cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6808211.v1
title: Additional file 2: of Consistent and reproducible long-term in vitro growth of health and disease-associated oral subgingival biofilms

description: Table S2. Per sample total read counts and absolute read counts for each species and genus detected by QIIME analysis of raw fasta files. Tab 1 (otu_table_L6) is all taxonomic assignments down to genus level. Tab 2 (otu_table_L7) is all taxonomic assignments down to species level. Tab 3 (CompHOMINGS-qiime) has total, matched, and unmatched read counts for each biofilm for HOMINGS and QIIME analysis, as well as the total number of species detected by each method. (XLSX 135 kb)
DOI: 10.6084/m9.figshare.6808196
title: Additional file 1: of Consistent and reproducible long-term in vitro growth of health and disease-associated oral subgingival biofilms

description: Table S1. Per sample total read counts and absolute read counts for each species and genus detected (species table from HOMINGS analysis). (XLSX 180 kb)
DOI: 10.6084/m9.figshare.6808199
title: MOESM4 of Debye–Hückel theory for refugees’ migration

description: Density. The DensityMatrixSij.csv contains the population density between every Syrian city i and Lebanese city j. (CSV 7 kB)
DOI: 10.6084/m9.figshare.6808196.v1
title: Additional file 1: of Consistent and reproducible long-term in vitro growth of health and disease-associated oral subgingival biofilms

description: Table S1. Per sample total read counts and absolute read counts for each species and genus detected (species table from HOMINGS analysis). (XLSX 180 kb)
DOI: 10.6084/m9.figshare.6808199.v1
title: MOESM4 of Debye–Hückel theory for refugees’ migration

description: Density. The DensityMatrixSij.csv contains the population density between every Syrian city i and Lebanese city j. (CSV 7 kB)
DOI: 10.6084/m9.figshare.6808184
title: Additional file 1: of Trend of HIV/AIDS for the last 26 years and predicting achievement of the 90–90-90 HIV prevention targets by 2020 in Ethiopia: a time series analysis

description: Trend of HIV/AIDS for the last 26 Years and Predicting Achievement of the 90-90-90 HIV Prevention Targets by 2020 in Ethiopia: A Time Series Analysis. (XLSX 18 kb)
DOI: 10.6084/m9.figshare.6808184.v1
title: Additional file 1: of Trend of HIV/AIDS for the last 26 years and predicting achievement of the 90–90-90 HIV prevention targets by 2020 in Ethiopia: a time series analysis

description: Trend of HIV/AIDS for the last 26 Years and Predicting Achievement of the 90-90-90 HIV Prevention Targets by 2020 in Ethiopia: A Time Series Analysis. (XLSX 18 kb)
DOI: 10.6084/m9.figshare.6808181
title: MOESM3 of Debye–Hückel theory for refugees’ migration

description: Syria–Syria-distance. The Syria-Syria-Distance.csv contains the pairwise distance matrix between Syrian cities retrieved through the google API. (CSV 2 kB)
DOI: 10.6084/m9.figshare.6808181.v1
title: MOESM3 of Debye–Hückel theory for refugees’ migration

description: Syria–Syria-distance. The Syria-Syria-Distance.csv contains the pairwise distance matrix between Syrian cities retrieved through the google API. (CSV 2 kB)
DOI: 10.6084/m9.figshare.6808163
title: MOESM2 of Debye–Hückel theory for refugees’ migration

description: Distance. The Distance.csv contains the pairwise distance matrix between Origin and destination cities retrieved through the google API. (CSV 3 kB)
DOI: 10.6084/m9.figshare.6808163.v1
title: MOESM2 of Debye–Hückel theory for refugees’ migration

description: Distance. The Distance.csv contains the pairwise distance matrix between Origin and destination cities retrieved through the google API. (CSV 3 kB)
DOI: 10.6084/m9.figshare.6808151
title: MOESM1 of Debyeâ HĂźckel theory for refugeesâ migration

description: Migration data. The Migration Data.xlsx is an excel file whose first row contains the name of the Syrian origin cities while the first column contains the Lebanese destination cities. The entries refer to the number of refugees fleeing from the corresponding origin city to the destination. (XLSX 8 kB)
DOI: 10.6084/m9.figshare.6808151.v1
title: MOESM1 of Debyeâ HĂźckel theory for refugeesâ migration

description: Migration data. The Migration Data.xlsx is an excel file whose first row contains the name of the Syrian origin cities while the first column contains the Lebanese destination cities. The entries refer to the number of refugees fleeing from the corresponding origin city to the destination. (XLSX 8 kB)
DOI: 10.6084/m9.figshare.6808010
title: Additional file 2: of Whole-transcriptome changes in gene expression accompany aging of sensory neurons in Aplysia californica

