cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14738769.v1
title: Additional file 2 of Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

description: Additional file 2: Table S2. Clinical information of samples in GSE57495 dataset.
DOI: 10.6084/m9.figshare.14738766.v1
title: Additional file 1 of Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

description: Additional file 1: Table S1. Clinical information of samples in TCGA entire dataset.
DOI: 10.6084/m9.figshare.14738708.v1
title: Additional file 4 of Genome-wide association studies reveal candidate genes associated to bacteraemia caused by ST93-IV CA-MRSA

description: Additional file 4:Supplementary Table 4: Gene rearrangements statistics associated to bacteremia
DOI: 10.6084/m9.figshare.14738705.v1
title: Additional file 3 of Genome-wide association studies reveal candidate genes associated to bacteraemia caused by ST93-IV CA-MRSA

description: Additional file 3:Supplementary Table 3: Statistics supporting bacteremia in clade 2
DOI: 10.6084/m9.figshare.14738703.v1
title: Additional file 3 of Putative markers for the detection of early-stage bladder cancer selected by urine metabolomics

description: Additional file 3: Table S3. Putative markers and their corresponding prediction results.
DOI: 10.6084/m9.figshare.14738702.v1
title: Additional file 2 of Genome-wide association studies reveal candidate genes associated to bacteraemia caused by ST93-IV CA-MRSA

description: Additional file 2:Supplementary Table 2: Statistics supporting clade specific genes
DOI: 10.6084/m9.figshare.14738700.v1
title: Additional file 2 of Putative markers for the detection of early-stage bladder cancer selected by urine metabolomics

description: Additional file 2: Table S2. The members of marker discovery cohort and independent test cohort.
DOI: 10.6084/m9.figshare.14738699.v1
title: Additional file 1 of Genome-wide association studies reveal candidate genes associated to bacteraemia caused by ST93-IV CA-MRSA

description: Additional file 1:Supplementary Table 1: ST93-IV isolates used in this study with bacteremia gene matrix
DOI: 10.6084/m9.figshare.14738697.v1
title: Additional file 1 of Putative markers for the detection of early-stage bladder cancer selected by urine metabolomics

description: Additional file 1: Table S1. The 922 compounds identified from 124 patients with bladder cancer or hernia.
DOI: 10.6084/m9.figshare.14738655.v1
title: Additional file 1 of Differential chromatin accessibility landscape of gain-of-function mutant p53 tumours

description: Additional file 1: Table S1. TCGA samples with TP53 mutation status. Table S2. The annotated significant differentially accessibility peaks identified in breast and colon cancers. Table S3. Enrichment of CNA events in different distance bins. Tabel S4. Results of TF motif enrichment analysis (related to Fig. 2a-d). Table S5. Enrichment of non-B-form DNA structure in differentially accessible peaks. Table S6. Results from differential gene expression analysis between mutant and wild-type p53 tumours. Table S7. Summary gene list from the differential accessibility, differential expression, and overlap of both.
DOI: 10.6084/m9.figshare.14738652.v1
title: Additional file 1 of A framework for handling missing accelerometer outcome data in trials

description: Additional file 1 The STATA DO-File (.do) provides example code for using multiple imputation with interval regression.
DOI: 10.6084/m9.figshare.14738619.v1
title: Additional file 2 of Reliability of GENEActiv accelerometers to estimate sleep, physical activity, and sedentary time in children

description: Additional file 2.
DOI: 10.6084/m9.figshare.14738594.v1
title: Additional file 1 of Integration of Dual Stress Transcriptomes and Major QTLs from a Pair of Genotypes Contrasting for Drought and Chronic Nitrogen Starvation Identifies Key Stress Responsive Genes in Rice

