cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21622760.v1
title: Additional file 26 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 26. List of small, genic deletions identified in the M. oryzae Guy11 genome. The first three columns describe genomic coordinates of the deletion, the fourth column is the missing gene’s ID, and the last column is the name of the genome where the deletion is present.
DOI: 10.6084/m9.figshare.21622757.v1
title: Additional file 25 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 25. List of GenBank accessions for the genomes of rice-infecting M. oryzae isolates used in this study for gene annotation.
DOI: 10.6084/m9.figshare.21622754.v1
title: Additional file 24 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 24. Enriched GO terms in the biological pathway ontology for eccDNA-associated genes. The first column lists the GO term, the second column lists the number of genes annotated with each term, the third column lists the number of genes observed in the eccDNA-associated category, the fourth column list the number of genes expected in that category, the fifth column shows is a description of the go term, the sixth column lists the Chi-square value for that GO term, and the final column lists the ratio of the observed number of genes in the eccDNA-associated category divided by the expected number of genes in that category.
DOI: 10.6084/m9.figshare.21622751.v1
title: Additional file 23 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 23. Enriched GO terms in the molecular function ontology for eccDNA-associated genes. The first column lists the GO term, the second column lists the number of genes annotated with each term, the third column lists the number of genes observed in the eccDNA-associated category, the fourth column lists the number of genes expected in that category, the fifth column shows is a description of the go term, the sixth column lists the Chi-square value for that GO term, and the final column lists the ratio of the observed number of genes in the eccDNA-associated category divided by the expected number of genes in that category.
DOI: 10.6084/m9.figshare.21622748.v1
title: Additional file 22 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 22. Enriched GO terms in the cellular components ontology for eccDNA-associated genes. The first column lists the GO term, the second column lists the number of genes annotated with each term, the third column lists the number of genes observed in the eccDNA-associated category, the fourth column list the number of genes expected in that category, the fifth column shows is a description of the go term, the sixth column lists the Chi-square value for that GO term, and the final column lists the ratio of the observed number of genes in the eccDNA-associated category divided by the expected number of genes in that category.
DOI: 10.6084/m9.figshare.21622745.v1
title: Additional file 21 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 21. List of genes annotated in the M. oryzae Guy11 genome along with other information discussed in this study for each gene. The first three columns describe the genomic coordinates of the gene, the fourth column is the gene’s ID, the fifth column describes whether the gene was predicted to be an effector, the sixth column lists its name if it is a known effector, the seventh column lists the name of the protein in the M. oryzae 70-15 proteome, the eighth column describes whether it is an eccDNA-associated or eccDNA-absent gene, and the last column describes whether this gene was kept in all rice-infecting M. oryzae genomes analyzed.
DOI: 10.6084/m9.figshare.21622742.v1
title: Additional file 20 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 20. List of eccDNA forming regions called using Illumina circularome sequencing data for S. cerevisiae cells from the deletion collection treated with zeocin published by Møller et al. [8]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622736.v1
title: Additional file 19 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 19. List of eccDNA forming regions called using Illumina circularome sequencing data for S. cerevisiae cells from the deletion collection published by Møller et al. [8]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622733.v1
title: Additional file 18 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 18. List of eccDNA forming regions called using Illumina circularome sequencing data for S. cerevisiae GAP1circle cells published by Møller et al. [8]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622730.v1
title: Additional file 17 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 17. List of eccDNA forming regions called using Illumina circularome sequencing data for S. cerevisiae wild type cells published by Møller et al. [7]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622727.v1
title: Additional file 16 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 16. List of eccDNA forming regions called using Illumina circularome sequencing data for A. thaliana flower tissue published by Wang et al. [5]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622724.v1
title: Additional file 15 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 15. List of eccDNA forming regions called using Illumina circularome sequencing data for A. thaliana stem tissue published by Wang et al. [5]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622721.v1
title: Additional file 14 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 14. List of eccDNA forming regions called using Illumina circularome sequencing data for A. thaliana root tissue published by Wang et al. [5]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21572373.v1
title: Dataset for fire and plant traits

description: Daset and code used in: Consistent physiological, ecological, and evolutionary effects of fire regime on conservative leaf economics strategies in plant communities published in Ecology Letters. DOI:
DOI: 10.6084/m9.figshare.21622718.v1
title: Additional file 13 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 13. List of eccDNA forming regions called using Illumina circularome sequencing data for A. thaliana leaf tissue published by Wang et al. [5]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622715.v1
title: Additional file 12 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 12. List of eccDNA forming regions called using Illumina circularome sequencing data for A. thaliana epi12 mutant tissue published by Lanciano et al. [6]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622712.v1
title: Additional file 11 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 11. List of eccDNA forming regions called using Illumina circularome sequencing data for A. thaliana wild type tissue published by Lanciano et al. [6]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21622709.v1
title: Additional file 10 of The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

description: Additional file 10. List of eccDNA forming regions called using Illumina circularome sequencing data for O. sativa callus tissue published by Lanciano et al. [6]. The first column describes the sample the eccDNA was called with, the next three columns represent the genomic coordinates of the eccDNA forming region, and the last column represents the number of junction split reads used to call the eccDNA forming region.
DOI: 10.6084/m9.figshare.21572373.v2
title: Dataset for fire and plant traits

description: Daset and code used in: Consistent physiological, ecological, and evolutionary effects of fire regime on conservative leaf economics strategies in plant communities published in Ecology Letters. DOI:
DOI: 10.6084/m9.figshare.21622656.v1
title: Additional file 1 of Daytime fluctuations of endurance performance in young soccer players: a randomized cross-over trial

description: Additional file 1. Exercise data of soccer players.
DOI: 10.6084/m9.figshare.21622608.v1
title: Additional file 9 of Folate regulates RNA m5C modification and translation in neural stem cells

description: Additional file 9. Source codes used to generate figures.
DOI: 10.6084/m9.figshare.21622599.v1
title: Additional file 7 of Folate regulates RNA m5C modification and translation in neural stem cells

description: Additional file 7. Combined raw data, with each figure on a spreadsheet.
DOI: 10.6084/m9.figshare.21622593.v1
title: Additional file 6 of Folate regulates RNA m5C modification and translation in neural stem cells

description: Additional file 6: Table 5. List of high-confidence m5C sites in mouse NSCs.
DOI: 10.6084/m9.figshare.21622587.v1
title: Additional file 5 of Folate regulates RNA m5C modification and translation in neural stem cells

description: Additional file 5: Table 4. List of differentially translated genes.
DOI: 10.6084/m9.figshare.21622584.v1
title: Additional file 4 of Folate regulates RNA m5C modification and translation in neural stem cells

description: Additional file 4: Table 3. List of differentially expressed genes.
DOI: 10.6084/m9.figshare.21622581.v1
title: Additional file 3 of Folate regulates RNA m5C modification and translation in neural stem cells

description: Additional file 3: Table 2. RNA expression level of total and polysome mRNA-seq libraries.
DOI: 10.6084/m9.figshare.21622578.v1
title: Additional file 2 of Folate regulates RNA m5C modification and translation in neural stem cells

description: Additional file 2: Table 1. Library statistics.
DOI: 10.6084/m9.figshare.21622497.v1
title: Additional file 1 of Bifidobacterium animalis subsp. lactis Probio-M8 undergoes host adaptive evolution by glcU mutation and translocates to the infant’s gut via oral-/entero-mammary routes through lactation

description: Additional file 1: Supplementary Table 1. Information of 11 healthy mother-infant pairs and sample collection. Supplementary Table 2. Genome information of 24 isolates recovered from M8 dry powder. Supplementary Table 3. Genome information of Bifidobacterium animalis subsp. lactis recovered from mother-infant pairs. Supplementary Table 4. Information of metagenome-assembled Bifidobacterium animalis subsp. lactis genomes. Supplementary Table 5. Information of single nucleotide polymorphisms (SNPs) identified in 195 homologous isolates of M8 recovered from mother-infant pairs. Supplementary Table 6. Information of single nucleotide polymorphisms (SNPs) in the glcU gene. Supplementary Table 7. Information of metagenomic data of maternal and infant fecal samples.
DOI: 10.6084/m9.figshare.21622457.v1
title: Additional file 4 of Is the cholesterol-perfluoroalkyl substance association confounded by dietary fiber intake?: a Bayesian analysis of NHANES data with adjustment for measurement error in fiber intake

description: Additional file 4.
DOI: 10.6084/m9.figshare.21622451.v1
title: Additional file 2 of Is the cholesterol-perfluoroalkyl substance association confounded by dietary fiber intake?: a Bayesian analysis of NHANES data with adjustment for measurement error in fiber intake

description: Additional file 2.
DOI: 10.6084/m9.figshare.21622448.v1
title: Additional file 1 of Is the cholesterol-perfluoroalkyl substance association confounded by dietary fiber intake?: a Bayesian analysis of NHANES data with adjustment for measurement error in fiber intake

description: Additional file 1.
DOI: 10.6084/m9.figshare.21622398.v1
title: Additional file 2 of Metabolic engineering of Clostridium autoethanogenum for ethyl acetate production from CO

description: Additional file 2: zip. GenBank files of plasmids used in this study, including: ppta-acka-atf1.gb, ppta-acka-eat1.gb, ppta-acka-treat1.gb, precas1-ald.gb, pthl-atf1.gb, SIBR-Cas pta.gb.
DOI: 10.5281/zenodo.7129155
title: Code & Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"

description: This entry contains code and data that was used in the publication: "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals" submitted in Publications journal. *It was version 2 when we added Fig_3_Tab2_Defining_science_disciplines_plus_plot.R script to version 1. *It was version 3 because we added script that calculates median and mean values of the stringency levels to version 2 data. *Latest version is version 4: we added supplementary data. #IDEA: This project was about analyzing policies of two thousand journals within the framework of eight TOP standards: <br> data citation, transparency of data, material, code and design and analysis, replication, plan and study pre-registration, <br> and two effective interventions: “Registered reports” and “Open science badges”. # MATERIALS & METHODS<br> We downloaded the TOP Factor (v33, 2022-08-29 3:12 PM) metric from the https://osf.io/kgnva/files/osfstorage/5e13502257341901c3805317 <br> website and analyzed its content with an in-house R script (in this repo):<br> 1) SCRIPT: fig1_Analyzing_journals_policies_and_TOP_guidelines.R<br> 2) SCRIPT: Figure2a_b_TOP_impl_journal_statistist_0_1_piechart_barplot.R<br> In order to get statistics about implementation of the TOP guidelines across discipline-specific journals, <br> we extracted information about journal’s disciplines from the Scopus content database. <br> We downloaded SCOPUS content coverage from the https://www.elsevier.com/solutions/scopus/how-scopus-works/content?dgcid=RN_AGCM_Sourced_300005030 (existJuly2022.xlsx)<br> and used the first Sheet.<br> We identified match between those 2 tables: <br> 3) SCRIPT: Rscript_overlapping_TOP_dataframe_and_SCOPUS_db.R<br> And resulted in Overlap_SCOPUS_TOP.rds file<br> And performed visualization and statistics:<br> 4) SCRIPT: Fig_3_Tab2_Defining_science_disciplines_plus_plot.R #RESULTS Submitted to Publications 30.9.2022. Reviewed 2.11.2022. Latest version: 25.11.2022.
DOI: 10.5281/zenodo.7129156
title: Code & Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"

description: This entry contains code and data that was used in the publication: "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals" submitted in Publications journal. #IDEA: This project was about analyzing policies of two thousand journals within the framework of eight TOP standards: <br> data citation, transparency of data, material, code and design and analysis, replication, plan and study pre-registration, <br> and two effective interventions: “Registered reports” and “Open science badges”. # MATERIALS & METHODS<br> We downloaded the TOP Factor (v33, 2022-08-29 3:12 PM) metric from the https://osf.io/kgnva/files/osfstorage/5e13502257341901c3805317 <br> website and analyzed its content with an in-house R script (in this repo):<br> 1) SCRIPT: fig1_Analyzing_journals_policies_and_TOP_guidelines.R<br> 2) SCRIPT: Figure2a_b_TOP_impl_journal_statistist_0_1_piechart_barplot.R<br> In order to get statistics about implementation of the TOP guidelines across discipline-specific journals, <br> we extracted information about journal’s disciplines from the Scopus content database. <br> We downloaded SCOPUS content coverage from the https://www.elsevier.com/solutions/scopus/how-scopus-works/content?dgcid=RN_AGCM_Sourced_300005030 (existJuly2022.xlsx)<br> and used the first Sheet.<br> We identified match between those 2 tables: <br> 3) SCRIPT: Rscript_overlapping_TOP_dataframe_and_SCOPUS_db.R<br> And resulted in Overlap_SCOPUS_TOP.rds file<br> And performed visualization and statistics:<br> 4) SCRIPT: Fig_3_Tab2_Defining_science_disciplines_plus_plot.R #RESULTS Submitted to Publications 30.9.2022.
DOI: 10.5281/zenodo.7129250
title: Code & Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"

description: This entry contains code and data that was used in the publication: "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals" submitted in Publications journal. *It is version 2 because the last verion of the Fig_3_Tab2_Defining_science_disciplines_plus_plot.R script and Supplementary Data were additionally uploaded. #IDEA: This project was about analyzing policies of two thousand journals within the framework of eight TOP standards: <br> data citation, transparency of data, material, code and design and analysis, replication, plan and study pre-registration, <br> and two effective interventions: “Registered reports” and “Open science badges”. # MATERIALS & METHODS<br> We downloaded the TOP Factor (v33, 2022-08-29 3:12 PM) metric from the https://osf.io/kgnva/files/osfstorage/5e13502257341901c3805317 <br> website and analyzed its content with an in-house R script (in this repo):<br> 1) SCRIPT: fig1_Analyzing_journals_policies_and_TOP_guidelines.R<br> 2) SCRIPT: Figure2a_b_TOP_impl_journal_statistist_0_1_piechart_barplot.R<br> In order to get statistics about implementation of the TOP guidelines across discipline-specific journals, <br> we extracted information about journal’s disciplines from the Scopus content database. <br> We downloaded SCOPUS content coverage from the https://www.elsevier.com/solutions/scopus/how-scopus-works/content?dgcid=RN_AGCM_Sourced_300005030 (existJuly2022.xlsx)<br> and used the first Sheet.<br> We identified match between those 2 tables: <br> 3) SCRIPT: Rscript_overlapping_TOP_dataframe_and_SCOPUS_db.R<br> And resulted in Overlap_SCOPUS_TOP.rds file<br> And performed visualization and statistics:<br> 4) SCRIPT: Fig_3_Tab2_Defining_science_disciplines_plus_plot.R #RESULTS Submitted to Publications 30.9.2022.
DOI: 10.5281/zenodo.7275030
title: Code & Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"

description: This entry contains code and data that was used in the publication: "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals" submitted in Publications journal. *It is version 2 because the last verion of the Fig_3_Tab2_Defining_science_disciplines_plus_plot.R script and Supplementary Data were additionally uploaded. *It is version 3 because we added script that calculates median and mean values of the stringency levels. #IDEA: This project was about analyzing policies of two thousand journals within the framework of eight TOP standards: <br> data citation, transparency of data, material, code and design and analysis, replication, plan and study pre-registration, <br> and two effective interventions: “Registered reports” and “Open science badges”. # MATERIALS & METHODS<br> We downloaded the TOP Factor (v33, 2022-08-29 3:12 PM) metric from the https://osf.io/kgnva/files/osfstorage/5e13502257341901c3805317 <br> website and analyzed its content with an in-house R script (in this repo):<br> 1) SCRIPT: fig1_Analyzing_journals_policies_and_TOP_guidelines.R<br> 2) SCRIPT: Figure2a_b_TOP_impl_journal_statistist_0_1_piechart_barplot.R<br> In order to get statistics about implementation of the TOP guidelines across discipline-specific journals, <br> we extracted information about journal’s disciplines from the Scopus content database. <br> We downloaded SCOPUS content coverage from the https://www.elsevier.com/solutions/scopus/how-scopus-works/content?dgcid=RN_AGCM_Sourced_300005030 (existJuly2022.xlsx)<br> and used the first Sheet.<br> We identified match between those 2 tables: <br> 3) SCRIPT: Rscript_overlapping_TOP_dataframe_and_SCOPUS_db.R<br> And resulted in Overlap_SCOPUS_TOP.rds file<br> And performed visualization and statistics:<br> 4) SCRIPT: Fig_3_Tab2_Defining_science_disciplines_plus_plot.R #RESULTS Submitted to Publications 30.9.2022. Reviewed 2.11.2022.