description: Excel file containing all differentially expressed genes identified by STAR. (XLSX 58 kb)
DOI: 10.6084/m9.figshare.6808010.v1
title: Additional file 2: of Whole-transcriptome changes in gene expression accompany aging of sensory neurons in Aplysia californica

description: Excel file containing all differentially expressed genes identified by STAR. (XLSX 58 kb)
DOI: 10.6084/m9.figshare.6807992
title: Additional file 3: of Whole-transcriptome changes in gene expression accompany aging of sensory neurons in Aplysia californica

description: Excel file with a complete list of GO ontologies enriched in Blast2GO analysis. This file contains p-values and sequences identified for each ontology as well. (XLSX 3392 kb)
DOI: 10.6084/m9.figshare.6807992.v1
title: Additional file 3: of Whole-transcriptome changes in gene expression accompany aging of sensory neurons in Aplysia californica

description: Excel file with a complete list of GO ontologies enriched in Blast2GO analysis. This file contains p-values and sequences identified for each ontology as well. (XLSX 3392 kb)
DOI: 10.6084/m9.figshare.6807974
title: Additional file 4: of Whole-transcriptome changes in gene expression accompany aging of sensory neurons in Aplysia californica

description: Excel file listing all ion channel genes identified in Blast2GO. (XLSX 175 kb)
DOI: 10.6084/m9.figshare.6807896
title: Additional file 1: of Genetics of resistance to photobacteriosis in gilthead sea bream (Sparus aurata) using 2b-RAD sequencing

description: Information on inflation of P-value, LD among significant SNPs, genes at QTL region and Manhattan plots. This file contains information on average and sex-specific (male vs. female) linkage maps along with 36Â bp sequences of 2b-RAD loci (XLSX 1344Â kb).
DOI: 10.6084/m9.figshare.6807896.v1
title: Additional file 1: of Genetics of resistance to photobacteriosis in gilthead sea bream (Sparus aurata) using 2b-RAD sequencing

description: Information on inflation of P-value, LD among significant SNPs, genes at QTL region and Manhattan plots. This file contains information on average and sex-specific (male vs. female) linkage maps along with 36Â bp sequences of 2b-RAD loci (XLSX 1344Â kb).
DOI: 10.6084/m9.figshare.6807875
title: Additional file 4: of Novel metrics for quantifying bacterial genome composition skews

description: Table S3. Presence and absence of genes associated with replication, recombination, and repair. Data were retrieved from the KEGG Orthology database [45] for homologous recombination (ko03440), mismatch repair (ko03430), DNA repair and recombination (ko3400), nucleotide excision repair (ko03420), and base excision repair pathways (ko03410). Asterisks denote skew outliers. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.6807875.v1
title: Additional file 4: of Novel metrics for quantifying bacterial genome composition skews

description: Table S3. Presence and absence of genes associated with replication, recombination, and repair. Data were retrieved from the KEGG Orthology database [45] for homologous recombination (ko03440), mismatch repair (ko03430), DNA repair and recombination (ko3400), nucleotide excision repair (ko03420), and base excision repair pathways (ko03410). Asterisks denote skew outliers. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.6807854
title: Additional file 3: of Novel metrics for quantifying bacterial genome composition skews

description: Table S2. (a) Summary of outliers counted by genus. (b-d) Lists of 7738 bacterial genomes sorted by dot-skew, cross-skew, and residual skew, respectively, with outliers indicated in red (positive outlier) or blue (negative outlier). (e) Summary of the derivation of the statistical thresholds. (XLSX 1059 kb)
DOI: 10.6084/m9.figshare.6807854.v1
title: Additional file 3: of Novel metrics for quantifying bacterial genome composition skews

description: Table S2. (a) Summary of outliers counted by genus. (b-d) Lists of 7738 bacterial genomes sorted by dot-skew, cross-skew, and residual skew, respectively, with outliers indicated in red (positive outlier) or blue (negative outlier). (e) Summary of the derivation of the statistical thresholds. (XLSX 1059 kb)
DOI: 10.6084/m9.figshare.6807842
title: Additional file 2: of Novel metrics for quantifying bacterial genome composition skews

description: Table S1. Accession, name, GC content, skew parameters and skew metrics for 7738 bacterial genomes studied. (XLSX 1838 kb)
DOI: 10.6084/m9.figshare.6807842.v1
title: Additional file 2: of Novel metrics for quantifying bacterial genome composition skews

