cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16909698.v1
title: Additional file 4 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 4. List of unobtained full text.
DOI: 10.6084/m9.figshare.16909701
title: Additional file 5 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 5. Inclusion and exclusion decisions.
DOI: 10.6084/m9.figshare.16909701.v1
title: Additional file 5 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 5. Inclusion and exclusion decisions.
DOI: 10.6084/m9.figshare.16909704
title: Additional file 6 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 6. List of accepted articles (all, unclear contexts, reviews/metapopulation management, translocation synthesis).
DOI: 10.6084/m9.figshare.16909704.v1
title: Additional file 6 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 6. List of accepted articles (all, unclear contexts, reviews/metapopulation management, translocation synthesis).
DOI: 10.6084/m9.figshare.16909707
title: Additional file 7 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 7. List of studies (all, unclear contexts, link data, translocation synthesis).
DOI: 10.6084/m9.figshare.16909707.v1
title: Additional file 7 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 7. List of studies (all, unclear contexts, link data, translocation synthesis).
DOI: 10.6084/m9.figshare.16909713
title: Additional file 9 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 9. List of rejected articles on language.
DOI: 10.6084/m9.figshare.16909713.v1
title: Additional file 9 of Existing evidence on the outcomes of wildlife translocations in protected areas: a systematic map

description: Additional file 9. List of rejected articles on language.
DOI: 10.6084/m9.figshare.16909753
title: Additional file 1 of Clinical M2 macrophages-related genes to aid therapy in pancreatic ductal adenocarcinoma

description: Additional file 1: Table S1: The Results of CIBERSORT algorithm. Table S2: The genes and corresponding modules after WGCNA. Table S3: The results of GO analysis of naïve B cells-related genes. Table S4: The results of KEGG analysis of naïve B cells-related genes. Table S5: The results of univariate regression analysis. Table S6: The results of multivariate regression analysis. Table S7: The results of correlation of risk score with immune infiltrating cell.
DOI: 10.6084/m9.figshare.16909753.v1
title: Additional file 1 of Clinical M2 macrophages-related genes to aid therapy in pancreatic ductal adenocarcinoma

description: Additional file 1: Table S1: The Results of CIBERSORT algorithm. Table S2: The genes and corresponding modules after WGCNA. Table S3: The results of GO analysis of naïve B cells-related genes. Table S4: The results of KEGG analysis of naïve B cells-related genes. Table S5: The results of univariate regression analysis. Table S6: The results of multivariate regression analysis. Table S7: The results of correlation of risk score with immune infiltrating cell.
DOI: 10.5066/p9v6ds94
title: Upper Rio Grande River Basin SSEBop Monthly Sum Actual Evapotranspiration 1984-2015

description: The monthly ET data for the Upper Rio Grande River Basin from January 1984-December 2015 were created using the operational Simplified Surface Energy Balance (SSEBop) model to quantify and map ET over irrigated fields using Landsat imagery and associated weather datasets. The data are provided in GeoTIFF format and can be downloaded per month or year. Satelite-based ET is useful for several agro-hydrologic applications such as basin water budget studies and drought monitoring. The Landsat satellite is unique in providing a field-scale estimation of ET with an unparalleled archive for historical perspective and trend analysis.
DOI: 10.5281/zenodo.5630795
title: LINCS-data

description: LINCS data
DOI: 10.5066/p9yxjdhx
title: Geophysical Data Collected in the Cedar River Floodplain, Cedar Rapids, Iowa, 2015-2017

