cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11415876
title: MOESM8 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 8: Logistic regression analysis between stratified clinical, response and treatment parameters and stratified biomarkers, showing the p-value, Odd ratio and the 95% confidence interval for this Odd ratio. Univariate and multivariate analysis. Table containing information regarding the interactions between biomarkers, as categorical variables, and different clinical parameters and treatment received by the patient.
DOI: 10.6084/m9.figshare.11415870
title: MOESM7 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 7: Logistic regression analysis between stratified biomarkers, showing the p-value, Odd ratio and the 95% confidence interval for this Odd ratio. Univariate and multivariate analysis. Table containing information regarding the relationship between biomarkers as categorical variables.
DOI: 10.6084/m9.figshare.11415876.v1
title: MOESM8 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 8: Logistic regression analysis between stratified clinical, response and treatment parameters and stratified biomarkers, showing the p-value, Odd ratio and the 95% confidence interval for this Odd ratio. Univariate and multivariate analysis. Table containing information regarding the interactions between biomarkers, as categorical variables, and different clinical parameters and treatment received by the patient.
DOI: 10.6084/m9.figshare.11415870.v1
title: MOESM7 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 7: Logistic regression analysis between stratified biomarkers, showing the p-value, Odd ratio and the 95% confidence interval for this Odd ratio. Univariate and multivariate analysis. Table containing information regarding the relationship between biomarkers as categorical variables.
DOI: 10.6084/m9.figshare.11415861
title: MOESM6 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 6: Logistic regression analysis between stratified biomarkers and normalized continuous biomarkers, showing the p-value, Odd ratio and the 95% confidence interval for this Odd ratio. Univariate and multivariate analysis. Table containing information regarding the relationship between biomarkers as categorical and continuous variables.
DOI: 10.6084/m9.figshare.11415861.v1
title: MOESM6 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 6: Logistic regression analysis between stratified biomarkers and normalized continuous biomarkers, showing the p-value, Odd ratio and the 95% confidence interval for this Odd ratio. Univariate and multivariate analysis. Table containing information regarding the relationship between biomarkers as categorical and continuous variables.
DOI: 10.6084/m9.figshare.11415852
title: MOESM5 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 5: Linear regression analysis between non stratified biomarkers, showing the p-value. Table containing information regarding the relationship between biomarkers as continuous variables.
DOI: 10.6084/m9.figshare.11415852.v1
title: MOESM5 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 5: Linear regression analysis between non stratified biomarkers, showing the p-value. Table containing information regarding the relationship between biomarkers as continuous variables.
DOI: 10.6084/m9.figshare.11415843
title: MOESM4 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 4: Descriptive statistics of variables and clinical characteristics of patients included in the study, according to the type of disease response. Descriptive statistics of the whole population according to clinical parameters.
DOI: 10.6084/m9.figshare.11415843.v1
title: MOESM4 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 4: Descriptive statistics of variables and clinical characteristics of patients included in the study, according to the type of disease response. Descriptive statistics of the whole population according to clinical parameters.
DOI: 10.6084/m9.figshare.11415834
title: MOESM3 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 3: Non-parametric correlation and linear regression analysis of the four biomarkers included in the study, as continuous variables, against tumour volume and number of metastatic sites. Mann-Whitney-Wilcoxon non parametric test and logistic regression analysis between stratified biomarkers and response categories against tumour volume and number of metastatics sites used as continuous variables, showing the p-value (multivariate analysis). Overall survival analysis of metastatic breast cancer patients, showing the p-value (univariate and multivariate analysis). Table including data regarding relationship between biomarkers, overall survival of patients and tumour bulk.
DOI: 10.6084/m9.figshare.11415834.v1
title: MOESM3 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 3: Non-parametric correlation and linear regression analysis of the four biomarkers included in the study, as continuous variables, against tumour volume and number of metastatic sites. Mann-Whitney-Wilcoxon non parametric test and logistic regression analysis between stratified biomarkers and response categories against tumour volume and number of metastatics sites used as continuous variables, showing the p-value (multivariate analysis). Overall survival analysis of metastatic breast cancer patients, showing the p-value (univariate and multivariate analysis). Table including data regarding relationship between biomarkers, overall survival of patients and tumour bulk.
DOI: 10.6084/m9.figshare.11415822
title: MOESM2 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 2: Composite table with information of all the 39 samples. Information about the small subset of the population used for preliminary analysis.
DOI: 10.6084/m9.figshare.11415822.v1
title: MOESM2 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 2: Composite table with information of all the 39 samples. Information about the small subset of the population used for preliminary analysis.
DOI: 10.6084/m9.figshare.11415810
title: MOESM1 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 1: Composite table with information of all the 194 samples included in the study. Information about the whole dataset included in the study.
DOI: 10.6084/m9.figshare.11415810.v1
title: MOESM1 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 1: Composite table with information of all the 194 samples included in the study. Information about the whole dataset included in the study.
DOI: 10.6084/m9.figshare.11415804
title: MOESM1 of Variation in plastid genomes in the gynodioecious species Silene vulgaris

