cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16928408
title: Additional file 6 of Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism

description: Additional file 6. GO (DMPs). Gene Ontology terms identified with GSEA using the differentially methylated positions. Type of GO term- biological process (BP), molecular function (MF), and cellular component (CC), name of GO term, N represents the total number of genes in the GO term, DE represents the number of differentially methylated genes in the GO term, and SigGenesInSet are the differentially methylated genes in the GO term.
DOI: 10.6084/m9.figshare.16928411.v1
title: Additional file 7 of Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism

description: Additional file 7. GO (DMRs). Gene Ontology terms identified with GSEA using the differentially methylated regions. Type of GO term- biological process (BP), molecular function (MF), and cellular component (CC), name of GO term, N represents the total number of genes in the GO term, DE represents the number of differentially methylated genes in the GO term, and SigGenesInSet are the differentially methylated genes in the GO term.
DOI: 10.6084/m9.figshare.16928414
title: Additional file 8 of Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism

description: Additional file 8. KEGG (DMPs). Kyoto Encyclopedia of Genes and Genomes pathways identified with GSEA using the differentially methylated positions. Description of KEGG pathway, N represents the total number of genes in the KEGG pathway, DE represents the number of differentially methylated genes in the KEGG pathway, and SigGenesInSet are the differentially methylated genes in the KEGG pathway.
DOI: 10.6084/m9.figshare.16928414.v1
title: Additional file 8 of Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism

description: Additional file 8. KEGG (DMPs). Kyoto Encyclopedia of Genes and Genomes pathways identified with GSEA using the differentially methylated positions. Description of KEGG pathway, N represents the total number of genes in the KEGG pathway, DE represents the number of differentially methylated genes in the KEGG pathway, and SigGenesInSet are the differentially methylated genes in the KEGG pathway.
DOI: 10.6084/m9.figshare.16928417
title: Additional file 9 of Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism

description: Additional file 9. KEGG (DMRs). Kyoto Encyclopedia of Genes and Genomes pathways identified with GSEA using the differentially methylated regions. Description of KEGG pathway, N represents the total number of genes in the KEGG pathway, DE represents the number of differentially methylated genes in the KEGG pathway, and SigGenesInSet are the differentially methylated genes in the KEGG pathway.
DOI: 10.6084/m9.figshare.16928417.v1
title: Additional file 9 of Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism

description: Additional file 9. KEGG (DMRs). Kyoto Encyclopedia of Genes and Genomes pathways identified with GSEA using the differentially methylated regions. Description of KEGG pathway, N represents the total number of genes in the KEGG pathway, DE represents the number of differentially methylated genes in the KEGG pathway, and SigGenesInSet are the differentially methylated genes in the KEGG pathway.
DOI: 10.6084/m9.figshare.16928433
title: Additional file 2 of Transposable elements that have recently been mobile in the human genome

description: Additional file 2: Supplementary Table 1. Source datasets used for polymorphic indel dataset generation. Supplementary Table 2. Manual verification of pMEDs reported in van de Lagemaat et. al. (2005) & list of current assemblies used for verification on the UCSC Genome Browser. Supplementary Table 3. Full list of TE subfamilies with human specific instances and their associated statistics. Supplementary Table 4. Full list of pMEIs identified from RMSs. Supplementary Table 5. LTR5_Hs pMEI consensus sequence. Supplementary Table 6. Genes analysed for pMEI and ASE correlation. Supplementary Table 7. Comparison of our RMS to frequency ranked lists from published pMEI datasets. Supplementary Table 8. Disease associated TE subfamilies and their hg19 remapping. Supplementary Table 9. Cell lines used in the study. Supplementary Table 10. Primers and oligos used in the study. Supplementary Table 11. Underlying DNA sequences of pMEIs and non-pMEI TE used for alignment.
DOI: 10.6084/m9.figshare.16928433.v1
title: Additional file 2 of Transposable elements that have recently been mobile in the human genome