description: A suite of geophysical methods was used along the Cedar River in Cedar Rapids, Iowa to support the hydrogeologic characterization of the alluvial aquifer associated with the river and to assess the area for suitability for larger-scale airborne geophysics. The aquifer is comprised of sand and gravel, interbedded with finer sediments, and underlain by carbonate-dominated bedrock. The aquifer is the principal source of municipal drinking water for the City of Cedar Rapids. The raw data provided here includes waterborne continuous resistivity profiling (CRP) and continuous seismic profiling (CSP) data (collected at the same time), electrical resistivity tomography (ERT) profiles, and horizontal-to-vertical spectral ratio (HVSR) seismic from April 2015. Also, several borehole geophysical logs including nuclear magnetic resonance (NMR), gamma, and electromagnetic induction (EMI) from nine wells, collected in June 2017, are provided. The CRP, ERT, and borehole logs measure the electrical properties of the subsurface, which can be related to stratigraphic layers. The CRP, CSP, HVSR, and some of the borehole logs characterize the depth to bedrock. Collectively, the suite of methods can help characterize the subsurface and map the extent of the sand and gravel aquifer. In addition, these geophysical measurements can be used to plan and to ground-truth air-borne electromagnetic surveys.
DOI: 10.6084/m9.figshare.16909792
title: Additional file 1 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 1. Metadata and PANGO lineages of the dataset of SARS-CoV-2 samples isolated by IZSAM in provinces of the Abruzzo region (Italy), then shotgun sequenced and analyzed in GENPAT until April 2021 (n = 1592).
DOI: 10.6084/m9.figshare.16909792.v1
title: Additional file 1 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 1. Metadata and PANGO lineages of the dataset of SARS-CoV-2 samples isolated by IZSAM in provinces of the Abruzzo region (Italy), then shotgun sequenced and analyzed in GENPAT until April 2021 (n = 1592).
DOI: 10.6084/m9.figshare.16909795
title: Additional file 2 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 2. Metadata and PANGO lineages of the dataset of SARS-CoV-2 samples isolated from several Italian provinces and retrieved by GENPAT from GISAID until April 2021 (n = 17,201).
DOI: 10.6084/m9.figshare.16909795.v1
title: Additional file 2 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 2. Metadata and PANGO lineages of the dataset of SARS-CoV-2 samples isolated from several Italian provinces and retrieved by GENPAT from GISAID until April 2021 (n = 17,201).
DOI: 10.6084/m9.figshare.16909798
title: Additional file 3 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 3. Distributions per Italian provinces (n = 25) of the SARS-CoV-2 PANGO lineages in Italy (n = 176) retrieved by GENPAT from GISAID until April 2021 (n = 17,201).
DOI: 10.6084/m9.figshare.16909798.v1
title: Additional file 3 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 3. Distributions per Italian provinces (n = 25) of the SARS-CoV-2 PANGO lineages in Italy (n = 176) retrieved by GENPAT from GISAID until April 2021 (n = 17,201).
DOI: 10.6084/m9.figshare.16909801
title: Additional file 4 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 4. Newick file inferred through variant calling-based analysis, binary matrix of functional annotations of variants (pan-SNPs, -MNPs and -InDels) with the program “vcf2mst.pl” and Hamming-like distance-based minimum spanning tree (MST) implemented in GrapeTree (“MSTree V2”), from the dataset of SARS-CoV-2 samples isolated by IZSAM in provinces of the Abruzzo region (Italy), then shotgun sequenced and analyzed in GENPAT until April 2021 (n = 1553).
DOI: 10.6084/m9.figshare.16909801.v1
title: Additional file 4 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 4. Newick file inferred through variant calling-based analysis, binary matrix of functional annotations of variants (pan-SNPs, -MNPs and -InDels) with the program “vcf2mst.pl” and Hamming-like distance-based minimum spanning tree (MST) implemented in GrapeTree (“MSTree V2”), from the dataset of SARS-CoV-2 samples isolated by IZSAM in provinces of the Abruzzo region (Italy), then shotgun sequenced and analyzed in GENPAT until April 2021 (n = 1553).
DOI: 10.6084/m9.figshare.16909804
title: Additional file 5 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 5. Newick file inferred through variant calling-based analysis, binary matrix of functional annotations of variants (pan-SNPs, -MNPs and -InDels) with the program “vcf2mst.pl” and Hamming-like distance-based minimum spanning tree (MST) implemented in GrapeTree (“MSTree V2”), from the dataset of SARS-CoV-2 samples isolated from several Italian provinces and retrieved by GENPAT from GISAID until April 2021 (n = 15,451).
DOI: 10.6084/m9.figshare.16909804.v1
title: Additional file 5 of SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