description: Additional file 1. Numerical tables. Data Set S1. Simple sequence repeats in plastid genomes of S. vulgaris. Data Set S2. Substitution rates in plastid genes of S. vulgaris. Data Set S3. KaKs matrices. Data Set S4. Gene coverage of plastid genes of S. vulgaris. Data Set S5. Antisense transcript coverage in plastid genomes of S. vulgaris. Data Set S6. Editing rates in plastid genomes of S. vulgaris. Data Set S7. psbZ editing extent
DOI: 10.6084/m9.figshare.11415807
title: MOESM4 of Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence

description: Additional file 4. The correlations between mRNA and protein in the three stages.
DOI: 10.6084/m9.figshare.11415801
title: MOESM10 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 10: Overall survival analysis of metastatic breast cancer patients, showing the p-value, Hazard ratio and the 95% confidence interval for this Hazard ratio. Comparison of joint analysis of new blood biomarkers (CTCs and cfDNA) against traditional biomarkers (CA15-3 and AP). Stratified biomarkers as variables. Overall survival population results from joint analysis of biomarkers.
DOI: 10.6084/m9.figshare.11415804.v1
title: MOESM1 of Variation in plastid genomes in the gynodioecious species Silene vulgaris

description: Additional file 1. Numerical tables. Data Set S1. Simple sequence repeats in plastid genomes of S. vulgaris. Data Set S2. Substitution rates in plastid genes of S. vulgaris. Data Set S3. KaKs matrices. Data Set S4. Gene coverage of plastid genes of S. vulgaris. Data Set S5. Antisense transcript coverage in plastid genomes of S. vulgaris. Data Set S6. Editing rates in plastid genomes of S. vulgaris. Data Set S7. psbZ editing extent
DOI: 10.6084/m9.figshare.11415807.v1
title: MOESM4 of Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence

description: Additional file 4. The correlations between mRNA and protein in the three stages.
DOI: 10.6084/m9.figshare.11415798
title: MOESM3 of Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence

description: Additional file 3. The enriched KEGG pathways in the three stages.
DOI: 10.6084/m9.figshare.11415798.v1
title: MOESM3 of Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence

description: Additional file 3. The enriched KEGG pathways in the three stages.
DOI: 10.6084/m9.figshare.11415801.v1
title: MOESM10 of Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer

description: Additional file 10: Overall survival analysis of metastatic breast cancer patients, showing the p-value, Hazard ratio and the 95% confidence interval for this Hazard ratio. Comparison of joint analysis of new blood biomarkers (CTCs and cfDNA) against traditional biomarkers (CA15-3 and AP). Stratified biomarkers as variables. Overall survival population results from joint analysis of biomarkers.
DOI: 10.6084/m9.figshare.11415792
title: MOESM2 of Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence

description: Additional file 2. The enriched GO terms in the three stages.
DOI: 10.6084/m9.figshare.11415789
title: MOESM1 of Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence

description: Additional file 1. The mainly regulatory pathways (without directions) with the most protein numbers in the three stages.
DOI: 10.6084/m9.figshare.11415792.v1
title: MOESM2 of Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence

description: Additional file 2. The enriched GO terms in the three stages.
DOI: 10.6084/m9.figshare.11415789.v1
title: MOESM1 of Quantitative proteomic analyses of two soybean low phytic acid mutants to identify the genes associated with seed field emergence

description: Additional file 1. The mainly regulatory pathways (without directions) with the most protein numbers in the three stages.
DOI: 10.6084/m9.figshare.11415774
title: MOESM3 of A deep neural network approach to predicting clinical outcomes of neuroblastoma patients