description: Table S1. Accession, name, GC content, skew parameters and skew metrics for 7738 bacterial genomes studied. (XLSX 1838 kb)
DOI: 10.6084/m9.figshare.6807737
title: Additional file 3: of Hepatitis B virus infection among pregnant women in Ethiopia: a systematic review and Meta-analysis of prevalence studies

description: The prevalence of HBV infection among pregnant women in different regions of Ethiopia from 1988 to 2017. (XLSX 20 kb)
DOI: 10.6084/m9.figshare.6807737.v1
title: Additional file 3: of Hepatitis B virus infection among pregnant women in Ethiopia: a systematic review and Meta-analysis of prevalence studies

description: The prevalence of HBV infection among pregnant women in different regions of Ethiopia from 1988 to 2017. (XLSX 20 kb)
DOI: 10.6084/m9.figshare.6807689
title: Additional file 1: of A standardized workflow for submitting data to the Minimum Information about a Biosynthetic Gene cluster (MIBiG) repository: prospects for research-based educational experiences

description: Supporting documents for MIBiG entries. (ZIP 1328 kb)
DOI: 10.6084/m9.figshare.6807689.v1
title: Additional file 1: of A standardized workflow for submitting data to the Minimum Information about a Biosynthetic Gene cluster (MIBiG) repository: prospects for research-based educational experiences

description: Supporting documents for MIBiG entries. (ZIP 1328 kb)
DOI: 10.6084/m9.figshare.6807521
title: Raw values in PONE-D-17-20773

description: <pre>The raw values behind graphs or figures presented in the toxicological assessment of multi-walled carbon nanotubes combined with nonylphenol in male mice were uploaded to a stable public repository Figshare as required.</pre>
DOI: 10.6084/m9.figshare.6807521.v1
title: Raw values in PONE-D-17-20773

description: <pre>The raw values behind graphs or figures presented in the toxicological assessment of multi-walled carbon nanotubes combined with nonylphenol in male mice were uploaded to a stable public repository Figshare as required.</pre>
DOI: 10.6084/m9.figshare.6807473
title: 263_GWAS

description: GWAS results for 263 individuals in the Major Goodman panel using whole genome sequence data at sites that overlap with the 600K SNP Chip used by Unterseer et al.
DOI: 10.6084/m9.figshare.6807473.v1
title: 263_GWAS

description: GWAS results for 263 individuals in the Major Goodman panel using whole genome sequence data at sites that overlap with the 600K SNP Chip used by Unterseer et al.
DOI: 10.6084/m9.figshare.6807470
title: Data from: Movement behaviour of the monito del monte (Dromiciops gliroides): new insights into the ecology of a unique marsupial

description: Original dataset from:<br>Franco, L.M., F.E. Fontúrbel, G. Guevara & M Soto-Gamboa. 2019. Movement behaviour of the monito del monte (Dromiciops gliroides): new insights into the ecology of a unique marsupial. Revista Chilena de Historia Natural (2019).<br>
DOI: 10.6084/m9.figshare.6807461
title: 281_GWAS

description: GWAS with 281 individuals from Major Goodman panel and GBS data. From Josephs et. al.
DOI: 10.6084/m9.figshare.6807461.v1
title: 281_GWAS

description: GWAS with 281 individuals from Major Goodman panel and GBS data. From Josephs et. al.
DOI: 10.6084/m9.figshare.6807386
title: Piranga mtDNA gene trees

description: Gene tree files, produced in RAxML (GTRGAMMA, 200 rapid BS).
DOI: 10.6084/m9.figshare.6807386.v1
title: Piranga mtDNA gene trees

description: Nexus files containing a gene tree for each mtDNA gene. These were the trees used for ASTRAL-II analysis.
DOI: 10.6084/m9.figshare.6807386.v3
title: Piranga mtDNA gene trees

description: Gene tree files, produced in RAxML (GTRGAMMA, 200 rapid BS).
DOI: 10.6084/m9.figshare.6807386.v2
title: Piranga mtDNA gene trees

description: Nexus files containing a gene tree for each mtDNA gene. These were the trees used for ASTRAL-II analysis.
DOI: 10.6084/m9.figshare.6807203
title: Prediction and diversity of tracrRNAs from type II CRISPR-Cas systems