description: Additional file 1: Supplementary Table 1: All differentially expressed genes identified under N-W+, N + W- and N_W- treatments compared to optimal input supply (N + W+) in root and shoot tissues of IR64 and N22. Supplementary Table 2: Comparison of the expression of N transporters, sensors and regulators under various stress treatments in IR64 and N22. Supplementary Table 3: Comparison of the expression of known transcription factors (TFs) under various stress treatments in IR64 and N22. Supplementary Table 4: Comparison of the expression of novel (not annotated) genes under various stress treatments in IR64 and N22. Supplementary Table 5: Comparison of plant hormone metabolism genes and their receptors under various stress treatments in IR64 and N22. Supplementary Table 6: Comparison of the expression profile of the genes and QTLs known for Nitrogen use efficiency. Supplementary Table 7: Details of primers designed for validation of the DEGs identified from transcriptome analysis by qPCR assay. Supplementary Table 8: SNPs in the two major QTL hotspot regions identified on chromosomes 1 and 6. Supplementary Table 9: Relative water content (%) under optimal and all the three stress conditions measured in an independent experiment. Supplementary Table 10: DEGS identified in genes encoding for major enzymes involved in C and N skeleton. Supplementary Table 11: Details of variations in cis elements between IR64 and N22 genotypes for 20 N transporter, N regulator, TOND1, Dof genes and candidate genes identified from the major QTLs mapped in the present study. Supplementary Table 12: miRNAs in the candidate genes present in interval of the QTL hotspot region identified on chromosome 6. Supplementary Table 13: Comparison of expression of DE ABA related genes under different stress treatments in two rice genotypes N22 and IR64.
DOI: 10.6084/m9.figshare.14738571.v1
title: Additional file 3 of Bone marrow mesenchymal stem cells and their derived exosomes resolve doxorubicin-induced chemobrain: critical role of their miRNA cargo

description: Additional file 3.
DOI: 10.6084/m9.figshare.14738568.v1
title: Additional file 2 of Bone marrow mesenchymal stem cells and their derived exosomes resolve doxorubicin-induced chemobrain: critical role of their miRNA cargo

description: Additional file 2.
DOI: 10.6084/m9.figshare.14738562.v1
title: Additional file 1 of SARS-CoV-2 complete genome sequencing from the Italian Campania region using a highly automated next generation sequencing system

description: Additional file 1: Table S1. Confirmation of unreported variants by S5 and Sanger sequencing.
DOI: 10.6084/m9.figshare.14738534.v1
title: Additional file 2 of SnoRNA copy regulation affects family size, genomic location and family abundance levels

description: Additional file 2: Table S2. Rfam classified snoRNA families and their characteristics. ‘Expressed’ refers to at least one family member expressed, according to our criteria (see Table S1). Average_sum_TPM is the average of the sum of all snoRNA family members across the 21 samples. Num_members and Num_expressed_members are the number of all and expressed members of a family, respectively. Switch refers to the presence of switches between the most abundant member across tissues. Same_host displays TRUE if all expressed members are in the same host gene. Family_covariation is the covariation (see Table S1) of the sum of abundance of all members of a family across tissues. Mean_member_covariation is the mean covariation of each expressed member of a family across tissues.
DOI: 10.6084/m9.figshare.14738531.v1
title: Additional file 1 of SnoRNA copy regulation affects family size, genomic location and family abundance levels

description: Additional file 1: Table S1. Rfam classified snoRNAs and their characteristics. ‘Expressed’ refers to at least 1 TPM of abundance in one of the 21 samples (7 tissues). Average_TPM, Min_TPM and Max_TPM is the average, max and min values, respectively, of the 21 samples. Tissue_most_expressed_in is the tissue where the average abundance of a tissue is the highest. Conservation_score refers to the average of the “phastCons 100 Vertebrates” score for the entire snoRNA divided by the length of the sequence. Alignement_score is the average pairwise sequence identity score for a snoRNA against all the other members of a family. The coefficient of variation (CV = σ / μ * 100, σ being the standard deviation and μ the mean) was calculated from the mean value of each tissue. Genomic_context displays the location of the snoRNA, which could be either coding (in a protein coding gene), noncoding (in a noncoding gene) or intergenic. SNP/nt_1000 is the number of SNP * 1000 divided by the length of the snoRNA.
DOI: 10.6084/m9.figshare.14738490.v1
title: Additional file 1 of Activity of Plasmodium vivax promoter elements in Plasmodium knowlesi, and a centromere-containing plasmid that expresses NanoLuc throughout the parasite life cycle

description: Additional file 1: Table S1. Oligonucleotide primers used in this work. Table S2. Transient transfection of Plasmodium parasites. Table S3. Plasmodium knowlesi growth and luminescence signal during selection using WR99210. Table S4. NanoLuc signal of in vitro cultivated transgenic blood-stage parasites. Table S5. Rhesus infections with transgenic luminescent P. knowlesi. Table S6. Number of oocysts detected in individual mosquitoes dissected 7 days after the feeds and Luminescence signals obtained (only midguts isolated from mosquitoes from Feed #2). Table S7. Total sporozoites isolated from 8 mosquitoes from each species, infected with transgenic bioluminescent P. knowlesi, 10 days after the feeds and Luminescence signals. Table S8. pvcen-pvhsp70-D-NanoLuc plasmid copy number variation in blood-stage parasites. Table S9. Half-maximum inhibitory concentration (IC50) measures of drug response. Table S10. Plasmodium knowlesi red blood cell invasion assays.
DOI: 10.6084/m9.figshare.14738475.v1
title: Additional file 3 of Differential transcription pathways associated with rootstock-induced dwarfing in breadfruit (Artocarpus altilis) scions