description: Additional file 5. Newick file inferred through variant calling-based analysis, binary matrix of functional annotations of variants (pan-SNPs, -MNPs and -InDels) with the program “vcf2mst.pl” and Hamming-like distance-based minimum spanning tree (MST) implemented in GrapeTree (“MSTree V2”), from the dataset of SARS-CoV-2 samples isolated from several Italian provinces and retrieved by GENPAT from GISAID until April 2021 (n = 15,451).
DOI: 10.6084/m9.figshare.16909836
title: Additional file 1 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 1. Standardized expression level files of GSE26387, GSE26440, GSE13904 and GSE4607.
DOI: 10.6084/m9.figshare.16909839
title: Additional file 2 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 2. Screening of 2009 differentially expressed genes with significant consistencywith significant consistency using MetaDE package.
DOI: 10.6084/m9.figshare.16909836.v1
title: Additional file 1 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 1. Standardized expression level files of GSE26387, GSE26440, GSE13904 and GSE4607.
DOI: 10.6084/m9.figshare.16909839.v1
title: Additional file 2 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 2. Screening of 2009 differentially expressed genes with significant consistencywith significant consistency using MetaDE package.
DOI: 10.6084/m9.figshare.16909842
title: Additional file 3 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 3. The genes in the nine significant stable modules, respectively.
DOI: 10.6084/m9.figshare.16909842.v1
title: Additional file 3 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 3. The genes in the nine significant stable modules, respectively.
DOI: 10.6084/m9.figshare.16909845
title: Additional file 4 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 4. Significantly enriched genetic information in stable modules.
DOI: 10.6084/m9.figshare.16909845.v1
title: Additional file 4 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 4. Significantly enriched genetic information in stable modules.
DOI: 10.6084/m9.figshare.16909848
title: Additional file 5 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 5. A total of 809 pairs of interacting connected pairs in PPI network.
DOI: 10.6084/m9.figshare.16909848.v1
title: Additional file 5 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 5. A total of 809 pairs of interacting connected pairs in PPI network.
DOI: 10.6084/m9.figshare.16909851.v1
title: Additional file 6 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 6. A total of 157 KEGG pathways related to ulcerative colitis in Comparative Toxicogenomics Database database.
DOI: 10.6084/m9.figshare.16909851
title: Additional file 6 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 6. A total of 157 KEGG pathways related to ulcerative colitis in Comparative Toxicogenomics Database database.
DOI: 10.6084/m9.figshare.16909854
title: Additional file 7 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 7. Screening of optimized gene combinations using recursive feature elimination method.
DOI: 10.6084/m9.figshare.16909854.v1
title: Additional file 7 of Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

description: Additional file 7. Screening of optimized gene combinations using recursive feature elimination method.
DOI: 10.6084/m9.figshare.16909881
title: Additional file 2 of Brain areas involved with obsessive-compulsive disorder present different DNA methylation modulation

description: Additional file 2: Table S1. Differentially methylated sites (DMSs) between OCD cases and controls. Table S2. Functional modules identified by FEM (Functional Epigenetic Modules) analysis. Table S3. Differentially methylated regions (DMRs) and related cgs. Table S4. Differential expression analysis between OCD cases and controls. Table S5. Nodes (genes) from STRING final networks classified according to network centrality measures. Table S6: Enrichment results from STRING for the final networks using differentially expressed genes (DEG), genes located on differentially methylated regions. Table S7. Transcription factors (TF) annotated from differentially methylated regions (DMRs) matched on differentially expressed genes (DEGs).
DOI: 10.6084/m9.figshare.16909881.v1
title: Additional file 2 of Brain areas involved with obsessive-compulsive disorder present different DNA methylation modulation