description: Type II CRISPR-Cas9 systems require a small RNA called the trans-activating CRISPR RNA (tracrRNA) in order to function. The prediction of these non-coding RNAs in prokaryotic genomes is challenging because they have dissimilar structures, having short stems (3–6 bp) and non-canonical base-pairs e.g. G-A. Much of the tracrRNA is involved in base-pairing interactions with the CRISPR RNA, or itself, or in RNA-protein interactions with Cas9. Here we develop a new bioinformatic tool to predict tracrRNAs. On an experimentally verified test set the algorithm achieved a high sensitivity and specificity, and a low false discovery rate (FDR) on genome analysis. Analysis of representative RefSeq genomes (5462) detected 275 tracrRNAs from 165 genera. These tracrRNAs could be grouped into 15 clusters which were used to build covariance models. These clusters included <i>Streptococci</i> and <i>Staphylococci</i> tracrRNAs from the CRISPR-Cas9 systems which are currently used for gene editing. Compensating base changes observed in the models were consistent with the experimental structures of single guide RNAs (sgRNAs). Other clusters, for which there are not yet structures available, were predicted to form novel tracrRNA folds. These clusters included a large and divergent tracrRNA set from <i>Bacteroidetes</i>. These computational models contribute to the understanding of CRISPR-Cas biology, and will assist in the design of further engineered CRISPR-Cas9 systems. The tracrRNA prediction software is available through a galaxy web server.
DOI: 10.6084/m9.figshare.6807203.v1
title: Prediction and diversity of tracrRNAs from type II CRISPR-Cas systems

description: Type II CRISPR-Cas9 systems require a small RNA called the trans-activating CRISPR RNA (tracrRNA) in order to function. The prediction of these non-coding RNAs in prokaryotic genomes is challenging because they have dissimilar structures, having short stems (3-6 bp) and non-canonical base-pairs e.g. G-A. Much of the tracrRNA is involved in base-pairing interactions with the CRISPR RNA, or itself, or in RNA-protein interactions with Cas9. Here we develop a new bioinformatic tool to predict tracrRNAs. On an experimentally verified test set the algorithm achieved a high sensitivity and specificity, and a low false discovery rate (FDR) on genome analysis. Analysis of representative RefSeq genomes (5462) detected 275 tracrRNAs from 165 genera. These tracrRNAs could be grouped into 15 clusters which were used to build covariance models. These clusters included <i>Streptococci</i> and <i>Staphylococci</i> tracrRNAs from the CRISPR-Cas9 systems which are currently used for gene editing. Compensating base changes observed in the models were consistent with the experimental structures of single guide RNAs (sgRNAs). Other clusters, for which there are not yet structures available, were predicted to form novel tracrRNA folds. These clusters included a large and divergent tracrRNA set from <i>Bacteroidetes</i>. These computational models contribute to the understanding of CRISPR-Cas biology, and will assist in the design of further engineered CRISPR-Cas9 systems. The tracrRNA prediction software is available through a galaxy web server.
DOI: 10.6084/m9.figshare.6807203.v3
title: Prediction and diversity of tracrRNAs from type II CRISPR-Cas systems

description: Type II CRISPR-Cas9 systems require a small RNA called the trans-activating CRISPR RNA (tracrRNA) in order to function. The prediction of these non-coding RNAs in prokaryotic genomes is challenging because they have dissimilar structures, having short stems (3–6 bp) and non-canonical base-pairs e.g. G-A. Much of the tracrRNA is involved in base-pairing interactions with the CRISPR RNA, or itself, or in RNA-protein interactions with Cas9. Here we develop a new bioinformatic tool to predict tracrRNAs. On an experimentally verified test set the algorithm achieved a high sensitivity and specificity, and a low false discovery rate (FDR) on genome analysis. Analysis of representative RefSeq genomes (5462) detected 275 tracrRNAs from 165 genera. These tracrRNAs could be grouped into 15 clusters which were used to build covariance models. These clusters included <i>Streptococci</i> and <i>Staphylococci</i> tracrRNAs from the CRISPR-Cas9 systems which are currently used for gene editing. Compensating base changes observed in the models were consistent with the experimental structures of single guide RNAs (sgRNAs). Other clusters, for which there are not yet structures available, were predicted to form novel tracrRNA folds. These clusters included a large and divergent tracrRNA set from <i>Bacteroidetes</i>. These computational models contribute to the understanding of CRISPR-Cas biology, and will assist in the design of further engineered CRISPR-Cas9 systems. The tracrRNA prediction software is available through a galaxy web server.
DOI: 10.6084/m9.figshare.6807203.v2
title: Prediction and diversity of tracrRNAs from type II CRISPR-Cas systems