description: Additional file 3: Table S3. Gene annotation and expression levels showing all differentially expressed genes (FDR &lt; 0.05 and |logFC| ≥1)*. *LogFC, Log2-fold change of expression from samples on marang rootstocks vs those on self-graft; FDR, adjusted p-value for multiple hypothesis testing; logCPM, average log count for the gene across all samples; F, quasi-likelihood F-statistic for genes across all samples; C1-C3, raw gene counts for replicates of self-graft control; T1-T3, raw gene counts for replicates on marang rootstocks.
DOI: 10.6084/m9.figshare.14738444.v1
title: Additional file 9 of Low nitrogen availability inhibits the phosphorus starvation response in maize (Zea mays ssp. mays L.)

description: Additional file 9: Supplemental file 3. MZ95 experiment. File contains phenotypic and gene expression data from qRT-PCR of maize leaves and roots under LowN, LowP and lowNP at 25 days after emergence. Workbook contains expression data and analysis.
DOI: 10.6084/m9.figshare.14738441.v1
title: Additional file 8 of Low nitrogen availability inhibits the phosphorus starvation response in maize (Zea mays ssp. mays L.)

description: Additional file 8: Supplemental file 2. Transcriptome analysis of from maize plants under lowN, lowP and lowNP until 25 days after emergence (experiment MZ67). Workbook contains count data, analysis, candidate gene lists and annotation, and enriched GO terms.
DOI: 10.6084/m9.figshare.14738438.v1
title: Additional file 7 of Low nitrogen availability inhibits the phosphorus starvation response in maize (Zea mays ssp. mays L.)

description: Additional file 7: Supplemental file 1. Plant growth to 40 days after emergence (experiment MZ66). Workbook contains raw and processed phenotypic data from maize plants under lowN, lowP and lowNP until 40 days after emergence.
DOI: 10.6084/m9.figshare.14738382.v1
title: Additional file 4 of Patient-derived scaffolds influence secretion profiles in cancer cells mirroring clinical features and breast cancer subtypes

description: Additional file 3. Correlation table with p-values and q-values (FDR) for all investigated proteins.
DOI: 10.6084/m9.figshare.14738379.v1
title: Additional file 3 of Patient-derived scaffolds influence secretion profiles in cancer cells mirroring clinical features and breast cancer subtypes

description: Additional file 2. Correlation table with p-values for all proteins in SOM1, SOM2 and SOM3.
DOI: 10.6084/m9.figshare.14738376.v1
title: Additional file 2 of Patient-derived scaffolds influence secretion profiles in cancer cells mirroring clinical features and breast cancer subtypes

description: Additional file 1. Name, abbreviation, secretion location and pathway inclusions for all investigated proteins.
DOI: 10.6084/m9.figshare.14738370.v1
title: Additional file 1 of The REASON score: an epigenetic and clinicopathologic score to predict risk of poor survival in patients with early stage oral squamous cell carcinoma

description: Additional file 1: Table S1. Functional network analysis (GO). Differentially methylated pathways (adjusted p-value
DOI: 10.6084/m9.figshare.14738862
title: Additional file 2 of A more practical guide to incorporating health equity domains in implementation determinant frameworks

description: Additional file 2: Qualitative Codebook of the Three Health Equity Domains from Health Equity Implementation Framework.
DOI: 10.6084/m9.figshare.14738849
title: Additional file 1 of Inequalities in access to safe drinking water in Peruvian households according to city size: an analysis from 2008 to 2018

description: Additional file 1: Figure S1. Access to safe drinking water in Peru across departments, excluding rural areas, ENAHO 2008–2018.
DOI: 10.6084/m9.figshare.14738844
title: Additional file 6 of A high-throughput screening assay based on automated microscopy for monitoring antibiotic susceptibility of Mycobacterium tuberculosis phenotypes

