cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.10094114
title: MOESM4 of Fingerprinting cities: differentiating subway microbiome functionality

description: Additional file 4. The microbiome functional signatures of city subway systems.
DOI: 10.6084/m9.figshare.10094114.v1
title: MOESM4 of Fingerprinting cities: differentiating subway microbiome functionality

description: Additional file 4. The microbiome functional signatures of city subway systems.
DOI: 10.6084/m9.figshare.10093667
title: Shared data for JGR(2019)

description: This is a compressed package including WRF simulation data, Automatic weather station data and Radar observation data.
DOI: 10.6084/m9.figshare.10093676
title: Dateset for 'spontaneous imbibition in porous media: verification of a dynamic pore-network model against VOF (volume of fluid)-based direct numerical simulations'

description: The dataset includes the following four items:1. Ansys fluent output file for VOF modeling of spontaneous imbibition with the contact angle of 60 degrees in the attachment of 'fluent.out'.2. 8-bit CT data of the sintered glass beads in the attachment of 'ct data.raw'.3. Pore-network data in the attachment of 'pore network data.zip'.4. Key model output files in the attachment of 'model output data.zip'.
DOI: 10.6084/m9.figshare.10093667.v1
title: Shared data for JGR(2019)

description: This is a compressed package including WRF simulation data, Automatic weather station data and Radar observation data.
DOI: 10.6084/m9.figshare.10093616
title: 5prime_mouse

description: 5prime
DOI: 10.6084/m9.figshare.10093616.v1
title: 5prime_mouse

description: 5prime
DOI: 10.6084/m9.figshare.10093544
title: Patterns of regional endemism among New Zealand invertebrates

description: Biodiversity is unevenly distributed worldwide in terms of both species diversity and species endemism. Although centres of endemism are a conservation priority, both patterns and drivers of endemism are poorly understood in New Zealand. Here we explore whether invertebrate species distribution records in New Zealand represent the complete geographic range of species. We use distribution records of 2,322 invertebrate species to survey variation in range size and regional-endemism among 28 New Zealand regions, and explore the correlates of diversity and regional-endemism. Our data suggest patterns of regional-endemism in New Zealand invertebrates are not artefacts of sampling effort and the majority of species are not widespread. We found that endemism-score (which is a measure that corrects for species diversity) correlates positively with the relative size of the region three million years ago. Five variables (and their interactions) contributed to the relative level of invertebrate species endemism within a region (in a generalised linear model). Level of endemism tends to be lower in regions with greater geographic connectivity. This suggests that high levels of regional-endemism are not simply the product of the accumulation of species over time, but depends on the ability of a region to retain local species.
DOI: 10.6084/m9.figshare.10093544.v1
title: Patterns of regional endemism among New Zealand invertebrates

description: Biodiversity is unevenly distributed worldwide in terms of both species diversity and species endemism. Although centres of endemism are a conservation priority, both patterns and drivers of endemism are poorly understood in New Zealand. Here we explore whether invertebrate species distribution records in New Zealand represent the complete geographic range of species. We use distribution records of 2,322 invertebrate species to survey variation in range size and regional-endemism among 28 New Zealand regions, and explore the correlates of diversity and regional-endemism. Our data suggest patterns of regional-endemism in New Zealand invertebrates are not artefacts of sampling effort and the majority of species are not widespread. We found that endemism-score (which is a measure that corrects for species diversity) correlates positively with the relative size of the region three million years ago. Five variables (and their interactions) contributed to the relative level of invertebrate species endemism within a region (in a generalised linear model). Level of endemism tends to be lower in regions with greater geographic connectivity. This suggests that high levels of regional-endemism are not simply the product of the accumulation of species over time, but depends on the ability of a region to retain local species.
DOI: 10.6084/m9.figshare.10093460
title: Identifying and characterizing extrapolation in multivariateresponse data

description: Inland lake data from the LAGOS-NE database. Multi-scale covariates available for ~8,000 lakes with observed and unobserved water quality response variables. <br>Lake data used for identifying and characterizing extrapolation in multivariate response data. Analyzed as part of PLOS One manuscript. Also available are output data with extrapolation index values and CART model fit with data.
DOI: 10.6084/m9.figshare.10093535
title: hgcA-in-silico-primer-stats

description: Results from in silico PCR of hgcA universal and clade specific primers with 0 and 2 mismatches run for each set
DOI: 10.6084/m9.figshare.10093409
title: Dual use and Peercrowd

description: The dataset includes the variables used in our paper on dual tobacco use among young adult peer crowds.<br>
DOI: 10.6084/m9.figshare.10093460.v1
title: Identifying and characterizing extrapolation in multivariateresponse data