description: Additional file 2: Supplementary Table 1. Source datasets used for polymorphic indel dataset generation. Supplementary Table 2. Manual verification of pMEDs reported in van de Lagemaat et. al. (2005) & list of current assemblies used for verification on the UCSC Genome Browser. Supplementary Table 3. Full list of TE subfamilies with human specific instances and their associated statistics. Supplementary Table 4. Full list of pMEIs identified from RMSs. Supplementary Table 5. LTR5_Hs pMEI consensus sequence. Supplementary Table 6. Genes analysed for pMEI and ASE correlation. Supplementary Table 7. Comparison of our RMS to frequency ranked lists from published pMEI datasets. Supplementary Table 8. Disease associated TE subfamilies and their hg19 remapping. Supplementary Table 9. Cell lines used in the study. Supplementary Table 10. Primers and oligos used in the study. Supplementary Table 11. Underlying DNA sequences of pMEIs and non-pMEI TE used for alignment.
DOI: 10.6084/m9.figshare.16928519.v1
title: Additional file 2 of Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer

description: Additional file 2.
DOI: 10.6084/m9.figshare.16928519
title: Additional file 2 of Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer

description: Additional file 2.
DOI: 10.6084/m9.figshare.16928522
title: Additional file 3 of Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer

description: Additional file 3.
DOI: 10.6084/m9.figshare.16928522.v1
title: Additional file 3 of Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer

description: Additional file 3.
DOI: 10.6084/m9.figshare.16928528
title: Additional file 4 of Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer

description: Additional file 4.
DOI: 10.6084/m9.figshare.16928528.v1
title: Additional file 4 of Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer

description: Additional file 4.
DOI: 10.6084/m9.figshare.16928514
title: Additional file 2 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 2: Supplementary File 1: GO enrichment during pod development processes of successive developmental stages in both genotypes’ peanut shells.
DOI: 10.6084/m9.figshare.16928517
title: Additional file 3 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 3: Supplementary File 2: Significant enrichment of GO terms in cluster matrix presented in a 4 × 4 transition matrix.
DOI: 10.6084/m9.figshare.16928514.v1
title: Additional file 2 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 2: Supplementary File 1: GO enrichment during pod development processes of successive developmental stages in both genotypes’ peanut shells.
DOI: 10.6084/m9.figshare.16928517.v1
title: Additional file 3 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 3: Supplementary File 2: Significant enrichment of GO terms in cluster matrix presented in a 4 × 4 transition matrix.
DOI: 10.6084/m9.figshare.16928520
title: Additional file 4 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 4: Supplementary File 3: Differentially expressed TF between genotypes present in H-2:53–1 cluster matrix.
DOI: 10.6084/m9.figshare.16928520.v1
title: Additional file 4 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 4: Supplementary File 3: Differentially expressed TF between genotypes present in H-2:53–1 cluster matrix.
DOI: 10.6084/m9.figshare.16928523.v1
title: Additional file 5 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 5: Supplementary File 4: Details and sequence of total of 155 genes of the cellulose synthase superfamily.
DOI: 10.6084/m9.figshare.16928526
title: Additional file 6 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 6: Supplementary File 5: Log2 transformed RPKM expression of CES superfamily was analyzed during different shell development stages.
DOI: 10.6084/m9.figshare.16928526.v1
title: Additional file 6 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 6: Supplementary File 5: Log2 transformed RPKM expression of CES superfamily was analyzed during different shell development stages.
DOI: 10.6084/m9.figshare.16928529
title: Additional file 7 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 7: Supplementary File 6: Log2 transformed RPKM expression data for cell wall modification-related genes and cluster analysis.
DOI: 10.6084/m9.figshare.16928535
title: Additional file 9 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 9: Supplementary File 8: Log2 modified RPKM values of DE TFs to generate heatmap and clusters using heat mapper resulted in four clusters.
DOI: 10.6084/m9.figshare.16928523
title: Additional file 5 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 5: Supplementary File 4: Details and sequence of total of 155 genes of the cellulose synthase superfamily.
DOI: 10.6084/m9.figshare.16928529.v1
title: Additional file 7 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 7: Supplementary File 6: Log2 transformed RPKM expression data for cell wall modification-related genes and cluster analysis.
DOI: 10.6084/m9.figshare.16928532
title: Additional file 8 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 8: Supplementary File 7: Log2 RPKM expression of TFs belonging to 67 TF families.
DOI: 10.6084/m9.figshare.16928535.v1
title: Additional file 9 of Deep transcriptomic study reveals the role of cell wall biosynthesis and organization networks in the developing shell of peanut pod