description: Additional file 6: Table S2. Intra- and inter-assay variability. Intra- and inter-assay variability was calculated using replicated measurements (n = 33) of total area/image (μm2) from 3 replicated experiments. Data is presented as coefficient of variation CV (%).
DOI: 10.6084/m9.figshare.14738835
title: Additional file 2 of A high-throughput screening assay based on automated microscopy for monitoring antibiotic susceptibility of Mycobacterium tuberculosis phenotypes

description: Additional file 2: Table S1. Frequency of aggregate sizes in planktonic and cording bacteria. Data represents median values of 33 technical replicates of untreated controls for both planktonic and cording phenotype in three independent experiments. NP (non-present) marks intervals where no aggregates were identified. Number of events in each experiment &gt;100.
DOI: 10.6084/m9.figshare.14738775
title: Additional file 4 of Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

description: Additional file 4: Table S4. Candidate genes obtained by differential gene expression analysis and univariate regression analysis.
DOI: 10.6084/m9.figshare.14738772
title: Additional file 3 of Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

description: Additional file 3: Table S3. Genes related to histone modification obtained from the GSEA website.
DOI: 10.6084/m9.figshare.14738769
title: Additional file 2 of Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

description: Additional file 2: Table S2. Clinical information of samples in GSE57495 dataset.
DOI: 10.6084/m9.figshare.14738766
title: Additional file 1 of Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

description: Additional file 1: Table S1. Clinical information of samples in TCGA entire dataset.
DOI: 10.6084/m9.figshare.14738708
title: Additional file 4 of Genome-wide association studies reveal candidate genes associated to bacteraemia caused by ST93-IV CA-MRSA

description: Additional file 4:Supplementary Table 4: Gene rearrangements statistics associated to bacteremia
DOI: 10.6084/m9.figshare.14738705
title: Additional file 3 of Genome-wide association studies reveal candidate genes associated to bacteraemia caused by ST93-IV CA-MRSA

description: Additional file 3:Supplementary Table 3: Statistics supporting bacteremia in clade 2
DOI: 10.6084/m9.figshare.14738703
title: Additional file 3 of Putative markers for the detection of early-stage bladder cancer selected by urine metabolomics

description: Additional file 3: Table S3. Putative markers and their corresponding prediction results.
DOI: 10.6084/m9.figshare.14738702
title: Additional file 2 of Genome-wide association studies reveal candidate genes associated to bacteraemia caused by ST93-IV CA-MRSA

description: Additional file 2:Supplementary Table 2: Statistics supporting clade specific genes
DOI: 10.6084/m9.figshare.14738700
title: Additional file 2 of Putative markers for the detection of early-stage bladder cancer selected by urine metabolomics

description: Additional file 2: Table S2. The members of marker discovery cohort and independent test cohort.
DOI: 10.6084/m9.figshare.14738699
title: Additional file 1 of Genome-wide association studies reveal candidate genes associated to bacteraemia caused by ST93-IV CA-MRSA

description: Additional file 1:Supplementary Table 1: ST93-IV isolates used in this study with bacteremia gene matrix
DOI: 10.6084/m9.figshare.14738697
title: Additional file 1 of Putative markers for the detection of early-stage bladder cancer selected by urine metabolomics

description: Additional file 1: Table S1. The 922 compounds identified from 124 patients with bladder cancer or hernia.
DOI: 10.6084/m9.figshare.14738655
title: Additional file 1 of Differential chromatin accessibility landscape of gain-of-function mutant p53 tumours

description: Additional file 1: Table S1. TCGA samples with TP53 mutation status. Table S2. The annotated significant differentially accessibility peaks identified in breast and colon cancers. Table S3. Enrichment of CNA events in different distance bins. Tabel S4. Results of TF motif enrichment analysis (related to Fig. 2a-d). Table S5. Enrichment of non-B-form DNA structure in differentially accessible peaks. Table S6. Results from differential gene expression analysis between mutant and wild-type p53 tumours. Table S7. Summary gene list from the differential accessibility, differential expression, and overlap of both.
DOI: 10.6084/m9.figshare.14738652
title: Additional file 1 of A framework for handling missing accelerometer outcome data in trials

description: Additional file 1 The STATA DO-File (.do) provides example code for using multiple imputation with interval regression.
DOI: 10.6084/m9.figshare.14738619
title: Additional file 2 of Reliability of GENEActiv accelerometers to estimate sleep, physical activity, and sedentary time in children