description: Inland lake data from the LAGOS-NE database. Multi-scale covariates available for ~8,000 lakes with observed and unobserved water quality response variables. <br>Lake data used for identifying and characterizing extrapolation in multivariate response data. Analyzed as part of PLOS One manuscript. Also available are output data with extrapolation index values and CART model fit with data.
DOI: 10.6084/m9.figshare.10087295
title: Multiple_sclerosis.sav

description: The study investigated the contribution of clinical aspects of multiple sclerosis and personality to multiple sclerosis fatigue. A total of 201 participants with multiple sclerosis took part in this online study, by filling questionnaires that measured clinical features of a disease, temperament and character dimensions, and MS-related fatigue. Sociodemographic variables and depression have been controlled.
DOI: 10.6084/m9.figshare.10087295.v2
title: Multiple_sclerosis.sav

description: The study investigated the contribution of clinical aspects of multiple sclerosis and personality to multiple sclerosis fatigue. A total of 201 participants with multiple sclerosis took part in this online study, by filling questionnaires that measured clinical features of a disease, temperament and character dimensions, and MS-related fatigue. Sociodemographic variables and depression have been controlled.
DOI: 10.6084/m9.figshare.10087295.v1
title: Multiple_sclerosis.sav

description: The study investigated the contribution of clinical aspects of multiple sclerosis and personality to multiple sclerosis fatigue. A total of 201 participants with multiple sclerosis took paet in this online study, by filling questionnaires that measured clinical features of a disease, personality traits, and MS-related fatigue. Sociodemographic variables and depression have been controlled.
DOI: 10.6084/m9.figshare.10087238
title: MOESM9 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 9: Table S5. Predictive accuracy across simulated populations for select models.
DOI: 10.6084/m9.figshare.10087229
title: MOESM8 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 8: Table S4. Bias with respect to the median for all models and simulated populations.
DOI: 10.6084/m9.figshare.10087220
title: MOESM7 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 7: Table S3. Bias with respect to the mean for all models and simulated populations.
DOI: 10.6084/m9.figshare.10087229.v1
title: MOESM8 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 8: Table S4. Bias with respect to the median for all models and simulated populations.
DOI: 10.6084/m9.figshare.10087211
title: MOESM6 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 6: Table S2. Observed risk parameter coverage rate for all models and simulated populations.
DOI: 10.6084/m9.figshare.10087220.v1
title: MOESM7 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 7: Table S3. Bias with respect to the mean for all models and simulated populations.
DOI: 10.6084/m9.figshare.10087199
title: MOESM2 of Impact of merging commercial breeding lines on the genetic diversity of Landrace pigs

description: Additional file 2: Table S1. Outlier SNPs identified (q-value ≤ 0.05) by BayeScan in the pairwise comparison between the current TN and the six former lines. SNP ID, SNP identifier; Chromosome, chromosome number; Position, position on the chromosome; prob, posterior probabilities; log10(PO), the logarithm to 10 of Posterior Odds; qval, q-value the threshold for significance of signatures of selection; alpha, a locus-specific component indicating the strength and direction of selection, a positive value of alpha suggests diversifying selection, whereas negative values suggest balancing or purifying selection; fst, fixation index; RS ID, accession number of the SNP; Gene Name (5 kb upstream/downstream), name of a gene that is located within 10 kb (5 kb downstream/upstream) of the SNP outlier; GO BP (GO-slim), Gene Ontology slim biological process term; General Term GO BP, general Gene Ontology biological process term.
DOI: 10.6084/m9.figshare.10087202
title: MOESM5 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 5: Table S1. Observed type-I error rate for all models and simulated populations.
DOI: 10.6084/m9.figshare.10087211.v1
title: MOESM6 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 6: Table S2. Observed risk parameter coverage rate for all models and simulated populations.
DOI: 10.6084/m9.figshare.10087199.v1
title: MOESM2 of Impact of merging commercial breeding lines on the genetic diversity of Landrace pigs

description: Additional file 2: Table S1. Outlier SNPs identified (q-value ≤ 0.05) by BayeScan in the pairwise comparison between the current TN and the six former lines. SNP ID, SNP identifier; Chromosome, chromosome number; Position, position on the chromosome; prob, posterior probabilities; log10(PO), the logarithm to 10 of Posterior Odds; qval, q-value the threshold for significance of signatures of selection; alpha, a locus-specific component indicating the strength and direction of selection, a positive value of alpha suggests diversifying selection, whereas negative values suggest balancing or purifying selection; fst, fixation index; RS ID, accession number of the SNP; Gene Name (5 kb upstream/downstream), name of a gene that is located within 10 kb (5 kb downstream/upstream) of the SNP outlier; GO BP (GO-slim), Gene Ontology slim biological process term; General Term GO BP, general Gene Ontology biological process term.
DOI: 10.6084/m9.figshare.10087202.v1
title: MOESM5 of Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study