description: Additional file 3 Full results of all models. Each model is described by its parameters and the corresponding balanced accuracy. Archive of XLSX files.
DOI: 10.6084/m9.figshare.11415768
title: MOESM2 of A deep neural network approach to predicting clinical outcomes of neuroblastoma patients

description: Additional file 2 Patient stratification of the ‘Fischer’ dataset. XLSX file.
DOI: 10.6084/m9.figshare.11415774.v1
title: MOESM3 of A deep neural network approach to predicting clinical outcomes of neuroblastoma patients

description: Additional file 3 Full results of all models. Each model is described by its parameters and the corresponding balanced accuracy. Archive of XLSX files.
DOI: 10.6084/m9.figshare.11415768.v1
title: MOESM2 of A deep neural network approach to predicting clinical outcomes of neuroblastoma patients

description: Additional file 2 Patient stratification of the ‘Fischer’ dataset. XLSX file.
DOI: 10.6084/m9.figshare.11415738
title: MOESM9 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 9 The results of functional enrichment analysis of the genes involved in the 147 prognostic gene pairs for BRCA.
DOI: 10.6084/m9.figshare.11415738.v1
title: MOESM9 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 9 The results of functional enrichment analysis of the genes involved in the 147 prognostic gene pairs for BRCA.
DOI: 10.6084/m9.figshare.11415729
title: MOESM8 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 8 Significant gene pairs derived from noncancer signatures used in the study of venet et al. [21].
DOI: 10.6084/m9.figshare.11415729.v1
title: MOESM8 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 8 Significant gene pairs derived from noncancer signatures used in the study of venet et al. [21].
DOI: 10.6084/m9.figshare.11415720
title: MOESM7 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 7 Top 10 prognostic gene pairs derived by PCC and SCC in three cancer types.
DOI: 10.6084/m9.figshare.11415720.v1
title: MOESM7 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 7 Top 10 prognostic gene pairs derived by PCC and SCC in three cancer types.
DOI: 10.6084/m9.figshare.11415687
title: MOESM3 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 3 Results of the log-rank test and the Cox proportional hazards model.
DOI: 10.6084/m9.figshare.11415687.v1
title: MOESM3 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 3 Results of the log-rank test and the Cox proportional hazards model.
DOI: 10.6084/m9.figshare.11415681
title: MOESM1 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 1 A total of 516 genes for BRCA, 466 genes for COAD, and 410 genes for LUAD are listed in BRCA.csv, COAD.csv, and LUAD.csv, respectively.
DOI: 10.6084/m9.figshare.11415681.v1
title: MOESM1 of Finding prognostic gene pairs for cancer from patient-specific gene networks

