectional study from Pakistan

description: Data of a cross-sectional study conducted to assess patient safety attitudes of pharmacy students in Pakistan
DOI: 10.17632/xhjfjrccxs.1
title: Additive Manufacturing by laser-assisted drop deposition from a metal wire - Supplementary material

description: This file contains the data used for the different figures in the paper
DOI: 10.17632/kpjjvg39k3.3
title: Gossip, Sabotage, and Friendship Network Dataset

description: Data were collected from a Men’s and Women’s collegiate crew team members from a small liberal arts college. Participants (N = 44) reported information about how often they gossip about members of the team (positively, negatively), who they have had hooked-up with on the team, who they consider to be friends with on the team, whether they have to sabotaged or been sabotaged by any teammates, their well-being and feelings of loneliness.
DOI: 10.17632/2tcfrpw65n.2
title: PLT

description: Persuasive Linguistic Tricks
DOI: 10.17632/4ypr4vm4vh.1
title: Acer miyabei SSR genotype data

description: SSR data of Acer miyabei genotyped by Saeki et al.
DOI: 10.25318/3310032301-fra
title: Contributions à la communauté en raison de la COVID-19, selon les caractéristiques de l’entreprise

description: Contributions à la communauté en raison de la COVID-19, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité commerciale et le propriétaire majoritaire.
DOI: 10.25318/3310032401-eng
title: Expected level of difficulty in procuring personal protective equipment or supplies, by business characteristics, first quarter of 2021

description: Level of difficulty expected in procuring personal protective equipment or supplies, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership.
DOI: 10.6084/m9.figshare.14381537
title: Additional file 1-supplementary methods

description: Additional file 1:Supplementary methods and information for geneco-expression network construction
DOI: 10.6084/m9.figshare.14381537.v2
title: Additional file 1-supplementary methods

description: Additional file 1:Supplementary methods and information for geneco-expression network construction
DOI: 10.6084/m9.figshare.14381537.v1
title: Additional file 1-supplementary methods

description: Additional file 1:Supplementary methods and information for geneco-expression network construction
DOI: 10.25318/3310032401-fra
title: Degré de difficulté attendu à se procurer de l’équipement de protection individuelle ou des fournitures, selon les caractéristiques de l’entreprise, premier trimestre de 2021

description: Degré de difficulté attendu à se procurer de l’équipement de protection individuelle ou des fournitures, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité commerciale et le propriétaire majoritaire.
DOI: 10.35002/vyq2-gn09
title: Operations and Maintenance (O&M) Activities
DOI: 10.2907/eusilc2004-2019v.2
title: EU Statistics on Income and Living Conditions microdata 2004-2019, release 1 in 2021
DOI: 10.25318/3310032501-eng
title: Reasons difficulty is expected in procuring personal protective equipment or supplies, by business characteristics, first quarter of 2021

description: Reasons business or organization expects significant or some difficulty procuring personal protective equipment or supplies, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership.