cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.10049696.v1
title: MOESM3 of Exploring gene networks in two sunflower lines with contrasting leaf senescence phenotype using a system biology approach

description: Additional file 3: Table S1. Differentially expressed genes between post-anthesis vs. anthesis in the early and delayed senescence lines respectively.
DOI: 10.6084/m9.figshare.10049645
title: MOESM2 of Soil domestication by rice cultivation results in plant-soil feedback through shifts in soil microbiota

description: Additional file 2 : Table S1. Soil chemistry profiles from domesticated and uncultivated soils used in the domestication experiment. Table S2. Permanova statistics on Bray-Curtis dissimilarities of the soil domestication study. Table S3. Permanova statistics on weighted and unweighted unifrac dissimilarity metrics for soil domestication study. Table S4. Betadispersion estimates for the soil domestication study. Table S5. Results of testing for differential abundance in each compartment between domesticated and uncultivated soils. Table S6. Differentially abundant OTUs between Domesticated and Uncultivated soils. Table S7. Permanova statistics on Bray-Curtis dissimilarities for the native plants study. Table S8. Permanova on weighted and unweighted Unifrac dissimilarity metrics for the native plants study. Table S9. Tukey HSD results for testing dissimilarity metrics for the rhizosphere microbiome of each plant species to bulk soil. Rice show significantly less distance to bulk soil than other plant species. Table S10. Tests for differential abundance to rice microbiota for each compartment and each plant host species. Table S11. Taxa that belong to the rice core enriched and rice core depleted microbes. Table S12. Overlapping OTUs enriched in domesticated soil microbiota and rice core enriched microbiota. Table S13. Post hoc tests comparing seedling vigor traits between soil inoculum types. Table S14. Permanova statistics on Bray-Curtis dissimilarities from the seedling vigor experiments. Table S15. OTUs showing significant correlations with seedling height in Seedling Vigor Experiment 1.
DOI: 10.6084/m9.figshare.10049645.v1
title: MOESM2 of Soil domestication by rice cultivation results in plant-soil feedback through shifts in soil microbiota

description: Additional file 2 : Table S1. Soil chemistry profiles from domesticated and uncultivated soils used in the domestication experiment. Table S2. Permanova statistics on Bray-Curtis dissimilarities of the soil domestication study. Table S3. Permanova statistics on weighted and unweighted unifrac dissimilarity metrics for soil domestication study. Table S4. Betadispersion estimates for the soil domestication study. Table S5. Results of testing for differential abundance in each compartment between domesticated and uncultivated soils. Table S6. Differentially abundant OTUs between Domesticated and Uncultivated soils. Table S7. Permanova statistics on Bray-Curtis dissimilarities for the native plants study. Table S8. Permanova on weighted and unweighted Unifrac dissimilarity metrics for the native plants study. Table S9. Tukey HSD results for testing dissimilarity metrics for the rhizosphere microbiome of each plant species to bulk soil. Rice show significantly less distance to bulk soil than other plant species. Table S10. Tests for differential abundance to rice microbiota for each compartment and each plant host species. Table S11. Taxa that belong to the rice core enriched and rice core depleted microbes. Table S12. Overlapping OTUs enriched in domesticated soil microbiota and rice core enriched microbiota. Table S13. Post hoc tests comparing seedling vigor traits between soil inoculum types. Table S14. Permanova statistics on Bray-Curtis dissimilarities from the seedling vigor experiments. Table S15. OTUs showing significant correlations with seedling height in Seedling Vigor Experiment 1.
DOI: 10.6084/m9.figshare.10049606
title: MOESM6 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 6: Table S5. Complete list of bacterial COGs found within the pathway â carbohydrate transport and metabolismâ .
DOI: 10.6084/m9.figshare.10049597
title: MOESM5 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 5: Table S4. Complete list of results of Linear Discriminant Analysis (LDA) of bacterial dataset.
DOI: 10.6084/m9.figshare.10049597.v1
title: MOESM5 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 5: Table S4. Complete list of results of Linear Discriminant Analysis (LDA) of bacterial dataset.
DOI: 10.6084/m9.figshare.10049606.v1
title: MOESM6 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 6: Table S5. Complete list of bacterial COGs found within the pathway â carbohydrate transport and metabolismâ .
DOI: 10.6084/m9.figshare.10049588
title: MOESM4 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 4: Table S3. Transposase abundance in the bacterial dataset in the pathway â replication, recombination and repairâ .
DOI: 10.6084/m9.figshare.10049579
title: MOESM3 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 3: Table S2. Complete list of results of Linear Discriminant Analysis (LDA) of protist dataset.
DOI: 10.6084/m9.figshare.10049588.v1
title: MOESM4 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 4: Table S3. Transposase abundance in the bacterial dataset in the pathway â replication, recombination and repairâ .
DOI: 10.6084/m9.figshare.10049570
title: MOESM10 of An optimised CRISPR/Cas9 protocol to create targeted mutations in homoeologous genes and an efficient genotyping protocol to identify edited events in wheat

description: Additional file 10. Size (bp) of genotyping amplicons observed for each of the six wheat homoeologs of TaNFXL1 in the T1 progeny of plants transformed with a construct expressing Cas9 and two sgRNA. To be conservative with the naming of the edited alleles, amplicons varying by less than 5 bp in size were given the same name. See Table 4 for an explication of the genotype code. N/A in amplicon size columns and ? in the genotype code indicate results not available. Genotype for Fielder, the parent line for the transgenic plants, is highlighted in grey.
DOI: 10.6084/m9.figshare.10049579.v1
title: MOESM3 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 3: Table S2. Complete list of results of Linear Discriminant Analysis (LDA) of protist dataset.
DOI: 10.6084/m9.figshare.10049570.v1
title: MOESM10 of An optimised CRISPR/Cas9 protocol to create targeted mutations in homoeologous genes and an efficient genotyping protocol to identify edited events in wheat

description: Additional file 10. Size (bp) of genotyping amplicons observed for each of the six wheat homoeologs of TaNFXL1 in the T1 progeny of plants transformed with a construct expressing Cas9 and two sgRNA. To be conservative with the naming of the edited alleles, amplicons varying by less than 5 bp in size were given the same name. See Table 4 for an explication of the genotype code. N/A in amplicon size columns and ? in the genotype code indicate results not available. Genotype for Fielder, the parent line for the transgenic plants, is highlighted in grey.
DOI: 10.6084/m9.figshare.10049564
title: MOESM2 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 2: Table S1. Sample Overview. Number of sequences before and after quality filtering, as well as taxonomic and functional annotation statistics
DOI: 10.6084/m9.figshare.10049564.v1
title: MOESM2 of Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

description: Additional file 2: Table S1. Sample Overview. Number of sequences before and after quality filtering, as well as taxonomic and functional annotation statistics
DOI: 10.6084/m9.figshare.10049546
title: MOESM1 of Three myths about risk thresholds for prediction models

description: Additional file 1. Csv file containing the predicted probabilities of malignancy by the ADNEX model and the true outcomes (1 = malignant, 0 = benign).
DOI: 10.6084/m9.figshare.10049540
title: MOESM7 of Gene-based analysis of ADHD using PASCAL: a biological insight into the novel associated genes

description: Additional file 7. GWASPGCmalesadhdpvalor.sum.genescores.xls. For each file different columns are represented: chromosome, start-end positions, strand (+ or -) relative to transcription start, gene symbol (UCSC), numSNPs (number of SNPs employed to calculate the gene score), p-value calculated by PASCAL.
DOI: 10.6084/m9.figshare.10049537
title: MOESM6 of Gene-based analysis of ADHD using PASCAL: a biological insight into the novel associated genes

description: Additional file 6. GWASPGCfemalesadhdpvalor.sum.genescores.xls.
DOI: 10.6084/m9.figshare.10049540.v1
title: MOESM7 of Gene-based analysis of ADHD using PASCAL: a biological insight into the novel associated genes

description: Additional file 7. GWASPGCmalesadhdpvalor.sum.genescores.xls. For each file different columns are represented: chromosome, start-end positions, strand (+ or -) relative to transcription start, gene symbol (UCSC), numSNPs (number of SNPs employed to calculate the gene score), p-value calculated by PASCAL.
DOI: 10.6084/m9.figshare.10049546.v1
title: MOESM1 of Three myths about risk thresholds for prediction models

description: Additional file 1. Csv file containing the predicted probabilities of malignancy by the ADNEX model and the true outcomes (1 = malignant, 0 = benign).
DOI: 10.6084/m9.figshare.10049534
title: MOESM5 of Gene-based analysis of ADHD using PASCAL: a biological insight into the novel associated genes

description: Additional file 5. adhd_eur_jun2017.genebased.sum.genescores.xls.
DOI: 10.6084/m9.figshare.10049537.v1
title: MOESM6 of Gene-based analysis of ADHD using PASCAL: a biological insight into the novel associated genes

description: Additional file 6. GWASPGCfemalesadhdpvalor.sum.genescores.xls.
DOI: 10.6084/m9.figshare.10049519
title: MOESM3 of Comprehensive anatomic ontologies for lung development: A comparison of alveolar formation and maturation within mouse and human lung

description: Additional file 3.. Comparison of ontology terms for human and mouse lung anatomy.
DOI: 10.6084/m9.figshare.10049534.v1
title: MOESM5 of Gene-based analysis of ADHD using PASCAL: a biological insight into the novel associated genes

description: Additional file 5. adhd_eur_jun2017.genebased.sum.genescores.xls.
DOI: 10.6084/m9.figshare.10049519.v1
title: MOESM3 of Comprehensive anatomic ontologies for lung development: A comparison of alveolar formation and maturation within mouse and human lung

description: Additional file 3.. Comparison of ontology terms for human and mouse lung anatomy.
DOI: 10.6084/m9.figshare.10049495
title: MOESM9 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 9: Table S9. Summary of CpG-based DMGs between diffuse SSc and limited SSc.
DOI: 10.6084/m9.figshare.10049489
title: MOESM8 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 8: Table S8. Summary of CpG-based DMGs between limited SSc and controls.
DOI: 10.6084/m9.figshare.10049495.v1
title: MOESM9 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 9: Table S9. Summary of CpG-based DMGs between diffuse SSc and limited SSc.
DOI: 10.6084/m9.figshare.10049489.v1
title: MOESM8 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 8: Table S8. Summary of CpG-based DMGs between limited SSc and controls.
DOI: 10.6084/m9.figshare.10049480
title: MOESM7 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 7: Table S7. Summary of CpG-based DMGs between diffuse SSc and controls.
DOI: 10.6084/m9.figshare.10049471
title: MOESM6 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 6: Table S6. Summary of CHH-based DMGs adjusted for sex effect.
DOI: 10.6084/m9.figshare.10049480.v1
title: MOESM7 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 7: Table S7. Summary of CpG-based DMGs between diffuse SSc and controls.
DOI: 10.6084/m9.figshare.10049456
title: MOESM3 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 3: Table S3. Summary of CHH-based DMGs.
DOI: 10.6084/m9.figshare.10049462
title: MOESM4 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 4: Table S4. Summary of CpG-based DMGs adjusted for sex effect.
DOI: 10.6084/m9.figshare.10049465
title: MOESM5 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 5: Table S5. Summary of CHG-based DMGs adjusted for sex effect.
DOI: 10.6084/m9.figshare.10049465.v1
title: MOESM5 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 5: Table S5. Summary of CHG-based DMGs adjusted for sex effect.
DOI: 10.6084/m9.figshare.10049471.v1
title: MOESM6 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 6: Table S6. Summary of CHH-based DMGs adjusted for sex effect.
DOI: 10.6084/m9.figshare.10049450
title: MOESM2 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 2: Table S2. Summary of CHG-based DMGs.
DOI: 10.6084/m9.figshare.10049456.v1
title: MOESM3 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 3: Table S3. Summary of CHH-based DMGs.
DOI: 10.6084/m9.figshare.10049462.v1
title: MOESM4 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 4: Table S4. Summary of CpG-based DMGs adjusted for sex effect.
DOI: 10.6084/m9.figshare.10049432
title: MOESM18 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 18: Supplementary Information. Quality control report of de-identified samples.
DOI: 10.6084/m9.figshare.10049450.v1
title: MOESM2 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 2: Table S2. Summary of CHG-based DMGs.
DOI: 10.6084/m9.figshare.10049441
title: MOESM1 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 1: Table S1. Summary of CpG-based DMGs.
DOI: 10.6084/m9.figshare.10049432.v1
title: MOESM18 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 18: Supplementary Information. Quality control report of de-identified samples.
DOI: 10.6084/m9.figshare.10049441.v1
title: MOESM1 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 1: Table S1. Summary of CpG-based DMGs.
DOI: 10.6084/m9.figshare.10049411
title: MOESM15 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 15: Table S15. Summary of CHH-based DMGs between diffuse SSc and limited SSc.
DOI: 10.6084/m9.figshare.10049417
title: MOESM16 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 16: Table S16. Summary of SNP-CpG associations.
DOI: 10.6084/m9.figshare.10049411.v1
title: MOESM15 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 15: Table S15. Summary of CHH-based DMGs between diffuse SSc and limited SSc.
DOI: 10.6084/m9.figshare.10049417.v1
title: MOESM16 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 16: Table S16. Summary of SNP-CpG associations.
DOI: 10.6084/m9.figshare.10049405
title: MOESM14 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 14: Table S14. Summary of CHH-based DMGs between limited SSc and controls.
DOI: 10.6084/m9.figshare.10049396
title: MOESM13 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 13: Table S13. Summary of CHH-based DMGs between diffuse SSc and controls.
DOI: 10.6084/m9.figshare.10049405.v1
title: MOESM14 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 14: Table S14. Summary of CHH-based DMGs between limited SSc and controls.
DOI: 10.6084/m9.figshare.10049390
title: MOESM12 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 12: Table S12. Summary of CHG-based DMGs between diffuse SSc and limited SSc.
DOI: 10.6084/m9.figshare.10049396.v1
title: MOESM13 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 13: Table S13. Summary of CHH-based DMGs between diffuse SSc and controls.
DOI: 10.6084/m9.figshare.10049390.v1
title: MOESM12 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 12: Table S12. Summary of CHG-based DMGs between diffuse SSc and limited SSc.
DOI: 10.6084/m9.figshare.10049381
title: MOESM11 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 11: Table S11. Summary of CHG-based DMGs between limited SSc and controls.
DOI: 10.6084/m9.figshare.10049384
title: MOESM2 of Genome wide survey, evolution and expression analysis of PHD finger genes reveal their diverse roles during the development and abiotic stress responses in Brassica rapa L.