description: Additional file 2: Table S1. Differentially methylated sites (DMSs) between OCD cases and controls. Table S2. Functional modules identified by FEM (Functional Epigenetic Modules) analysis. Table S3. Differentially methylated regions (DMRs) and related cgs. Table S4. Differential expression analysis between OCD cases and controls. Table S5. Nodes (genes) from STRING final networks classified according to network centrality measures. Table S6: Enrichment results from STRING for the final networks using differentially expressed genes (DEG), genes located on differentially methylated regions. Table S7. Transcription factors (TF) annotated from differentially methylated regions (DMRs) matched on differentially expressed genes (DEGs).
DOI: 10.6084/m9.figshare.16909890.v1
title: Additional file 1 of Analysis of multiple gene co-expression networks to discover interactions favoring CFTR biogenesis and ΔF508-CFTR rescue

description: Additional file 1. Table S1. Summary of differentially expressed genes across conditions in CFBE cells. Summary of up- and down-regulated differentially expressed genes in conditions vs. controls. Table S2. Differentially expressed genes in the miR-138/SIN3A condition. List of differentially expressed genes in the miR-138/SIN3A conditions vs. scrambled siRNA control. Table S3. Differentially expressed genes in the NEDD8/SYVN1 condition. List of differentially expressed genes in the NEDD8/SYVN1 conditions vs. scrambled siRNA control. Table S4. Differentially expressed genes in the temperature condition. List of differentially expressed genes in the temperature conditions vs. 37°C control. Table S5. CFTR interactome used as seed nodes. List of CFTR effectors and interactors used as seed nodes in the M-module analysis. Table S6. DsiRNA and primer sequences. List of siRNA and primer sequences used in the functional knockdown experiments to test for CFTR rescue. Table S7. Untested non-seed module genes. List of genes resulting from the M-module analysis that have not been previously tested or linked to CFTR. Table S8. Top 50 predicted gene ontology biological processes for CHURC1. List of biological processes associated with CHURC1 according to the ARChS4 software. Table S9. Top 50 predicted gene ontology biological processes for RPL15. List of biological processes associated with RPL15 according to the ARChS4 software. Table S10. Top 50 predicted gene ontology biological processes for GZF1. List of biological processes associated with GZF1 according to the ARChS4 software. Figure S1. Schematic showing intersection of differentially expressed genes across conditions. Controls and conditions are described in Table 1. Up arrows indicate up-regulated genes; down arrows indicate down-regulated genes. Significance is defined as FDR &lt; 0.05. Figure S2. Representative transepithelial current tracings demonstrating the effects of individual gene knockdown on CFTR-dependent chloride current in CFBE cells. The Y-axis represents transepithelial current in µA and the X-axis represents time in seconds. The addition of the cAMP agonists forskolin and IBMX resulted in an increase in CFTR-dependent transepithelial chloride current in cells treated with DsiRNAs targeting: A) CHURC1 or B) RPL15. This increase in current was inhibited by the CFTR channel inhibitor GlyH-101. The tracing shown in C demonstrates that DsiRNA knockdown of THOC7 was ineffective in restoring CFTR-dependent chloride current.
DOI: 10.6084/m9.figshare.16909890
title: Additional file 1 of Analysis of multiple gene co-expression networks to discover interactions favoring CFTR biogenesis and ΔF508-CFTR rescue