description: Additional file 9: Supplementary File 8: Log2 modified RPKM values of DE TFs to generate heatmap and clusters using heat mapper resulted in four clusters.
DOI: 10.6084/m9.figshare.16928550
title: Additional file 2 of Bayesian modelling of population trends in alcohol consumption provides empirically based country estimates for South Africa

description: Additional file 2. Additional tables.
DOI: 10.6084/m9.figshare.16928550.v1
title: Additional file 2 of Bayesian modelling of population trends in alcohol consumption provides empirically based country estimates for South Africa

description: Additional file 2. Additional tables.
DOI: 10.6084/m9.figshare.16928558
title: Additional file 3 of Molecular insights into the Y-domain of hepatitis E virus using computational analyses

description: Additional File 3. File S3. PDB file of the obtained HEV Y-domain RaptorX model.
DOI: 10.6084/m9.figshare.16928561
title: Additional file 4 of Molecular insights into the Y-domain of hepatitis E virus using computational analyses

description: Additional File 4. File S4. PDB file of the obtained HEV Y-domain Phyre2 model.
DOI: 10.6084/m9.figshare.16928561.v1
title: Additional file 4 of Molecular insights into the Y-domain of hepatitis E virus using computational analyses

description: Additional File 4. File S4. PDB file of the obtained HEV Y-domain Phyre2 model.
DOI: 10.6084/m9.figshare.16928564
title: Additional file 5 of Molecular insights into the Y-domain of hepatitis E virus using computational analyses

description: Additional File 5. File S5. PDB file of the obtained HEV Y-domain I-TASSER model (model 1) having a C-score of -4.10.
DOI: 10.6084/m9.figshare.16928564.v1
title: Additional file 5 of Molecular insights into the Y-domain of hepatitis E virus using computational analyses

description: Additional File 5. File S5. PDB file of the obtained HEV Y-domain I-TASSER model (model 1) having a C-score of -4.10.
DOI: 10.6084/m9.figshare.16928558.v1
title: Additional file 3 of Molecular insights into the Y-domain of hepatitis E virus using computational analyses

description: Additional File 3. File S3. PDB file of the obtained HEV Y-domain RaptorX model.
DOI: 10.6084/m9.figshare.16928567
title: Additional file 6 of Molecular insights into the Y-domain of hepatitis E virus using computational analyses

description: Additional File 6. File S6. PDB file of the obtained HEV Y-domain I-TASSER model (model 5) having a C-score of -4.25.
DOI: 10.6084/m9.figshare.16928567.v1
title: Additional file 6 of Molecular insights into the Y-domain of hepatitis E virus using computational analyses

description: Additional File 6. File S6. PDB file of the obtained HEV Y-domain I-TASSER model (model 5) having a C-score of -4.25.
DOI: 10.6084/m9.figshare.16928598
title: Additional file 1 of Placenta mediates the effect of maternal hypertension polygenic score on offspring birth weight: a study of birth cohort with fetal growth velocity data