description: Additional file 2: Table S1. List of 145 B. rapa PHD finger protein genes, and their related informations. Table S2. List of 16 suspected B. rapa PHD finger proteins. Table S3. Summary of gene ontology terms of 98 A. thaliana PHD finger protein genes (retrieved from TAIR database, https://www.arabidopsis.org/index.jsp) in relation to the phylogenetic classification of their encoded proteins along with the 145 B. rapa PHD finger proteins in Fig.Â 2. Table S4. Classification of145 B. rapa PHD domain-containing proteins based on the presence or not and organization of additional domainÂ (s). Table S5. Synteny relationships between Arabidopsis and B.rapa PHD finger protein genes. Table S6. The information of primers used in the quantitative real-time PCR (qRT-PCR) analysis.
DOI: 10.6084/m9.figshare.10049372
title: MOESM10 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 10: Table S10. Summary of CHG-based DMGs between diffuse SSc and controls. (XLS 32 kb)
DOI: 10.6084/m9.figshare.10049381.v1
title: MOESM11 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 11: Table S11. Summary of CHG-based DMGs between limited SSc and controls.
DOI: 10.6084/m9.figshare.10049372.v1
title: MOESM10 of Whole-genome bisulfite sequencing in systemic sclerosis provides novel targets to understand disease pathogenesis

description: Additional file 10: Table S10. Summary of CHG-based DMGs between diffuse SSc and controls. (XLS 32 kb)
DOI: 10.6084/m9.figshare.10049384.v1
title: MOESM2 of Genome wide survey, evolution and expression analysis of PHD finger genes reveal their diverse roles during the development and abiotic stress responses in Brassica rapa L.

description: Additional file 2: Table S1. List of 145 B. rapa PHD finger protein genes, and their related informations. Table S2. List of 16 suspected B. rapa PHD finger proteins. Table S3. Summary of gene ontology terms of 98 A. thaliana PHD finger protein genes (retrieved from TAIR database, https://www.arabidopsis.org/index.jsp) in relation to the phylogenetic classification of their encoded proteins along with the 145 B. rapa PHD finger proteins in Fig.Â 2. Table S4. Classification of145 B. rapa PHD domain-containing proteins based on the presence or not and organization of additional domainÂ (s). Table S5. Synteny relationships between Arabidopsis and B.rapa PHD finger protein genes. Table S6. The information of primers used in the quantitative real-time PCR (qRT-PCR) analysis.
DOI: 10.6084/m9.figshare.10049336
title: MOESM2 of What is the nature and extent of evidence on methodologies for monitoring and evaluating marine spatial management measures in UK and similar coastal waters? A systematic map protocol

description: Additional file 2. ROSES for Systematic Map Protocols. Version 1.0.
DOI: 10.6084/m9.figshare.10049327
title: MOESM1 of What is the nature and extent of evidence on methodologies for monitoring and evaluating marine spatial management measures in UK and similar coastal waters? A systematic map protocol

description: Additional file 1. Data coding framework. Proposed data coding framework detailing information to be extracted or coded from relevant studies in the final systematic map database (information in the ‘Meta-data and codes’ tab will form drop-down lists in the final map spreadsheet) together with detailed explanations for each column data will be extracted/coded (‘Coding descriptors’ tab). To demonstrate the data coding framework in use, fifteen articles used as a benchmark to scope the search string (Additional file 3: Table S3) have been coded (‘Systematic map database’ and ‘Secondary studies database’ tabs).
DOI: 10.6084/m9.figshare.10049336.v1
title: MOESM2 of What is the nature and extent of evidence on methodologies for monitoring and evaluating marine spatial management measures in UK and similar coastal waters? A systematic map protocol

description: Additional file 2. ROSES for Systematic Map Protocols. Version 1.0.