description: Additional file 1 A total of 516 genes for BRCA, 466 genes for COAD, and 410 genes for LUAD are listed in BRCA.csv, COAD.csv, and LUAD.csv, respectively.
DOI: 10.6084/m9.figshare.11415621
title: MOESM18 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 18: Table S11. Genes commonly hypermethylated or hypomethylated in all pairwise comparisons. Enriched biological processes of genes commonly affected in the SO vs. SOA and IFC vs. SOA comparisons related to sexual maturity of oocytes (n=352).
DOI: 10.6084/m9.figshare.11415621.v1
title: MOESM18 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 18: Table S11. Genes commonly hypermethylated or hypomethylated in all pairwise comparisons. Enriched biological processes of genes commonly affected in the SO vs. SOA and IFC vs. SOA comparisons related to sexual maturity of oocytes (n=352).
DOI: 10.6084/m9.figshare.11415615
title: MOESM17 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 17: Table S10. Specific loci in IFC vs. SOA comparison that contained multiple differential hypo- or hypermethylated tiles (more than 20% methylation difference).
DOI: 10.6084/m9.figshare.11415615.v1
title: MOESM17 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 17: Table S10. Specific loci in IFC vs. SOA comparison that contained multiple differential hypo- or hypermethylated tiles (more than 20% methylation difference).
DOI: 10.6084/m9.figshare.11415606
title: MOESM15 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 15: Table S8. Specific loci in SO vs. SOA comparison that contained multiple differential hypo- or hypermethylated tiles (more than 20% methylation difference). Enriched biological processes of hypermethylated genes in SO compared to SOA (n=40), including the proteins involved in each GO term.
DOI: 10.6084/m9.figshare.11415609
title: MOESM16 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 16: Table S9. Differentially hypomethylated tiles (n=4158) and hypermethylated tiles (n=3477) with more than 20% methylation difference in IFC compared to SOA. Each tile contains information about the genome location, overlapping gene, Ensembl ID, gene description and methylation percentage in each sample.
DOI: 10.6084/m9.figshare.11415606.v1
title: MOESM15 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 15: Table S8. Specific loci in SO vs. SOA comparison that contained multiple differential hypo- or hypermethylated tiles (more than 20% methylation difference). Enriched biological processes of hypermethylated genes in SO compared to SOA (n=40), including the proteins involved in each GO term.
DOI: 10.6084/m9.figshare.11415609.v1
title: MOESM16 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 16: Table S9. Differentially hypomethylated tiles (n=4158) and hypermethylated tiles (n=3477) with more than 20% methylation difference in IFC compared to SOA. Each tile contains information about the genome location, overlapping gene, Ensembl ID, gene description and methylation percentage in each sample.
DOI: 10.6084/m9.figshare.11415603
title: MOESM14 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 14: Table S7. Differentially hypomethylated tiles (n=48) and hypermethylated tiles (n=2031) with more than 20% methylation difference in SO compared to SOA. Each tile contains information about the genome location, overlapping gene, Ensembl ID, gene description and methylation percentage in each sample. Differentially methylated CGIs between SO and SOA (n=107)
DOI: 10.6084/m9.figshare.11415603.v1
title: MOESM14 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 14: Table S7. Differentially hypomethylated tiles (n=48) and hypermethylated tiles (n=2031) with more than 20% methylation difference in SO compared to SOA. Each tile contains information about the genome location, overlapping gene, Ensembl ID, gene description and methylation percentage in each sample. Differentially methylated CGIs between SO and SOA (n=107)
DOI: 10.6084/m9.figshare.11415594
title: MOESM13 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 13: Table S6. Specific loci in SOA compared to IV that contained multiple differential hypo- or hypermethylated tiles (&gt; 20% methylation difference). Enriched biological processes of hypermethylated promoters in SOA vs IV (20% difference of methylation, n=128).
DOI: 10.6084/m9.figshare.11415594.v1
title: MOESM13 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 13: Table S6. Specific loci in SOA compared to IV that contained multiple differential hypo- or hypermethylated tiles (&gt; 20% methylation difference). Enriched biological processes of hypermethylated promoters in SOA vs IV (20% difference of methylation, n=128).
DOI: 10.6084/m9.figshare.11415582
title: MOESM12 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 12: Table S5. Differentially hypomethylated tiles (n=110) and hypermethylated tiles (n=455) with more than 20% methylation difference in SOA compared to IV. Each tile contains information about the genome location, overlapping gene, Ensembl ID, gene description and methylation percentage in each sample. Differentially methylated CGIs between SOA and IV (n=60).
DOI: 10.6084/m9.figshare.11415579
title: MOESM1 of Targeted test evaluation: a framework for designing diagnostic accuracy studies with clear study hypotheses

description: Additional file 1. An example of a sample size calculator.
DOI: 10.6084/m9.figshare.11415582.v1
title: MOESM12 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 12: Table S5. Differentially hypomethylated tiles (n=110) and hypermethylated tiles (n=455) with more than 20% methylation difference in SOA compared to IV. Each tile contains information about the genome location, overlapping gene, Ensembl ID, gene description and methylation percentage in each sample. Differentially methylated CGIs between SOA and IV (n=60).
DOI: 10.6084/m9.figshare.11415579.v1
title: MOESM1 of Targeted test evaluation: a framework for designing diagnostic accuracy studies with clear study hypotheses

description: Additional file 1. An example of a sample size calculator.
DOI: 10.6084/m9.figshare.11415573
title: MOESM11 of Genome-wide assessment of DNA methylation in mouse oocytes reveals effects associated with in vitro growth, superovulation, and sexual maturity

description: Additional file 11: Table S4. Specific loci in IFC compared to SO that contained multiple differential hypo- or hypermethylated tiles (&gt; 20% methylation difference). Enriched biological processes of hypomethylated genes in IFC compared to SO (n = 17), including the proteins involved in each GO term.