description: Type II CRISPR-Cas9 systems require a small RNA called the trans-activating CRISPR RNA (tracrRNA) in order to function. The prediction of these non-coding RNAs in prokaryotic genomes is challenging because they have dissimilar structures, having short stems (3–6 bp) and non-canonical base-pairs e.g. G-A. Much of the tracrRNA is involved in base-pairing interactions with the CRISPR RNA, or itself, or in RNA-protein interactions with Cas9. Here we develop a new bioinformatic tool to predict tracrRNAs. On an experimentally verified test set the algorithm achieved a high sensitivity and specificity, and a low false discovery rate (FDR) on genome analysis. Analysis of representative RefSeq genomes (5462) detected 275 tracrRNAs from 165 genera. These tracrRNAs could be grouped into 15 clusters which were used to build covariance models. These clusters included <i>Streptococci</i> and <i>Staphylococci</i> tracrRNAs from the CRISPR-Cas9 systems which are currently used for gene editing. Compensating base changes observed in the models were consistent with the experimental structures of single guide RNAs (sgRNAs). Other clusters, for which there are not yet structures available, were predicted to form novel tracrRNA folds. These clusters included a large and divergent tracrRNA set from <i>Bacteroidetes</i>. These computational models contribute to the understanding of CRISPR-Cas biology, and will assist in the design of further engineered CRISPR-Cas9 systems. The tracrRNA prediction software is available through a galaxy web server.
DOI: 10.6084/m9.figshare.6807191
title: CRISPR-Cas systems in multicellular cyanobacteria

description: Novel CRISPR-Cas systems possess substantial potential for genome editing and manipulation of gene expression. The types and numbers of CRISPR-Cas systems vary substantially between different organisms. Some filamentous cyanobacteria harbor &gt; 40 different putative CRISPR repeat-spacer cassettes, while the number of <i>cas</i> gene instances is much lower. Here we addressed the types and diversity of CRISPR-Cas systems and of CRISPR-like repeat-spacer arrays in 171 publicly available genomes of multicellular cyanobacteria. The number of 1328 repeat-spacer arrays exceeded the total of 391 encoded Cas1 proteins suggesting a tendency for fragmentation or the involvement of alternative adaptation factors. The model cyanobacterium <i>Anabaena</i> sp. PCC 7120 contains only three <i>cas1</i> genes but hosts three Class 1, possibly one Class 2 and five orphan repeat-spacer arrays, all of which exhibit crRNA-typical expression patterns suggesting active transcription, maturation and incorporation into CRISPR complexes. The CRISPR-Cas system within the element interrupting the <i>Anabaena</i> sp. PCC 7120 <i>fdxN</i> gene, as well as analogous arrangements in other strains, occupy the genetic elements that become excised during the differentiation-related programmed site-specific recombination. This fact indicates the propensity of these elements for the integration of CRISPR-<i>cas</i> systems and points to a previously not recognized connection. The gene <i>all3613</i> resembling a possible Class 2 effector protein is linked to a short repeat-spacer array and a single tRNA gene, similar to its homologs in other cyanobacteria. The diversity and presence of numerous CRISPR-Cas systems in DNA elements that are programmed for homologous recombination make filamentous cyanobacteria a prolific resource for their study. <b>Abbreviations</b>: Cas: CRISPR associated sequences; CRISPR: Clustered Regularly Interspaced Short Palindromic Repeats; C2c: Class 2 candidate; SDR: small dispersed repeat; TSS: transcriptional start site; UTR: untranslated region.
DOI: 10.6084/m9.figshare.6807197.v1
title: The role of SAGA coactivator complex in snRNA transcription

description: The general snRNA gene transcription apparatus has been extensively studied. However, the role of coactivators in this process is far from being clearly understood. Here, we have demonstrated that the <i>Drosophila</i> SAGA complex interacts with the PBP complex, the key component of the snRNA gene transcription apparatus, and is present at the promoter regions of the snRNA genes transcribed by both the RNA polymerase II and RNA polymerase III (U6 snRNA). We show that SAGA interacts with the Brf1 transcription factor, which is a part of the RNA polymerase III transcription apparatus and is present at promoters of a number of Pol III-transcribed genes. Mutations inactivating several SAGA subunit genes resulted in reduced snRNA levels in adult flies, indicating that SAGA is indeed the transcriptional coactivator for the snRNA genes. The transcription of the Pol II and Pol III-transcribed U genes was reduced by mutations in all tested SAGA complex subunits. Therefore, the transcription of the Pol II and Pol III-transcribed U genes was reduced by the mutations in the deubiquitinase module, as well as in the acetyltransferase module of the SAGA, indicating that the whole complex is essential for their transcription. Therefore, the SAGA complex activates snRNA genes suggesting its wide involvement in the regulation of gene transcription, and consequently, in the maintenance of cellular homeostasis.