description: Additional file 5: Table S1. Observed type-I error rate for all models and simulated populations.
DOI: 10.6084/m9.figshare.10087169
title: MOESM4 of Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid

description: Additional file 4: Table S3. Effects of ATRA on cardiolipin amounts in genetically engineered breast cancer MDA-MB-453 and SK-BR-3 cells.
DOI: 10.6084/m9.figshare.10087163
title: MOESM3 of Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid

description: Additional file 3: Table S2. Effects of ATRA on cardiolipin amounts in SK-BR-3 cells.
DOI: 10.6084/m9.figshare.10087157
title: MOESM2 of Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid

description: Additional file 2: Table S1. Lipidomics raw data, Highthroughput lipid ID.
DOI: 10.6084/m9.figshare.10087169.v1
title: MOESM4 of Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid

description: Additional file 4: Table S3. Effects of ATRA on cardiolipin amounts in genetically engineered breast cancer MDA-MB-453 and SK-BR-3 cells.
DOI: 10.6084/m9.figshare.10087163.v1
title: MOESM3 of Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid

description: Additional file 3: Table S2. Effects of ATRA on cardiolipin amounts in SK-BR-3 cells.
DOI: 10.6084/m9.figshare.10087157.v1
title: MOESM2 of Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid

description: Additional file 2: Table S1. Lipidomics raw data, Highthroughput lipid ID.
DOI: 10.6084/m9.figshare.10087142
title: MOESM6 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 6: Table S5. Mean mutational load of common and rare nonsynonymous variants per subject in subjects with haplogroup J and K as compared to other haplogroups.
DOI: 10.6084/m9.figshare.10087136
title: MOESM5 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 5: Table S4. Mean mutational load of common and rare nonsynonymous functional variants per subject in Finnish athletes and controls.
DOI: 10.6084/m9.figshare.10087127
title: MOESM4 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 4: Table S3. A list of rare rRNA functional variants in Finnish athletes and controls.
DOI: 10.6084/m9.figshare.10087142.v1
title: MOESM6 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 6: Table S5. Mean mutational load of common and rare nonsynonymous variants per subject in subjects with haplogroup J and K as compared to other haplogroups.
DOI: 10.6084/m9.figshare.10087136.v1
title: MOESM5 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 5: Table S4. Mean mutational load of common and rare nonsynonymous functional variants per subject in Finnish athletes and controls.
DOI: 10.6084/m9.figshare.10087124
title: MOESM3 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 3: Table S2. A list of rare tRNA functional variants in Finnish athletes and controls.
DOI: 10.6084/m9.figshare.10087127.v1
title: MOESM4 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 4: Table S3. A list of rare rRNA functional variants in Finnish athletes and controls.
DOI: 10.6084/m9.figshare.10087115
title: MOESM2 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 2: Table S1. A list of rare nonsynonymous functional variants in Finnish athletes and controls.
DOI: 10.6084/m9.figshare.10087124.v1
title: MOESM3 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 3: Table S2. A list of rare tRNA functional variants in Finnish athletes and controls.
DOI: 10.6084/m9.figshare.10087115.v1
title: MOESM2 of Analysis of functional variants in mitochondrial DNA of Finnish athletes

description: Additional file 2: Table S1. A list of rare nonsynonymous functional variants in Finnish athletes and controls.
DOI: 10.6084/m9.figshare.10087076
title: MOESM6 of Radio-detoxified LPS alters bone marrow-derived extracellular vesicles and endothelial progenitor cells

description: Additional file 6. Detailed results of the enrichment analysis. Output from the g:Profiler enrichment analysis for the three main Gene Ontology categories (Biological Process, Cellular Component, Molecular function).
DOI: 10.6084/m9.figshare.10087070
title: MOESM5 of Radio-detoxified LPS alters bone marrow-derived extracellular vesicles and endothelial progenitor cells

description: Additional file 5 List of small extracellular vesicle proteins identified by LC-MS/MS in BM-derived cells. List of proteins identified by LC-MS/MS are given in separate sheets. Sheet ‘PBS’ shows the result of measurement on controls (n=7); the results of the treated group (n=9) are listed on sheet ‘RD-LPS’.
DOI: 10.6084/m9.figshare.10087073
title: MOESM2 of Validation and reproducibility of a new iodine specific food frequency questionnaire for assessing iodine intake in Norwegian pregnant women

description: Additional file 2: Table S2. Iodine content in food items used for calculation of iodine intake from the I-FFQ. Table S3. Iodine content in food items used for calculation of iodine intake from the food diary.
DOI: 10.6084/m9.figshare.10087076.v1
title: MOESM6 of Radio-detoxified LPS alters bone marrow-derived extracellular vesicles and endothelial progenitor cells