description: Additional file 1: Table S1. Characteristics of participants included in this study. Table S2. Genome-wide significant loci for blood pressure phenotypes and classification based on vasculature relevance. Table S3. Variants constituting SBP-increasing PGS at p value threshold of 1 x 10−6 and classification based on vasculature relevance. Table S4. Linear regression analyses for maternal SBP-increasing PGS predicting various traits including birth weight. Table S5. Linear regression analyses for maternal DBP-increasing PGS predicting various traits including birth weight. Table S6. Linear regression analyses for maternal MAP-increasing PGS predicting various traits including birth weight. Table S7. Linear regression analyses for maternal PP-increasing PGS predicting various traits including birth weight. Table S8. Linear regression analyses for maternal BP traits predicting placental weight. Table S9. Sensitivity analysis for estimates of the causal mediation analyses by excluding pleotropic SNPs from exposure PGS.Table S10. Linear regression analyses for BP-increasing allele predicting birth weight or placental weight.
DOI: 10.6084/m9.figshare.16928598.v1
title: Additional file 1 of Placenta mediates the effect of maternal hypertension polygenic score on offspring birth weight: a study of birth cohort with fetal growth velocity data

description: Additional file 1: Table S1. Characteristics of participants included in this study. Table S2. Genome-wide significant loci for blood pressure phenotypes and classification based on vasculature relevance. Table S3. Variants constituting SBP-increasing PGS at p value threshold of 1 x 10−6 and classification based on vasculature relevance. Table S4. Linear regression analyses for maternal SBP-increasing PGS predicting various traits including birth weight. Table S5. Linear regression analyses for maternal DBP-increasing PGS predicting various traits including birth weight. Table S6. Linear regression analyses for maternal MAP-increasing PGS predicting various traits including birth weight. Table S7. Linear regression analyses for maternal PP-increasing PGS predicting various traits including birth weight. Table S8. Linear regression analyses for maternal BP traits predicting placental weight. Table S9. Sensitivity analysis for estimates of the causal mediation analyses by excluding pleotropic SNPs from exposure PGS.Table S10. Linear regression analyses for BP-increasing allele predicting birth weight or placental weight.
DOI: 10.6084/m9.figshare.16928628
title: Additional file 1 of Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

description: Additional file 1 (xlsx). EpiDish results for cell culture and biopsies. Given are the estimations for the proportions of the major cell types epithelial cells (Epi), fibroblasts (Fib), and immune cells (IC) per sample.
DOI: 10.6084/m9.figshare.16928628.v1
title: Additional file 1 of Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

description: Additional file 1 (xlsx). EpiDish results for cell culture and biopsies. Given are the estimations for the proportions of the major cell types epithelial cells (Epi), fibroblasts (Fib), and immune cells (IC) per sample.
DOI: 10.6084/m9.figshare.16928634.v1
title: Additional file 3 of Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

description: Additional file 3 (xlsx). Significant DMPs in full set. Results for all 15,507 DMPs significant in the full set of 48 samples of clinically uninflamed and 48 samples of inflamed gingiva.
DOI: 10.6084/m9.figshare.16928637.v1
title: Additional file 4 of Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

description: Additional file 4 (xlsx). 441 DMPs from stringent filtering step. Results for the 441 DMPs in 193 clusters that were derived from a more stringent filtering process (q
DOI: 10.6084/m9.figshare.16928640
title: Additional file 5 of Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

description: Additional file 5 (xlsx). Enrichment analysis of GO terms and KEGG pathways. Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for genes corresponding to the 2347 DMPs significant in the full and paired sub-analysis. BP = biological process, MF = molecular function, CC = cellular component.
DOI: 10.6084/m9.figshare.16928637
title: Additional file 4 of Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

description: Additional file 4 (xlsx). 441 DMPs from stringent filtering step. Results for the 441 DMPs in 193 clusters that were derived from a more stringent filtering process (q
DOI: 10.6084/m9.figshare.16928634
title: Additional file 3 of Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

description: Additional file 3 (xlsx). Significant DMPs in full set. Results for all 15,507 DMPs significant in the full set of 48 samples of clinically uninflamed and 48 samples of inflamed gingiva.
DOI: 10.6084/m9.figshare.16928640.v1
title: Additional file 5 of Epigenetic adaptations of the masticatory mucosa to periodontal inflammation