description: Additional file 1. Table S1. Summary of differentially expressed genes across conditions in CFBE cells. Summary of up- and down-regulated differentially expressed genes in conditions vs. controls. Table S2. Differentially expressed genes in the miR-138/SIN3A condition. List of differentially expressed genes in the miR-138/SIN3A conditions vs. scrambled siRNA control. Table S3. Differentially expressed genes in the NEDD8/SYVN1 condition. List of differentially expressed genes in the NEDD8/SYVN1 conditions vs. scrambled siRNA control. Table S4. Differentially expressed genes in the temperature condition. List of differentially expressed genes in the temperature conditions vs. 37°C control. Table S5. CFTR interactome used as seed nodes. List of CFTR effectors and interactors used as seed nodes in the M-module analysis. Table S6. DsiRNA and primer sequences. List of siRNA and primer sequences used in the functional knockdown experiments to test for CFTR rescue. Table S7. Untested non-seed module genes. List of genes resulting from the M-module analysis that have not been previously tested or linked to CFTR. Table S8. Top 50 predicted gene ontology biological processes for CHURC1. List of biological processes associated with CHURC1 according to the ARChS4 software. Table S9. Top 50 predicted gene ontology biological processes for RPL15. List of biological processes associated with RPL15 according to the ARChS4 software. Table S10. Top 50 predicted gene ontology biological processes for GZF1. List of biological processes associated with GZF1 according to the ARChS4 software. Figure S1. Schematic showing intersection of differentially expressed genes across conditions. Controls and conditions are described in Table 1. Up arrows indicate up-regulated genes; down arrows indicate down-regulated genes. Significance is defined as FDR &lt; 0.05. Figure S2. Representative transepithelial current tracings demonstrating the effects of individual gene knockdown on CFTR-dependent chloride current in CFBE cells. The Y-axis represents transepithelial current in µA and the X-axis represents time in seconds. The addition of the cAMP agonists forskolin and IBMX resulted in an increase in CFTR-dependent transepithelial chloride current in cells treated with DsiRNAs targeting: A) CHURC1 or B) RPL15. This increase in current was inhibited by the CFTR channel inhibitor GlyH-101. The tracing shown in C demonstrates that DsiRNA knockdown of THOC7 was ineffective in restoring CFTR-dependent chloride current.
DOI: 10.6084/m9.figshare.16909903
title: Additional file 1 of Distinct patterns of whole blood transcriptional responses are induced in mice following immunisation with adenoviral and poxviral vector vaccines encoding the same antigen

description: Additional file 1: Supplementary Figure 1. Overlap between significantly differentially expressed genes (DEGs) in mouse whole blood 24 h after immunisation with human adenovirus serotype 5 (HuAd5) encoding a bacterial (factor H binding protein, Ad-fHbp), viral (pre-fusion F protein, Ad-preF), or no antigen (Ad-empty) and a modified vaccinia Ankara (MVA) virus encoding fHbp. Significantly DEGs were defined as those with an FDR
DOI: 10.6084/m9.figshare.16909903.v1
title: Additional file 1 of Distinct patterns of whole blood transcriptional responses are induced in mice following immunisation with adenoviral and poxviral vector vaccines encoding the same antigen

description: Additional file 1: Supplementary Figure 1. Overlap between significantly differentially expressed genes (DEGs) in mouse whole blood 24 h after immunisation with human adenovirus serotype 5 (HuAd5) encoding a bacterial (factor H binding protein, Ad-fHbp), viral (pre-fusion F protein, Ad-preF), or no antigen (Ad-empty) and a modified vaccinia Ankara (MVA) virus encoding fHbp. Significantly DEGs were defined as those with an FDR
DOI: 10.6084/m9.figshare.16909914.v1
title: Additional file 3 of Isolation and characterization of high affinity and highly stable anti-Chikungunya virus antibodies using ALTHEA Gold Libraries™

description: Additional file 3. Principal characteristics in the sequence of the heavy and ligth variable chains of the anti-Chikungunya antibodies.
DOI: 10.6084/m9.figshare.16909917
title: Additional file 4 of Isolation and characterization of high affinity and highly stable anti-Chikungunya virus antibodies using ALTHEA Gold Libraries™

description: Additional file 4. Nucleotide sequence of 033 isolate Chikungunya virus in fasta format.