description: Additional file 2.
DOI: 10.6084/m9.figshare.14738594
title: Additional file 1 of Integration of Dual Stress Transcriptomes and Major QTLs from a Pair of Genotypes Contrasting for Drought and Chronic Nitrogen Starvation Identifies Key Stress Responsive Genes in Rice

description: Additional file 1: Supplementary Table 1: All differentially expressed genes identified under N-W+, N + W- and N_W- treatments compared to optimal input supply (N + W+) in root and shoot tissues of IR64 and N22. Supplementary Table 2: Comparison of the expression of N transporters, sensors and regulators under various stress treatments in IR64 and N22. Supplementary Table 3: Comparison of the expression of known transcription factors (TFs) under various stress treatments in IR64 and N22. Supplementary Table 4: Comparison of the expression of novel (not annotated) genes under various stress treatments in IR64 and N22. Supplementary Table 5: Comparison of plant hormone metabolism genes and their receptors under various stress treatments in IR64 and N22. Supplementary Table 6: Comparison of the expression profile of the genes and QTLs known for Nitrogen use efficiency. Supplementary Table 7: Details of primers designed for validation of the DEGs identified from transcriptome analysis by qPCR assay. Supplementary Table 8: SNPs in the two major QTL hotspot regions identified on chromosomes 1 and 6. Supplementary Table 9: Relative water content (%) under optimal and all the three stress conditions measured in an independent experiment. Supplementary Table 10: DEGS identified in genes encoding for major enzymes involved in C and N skeleton. Supplementary Table 11: Details of variations in cis elements between IR64 and N22 genotypes for 20 N transporter, N regulator, TOND1, Dof genes and candidate genes identified from the major QTLs mapped in the present study. Supplementary Table 12: miRNAs in the candidate genes present in interval of the QTL hotspot region identified on chromosome 6. Supplementary Table 13: Comparison of expression of DE ABA related genes under different stress treatments in two rice genotypes N22 and IR64.
DOI: 10.6084/m9.figshare.14738571
title: Additional file 3 of Bone marrow mesenchymal stem cells and their derived exosomes resolve doxorubicin-induced chemobrain: critical role of their miRNA cargo

description: Additional file 3.
DOI: 10.6084/m9.figshare.14738568
title: Additional file 2 of Bone marrow mesenchymal stem cells and their derived exosomes resolve doxorubicin-induced chemobrain: critical role of their miRNA cargo

description: Additional file 2.
DOI: 10.6084/m9.figshare.14738562
title: Additional file 1 of SARS-CoV-2 complete genome sequencing from the Italian Campania region using a highly automated next generation sequencing system

description: Additional file 1: Table S1. Confirmation of unreported variants by S5 and Sanger sequencing.
DOI: 10.6084/m9.figshare.14738534
title: Additional file 2 of SnoRNA copy regulation affects family size, genomic location and family abundance levels

description: Additional file 2: Table S2. Rfam classified snoRNA families and their characteristics. ‘Expressed’ refers to at least one family member expressed, according to our criteria (see Table S1). Average_sum_TPM is the average of the sum of all snoRNA family members across the 21 samples. Num_members and Num_expressed_members are the number of all and expressed members of a family, respectively. Switch refers to the presence of switches between the most abundant member across tissues. Same_host displays TRUE if all expressed members are in the same host gene. Family_covariation is the covariation (see Table S1) of the sum of abundance of all members of a family across tissues. Mean_member_covariation is the mean covariation of each expressed member of a family across tissues.
DOI: 10.6084/m9.figshare.14738531
title: Additional file 1 of SnoRNA copy regulation affects family size, genomic location and family abundance levels

description: Additional file 1: Table S1. Rfam classified snoRNAs and their characteristics. ‘Expressed’ refers to at least 1 TPM of abundance in one of the 21 samples (7 tissues). Average_TPM, Min_TPM and Max_TPM is the average, max and min values, respectively, of the 21 samples. Tissue_most_expressed_in is the tissue where the average abundance of a tissue is the highest. Conservation_score refers to the average of the “phastCons 100 Vertebrates” score for the entire snoRNA divided by the length of the sequence. Alignement_score is the average pairwise sequence identity score for a snoRNA against all the other members of a family. The coefficient of variation (CV = σ / μ * 100, σ being the standard deviation and μ the mean) was calculated from the mean value of each tissue. Genomic_context displays the location of the snoRNA, which could be either coding (in a protein coding gene), noncoding (in a noncoding gene) or intergenic. SNP/nt_1000 is the number of SNP * 1000 divided by the length of the snoRNA.