description: Additional file 5 (xlsx). Enrichment analysis of GO terms and KEGG pathways. Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for genes corresponding to the 2347 DMPs significant in the full and paired sub-analysis. BP = biological process, MF = molecular function, CC = cellular component.
DOI: 10.6084/m9.figshare.16928645
title: Additional file 3 of Spirometric reference equations for Cameroonians aged 4 to 89 years derived using lambda, mu, sigma (LMS) method

description: Additional file 3. Lookup tables for splines and coefficients to derive normal spirometric values for Cameroonian aged 4 to 89 years old.
DOI: 10.6084/m9.figshare.16928645.v1
title: Additional file 3 of Spirometric reference equations for Cameroonians aged 4 to 89 years derived using lambda, mu, sigma (LMS) method

description: Additional file 3. Lookup tables for splines and coefficients to derive normal spirometric values for Cameroonian aged 4 to 89 years old.
DOI: 10.6084/m9.figshare.16928648
title: Additional file 4 of Spirometric reference equations for Cameroonians aged 4 to 89 years derived using lambda, mu, sigma (LMS) method

description: Additional file 4. SPSS syntaxes for calculation of normal spirometric values for Cameroonian aged 4 to 89 years old.
DOI: 10.6084/m9.figshare.16928648.v1
title: Additional file 4 of Spirometric reference equations for Cameroonians aged 4 to 89 years derived using lambda, mu, sigma (LMS) method

description: Additional file 4. SPSS syntaxes for calculation of normal spirometric values for Cameroonian aged 4 to 89 years old.
DOI: 10.6084/m9.figshare.16928649
title: Additional file 1 of Efficacy of artesunate-amodiaquine and artemether-lumefantrine for uncomplicated Plasmodium falciparum malaria in Madagascar, 2018

description: Additional file 1: Microsatellite lengths of paired Day 0-Day of Failure samples from cases of recurrent parasitemia and a random sample of day 0 samples of non-recurrent parasitemias observed over the 2018 therapeutic efficacy study in Madagascar. Last column shows the posterior probability of recrudescence obtained from Bayesian analysis of observed data.
DOI: 10.6084/m9.figshare.16928658.v1
title: Additional file 3 of Genetic architecture and genomic selection of fatty acid composition predicted by Raman spectroscopy in rainbow trout

description: Additional file 3.Candidate genes from the NCBI Oncorhynchus mykiss Annotation Release 100 (GCF_002163495.1) that were located within the confidence or credibility intervals estimated using BCπ analysis.
DOI: 10.6084/m9.figshare.16928658
title: Additional file 3 of Genetic architecture and genomic selection of fatty acid composition predicted by Raman spectroscopy in rainbow trout

description: Additional file 3.Candidate genes from the NCBI Oncorhynchus mykiss Annotation Release 100 (GCF_002163495.1) that were located within the confidence or credibility intervals estimated using BCπ analysis.
DOI: 10.6084/m9.figshare.16928666.v1
title: Additional file 10 of Transcriptome profiling reveals the developmental regulation of NaCl-treated Forcipomyia taiwana eggs

description: Additional file 10.
DOI: 10.6084/m9.figshare.16928666
title: Additional file 10 of Transcriptome profiling reveals the developmental regulation of NaCl-treated Forcipomyia taiwana eggs

description: Additional file 10.
DOI: 10.6084/m9.figshare.16928675
title: Additional file 2 of Transcriptome profiling reveals the developmental regulation of NaCl-treated Forcipomyia taiwana eggs

description: Additional file 2.
DOI: 10.6084/m9.figshare.16928675.v1
title: Additional file 2 of Transcriptome profiling reveals the developmental regulation of NaCl-treated Forcipomyia taiwana eggs

description: Additional file 2.