description: Additional file 6. Detailed results of the enrichment analysis. Output from the g:Profiler enrichment analysis for the three main Gene Ontology categories (Biological Process, Cellular Component, Molecular function).
DOI: 10.6084/m9.figshare.10087073.v1
title: MOESM2 of Validation and reproducibility of a new iodine specific food frequency questionnaire for assessing iodine intake in Norwegian pregnant women

description: Additional file 2: Table S2. Iodine content in food items used for calculation of iodine intake from the I-FFQ. Table S3. Iodine content in food items used for calculation of iodine intake from the food diary.
DOI: 10.6084/m9.figshare.10087070.v1
title: MOESM5 of Radio-detoxified LPS alters bone marrow-derived extracellular vesicles and endothelial progenitor cells

description: Additional file 5 List of small extracellular vesicle proteins identified by LC-MS/MS in BM-derived cells. List of proteins identified by LC-MS/MS are given in separate sheets. Sheet ‘PBS’ shows the result of measurement on controls (n=7); the results of the treated group (n=9) are listed on sheet ‘RD-LPS’.
DOI: 10.6084/m9.figshare.10087058
title: MOESM1 of Trans-arterial embolization of malignant tumor-related gastrointestinal bleeding: technical and clinical efficacy

description: Additional file 1. Demographics, angiographic, procedural, post-procedural follow-up data for each patient.
DOI: 10.6084/m9.figshare.10087058.v1
title: MOESM1 of Trans-arterial embolization of malignant tumor-related gastrointestinal bleeding: technical and clinical efficacy

description: Additional file 1. Demographics, angiographic, procedural, post-procedural follow-up data for each patient.
DOI: 10.6084/m9.figshare.10087043
title: MOESM1 of Thyroid dysfunction in preterm infants born before 32 gestational weeks

description: Additional file 1. The raw data set including demographics and all results of serial thyroid function tests of the study population.
DOI: 10.6084/m9.figshare.10087043.v1
title: MOESM1 of Thyroid dysfunction in preterm infants born before 32 gestational weeks

description: Additional file 1. The raw data set including demographics and all results of serial thyroid function tests of the study population.
DOI: 10.6084/m9.figshare.10086950
title: MOESM9 of Connecting the dots between different networks: miRNAs associated with bladder cancer risk and progression

description: Additional file 9: Table S9. NGS sequencing data for bladder cancer.
DOI: 10.6084/m9.figshare.10086950.v1
title: MOESM9 of Connecting the dots between different networks: miRNAs associated with bladder cancer risk and progression

description: Additional file 9: Table S9. NGS sequencing data for bladder cancer.
DOI: 10.6084/m9.figshare.10086938
title: MOESM9 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 9: Table S6. GO classification of the biological processes.
DOI: 10.6084/m9.figshare.10086926
title: MOESM7 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 7: Table S4. The identified homologous transcripts between C. breviculmis and rice.
DOI: 10.6084/m9.figshare.10086938.v1
title: MOESM9 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 9: Table S6. GO classification of the biological processes.
DOI: 10.6084/m9.figshare.10086923
title: MOESM9 of Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-â omics analysis

description: Additional file 9 Complete GO Analysis for 90th percentile outliers. We only make use of Biological Process and FDR &lt; 0.01, but many other categories are included with this analysis. Tabs include All 9 (3 selection features * 3 cell phases), G1, S and G2/M.
DOI: 10.6084/m9.figshare.10086926.v1
title: MOESM7 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 7: Table S4. The identified homologous transcripts between C. breviculmis and rice.
DOI: 10.6084/m9.figshare.10086920
title: MOESM6 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 6: Table S3. Prediction results of the target mRNAs for lncRNAs.
DOI: 10.6084/m9.figshare.10086911
title: MOESM5 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 5: Table S2. Summary of the lncRNAs.
DOI: 10.6084/m9.figshare.10086920.v1
title: MOESM6 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 6: Table S3. Prediction results of the target mRNAs for lncRNAs.
DOI: 10.6084/m9.figshare.10086923.v1
title: MOESM9 of Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-â omics analysis

description: Additional file 9 Complete GO Analysis for 90th percentile outliers. We only make use of Biological Process and FDR &lt; 0.01, but many other categories are included with this analysis. Tabs include All 9 (3 selection features * 3 cell phases), G1, S and G2/M.
DOI: 10.6084/m9.figshare.10086911.v1
title: MOESM5 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 5: Table S2. Summary of the lncRNAs.
DOI: 10.6084/m9.figshare.10086902
title: MOESM4 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 4: Table S1. Summary of the candidate alternative splice (AS) events.
DOI: 10.6084/m9.figshare.10086902.v1
title: MOESM4 of PacBio single-molecule long-read sequencing shed new light on the complexity of the Carex breviculmis transcriptome

description: Additional file 4: Table S1. Summary of the candidate alternative splice (AS) events.