cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.c.3642326_d2.v1
title: Additional file 1: of Comparison of an automatic analysis and a manual analysis of conjunctival microcirculation in a sheep model of haemorrhagic shock

description: Raw data of blood withdrawal, haemodynamics, blood gas analysis and microcirculatory analysis. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.c.3642338_d1.v1
title: Additional file 1: Table S1. of 
                     De novo transcriptome analyses of host-fungal interactions in oil palm (Elaeis guineensis Jacq.)

description: DEGs in G-treated oil palm roots compared to untreated roots. Table S2. DEGs in T-treated oil palm roots compared to untreated roots. Table S3. Fungal transcripts in oil palm transcriptomes. Table S4. List of qRT-PCR primers used for verification of DEGs. (XLSX 833 kb)
DOI: 10.6084/m9.figshare.c.3642350_d23.v1
title: Additional file 2: Table S1. of 
                     De novo transcriptome sequencing and gene expression profiling of Elymus nutans under cold stress

description: Summary of transcripts assembly. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.c.3642350_d24.v1
title: Additional file 9: Table S4. of 
                     De novo transcriptome sequencing and gene expression profiling of Elymus nutans under cold stress

description: Annotation of 4074 DEGs between DX and GN in response to cold stress. (XLSX 1516 kb)
DOI: 10.6084/m9.figshare.c.3642350_d25.v1
title: Additional file 20: Table S14. of 
                     De novo transcriptome sequencing and gene expression profiling of Elymus nutans under cold stress

description: Differently-expressed genes related to ROS producing and scavenging system in response to cold treatment of DX and GN genotypes. (XLSX 397 kb)
DOI: 10.6084/m9.figshare.c.3642350_d27.v1
title: Additional file 18: Table S10. of 
                     De novo transcriptome sequencing and gene expression profiling of Elymus nutans under cold stress

description: List of KEGG pathway enrichment analysis (Q value ≤ 0.05) of specifically expressed genes in DX and GN in response to 3, 24 h, and 5 d of cold stress. (XLSX 358 kb)
DOI: 10.6084/m9.figshare.c.3642350_d29.v1
title: Additional file 15: Table S11. of 
                     De novo transcriptome sequencing and gene expression profiling of Elymus nutans under cold stress

description: Differentially expressed transcription factors (TFs) in response to cold treatment of DX and GN genotypes. DX-specific TFs are color-coded with pale yellow shaded. GN-specific TFs are color-coded with light green shaded. Common expression TFs are color-coded with gray shaded. Significant (Pâ  &gt;â  0.8) decrease of transcript abundance is highlighted in blue and bold, significant transcript increase is highlighted in red and bold. (XLSX 490 kb)
DOI: 10.6084/m9.figshare.c.3642353_d6.v1
title: Additional file 1: Table S1. of Identification of global regulators of T-helper cell lineage specification

description: Reads obtained from next-generation sequencing data. (XLSX 43 kb)
DOI: 10.6084/m9.figshare.c.3642353_d7.v1
title: Additional file 9: Table S6. of Identification of global regulators of T-helper cell lineage specification

description: List of Th1- and Th2-specific long non-coding RNAs. (XLSX 97 kb)
DOI: 10.6084/m9.figshare.c.3642353_d10.v1
title: Additional file 8: Table S5. of Identification of global regulators of T-helper cell lineage specification

description: Novel list of Th1- and Th2-specific genes in human. (XLSX 122 kb)
DOI: 10.6084/m9.figshare.c.3642353_d13.v1
title: Additional file 6: Table S3. of Identification of global regulators of T-helper cell lineage specification

description: Table showing Pearson correlation coefficients between platforms. (XLSX 34 kb)
DOI: 10.6084/m9.figshare.c.3642398_d1.v1
title: MOESM1 of Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends

description: Additional file 1. Additional Tables.
DOI: 10.6084/m9.figshare.c.3642404_d4.v1
title: Additional file 2: of Genome mining for natural product biosynthetic gene clusters in the Subsection V cyanobacteria

description: W. intricata UH strain HT-29-1 and H. welwitschii UH strain IC-52-3 102 housekeeping genes, COGs. (XLSX 118 kb)
DOI: 10.6084/m9.figshare.c.3642413_d1.v1
title: Additional file 4: of Metassembler: merging and optimizing de novo genome assemblies

description: A1Zscores.txt: Zscores for all metrics and Overall Zscore for all metassemblies and input assemblies. (TXT 11 kb)
DOI: 10.6084/m9.figshare.c.3642413_d2.v1
title: Additional file 5: of Metassembler: merging and optimizing de novo genome assemblies

description: A2MetEventsTable.txt: Reported metassembly events for all Assemblathon2 metassemblies of the three species at each merging step. (TXT 1 kb)
DOI: 10.6084/m9.figshare.c.3642413_d5.v1
title: Additional file 3: of Metassembler: merging and optimizing de novo genome assemblies

description: A1metricTable.txt: GAGE reported assembly evaluation metrics for all Assemblathon1 metassemblies at each step. (TXT 206 kb)
DOI: 10.6084/m9.figshare.c.3642452_d6.v1
title: Additional file 2: Table S1. of The PfAlba1 RNA-binding protein is an important regulator of translational timing in Plasmodium falciparum blood stages

description: List of transcripts that co-immunoprecipitated with PfAlba1-Ty1 complexes in trophozoite stages. (XLS 435 kb)
DOI: 10.6084/m9.figshare.c.3642452_d7.v1
title: Additional file 7: Table S6. of The PfAlba1 RNA-binding protein is an important regulator of translational timing in Plasmodium falciparum blood stages

description: Gene Ontology (GO) analysis of 926 transcripts that were differentially regulated in PfAlba1-Ty1 trophozoites. (XLS 115 kb)
DOI: 10.6084/m9.figshare.c.3642452_d8.v1
title: Additional file 4: Table S3. of The PfAlba1 RNA-binding protein is an important regulator of translational timing in Plasmodium falciparum blood stages

description: List of transcripts that bound to GST-PfAlba1 in vitro. (XLS 232 kb)
DOI: 10.6084/m9.figshare.c.3642452_d10.v1
title: Additional file 8: Table S7. of The PfAlba1 RNA-binding protein is an important regulator of translational timing in Plasmodium falciparum blood stages

description: List of transcripts that were over twofold differentially regulated in PfAlba1-Ty1 trophozoites and that were bound directly by PfAlba1 in vivo and in vitro. (XLS 42 kb)
DOI: 10.6084/m9.figshare.c.3642452_d9.v1
title: Additional file 5: Table S4. of The PfAlba1 RNA-binding protein is an important regulator of translational timing in Plasmodium falciparum blood stages

description: Gene Ontology (GO) analysis of transcripts that bound to GST-PfAlba1 in vitro. (XLS 266 kb)
DOI: 10.6084/m9.figshare.c.3642452_d11.v1
title: Additional file 9: Table S8. of The PfAlba1 RNA-binding protein is an important regulator of translational timing in Plasmodium falciparum blood stages

description: List of transcripts identified by Foth et al. [16] and Caro et al. [19] as being translationally regulated in Plasmodium falciparum asexual blood stages. (XLS 80 kb)
DOI: 10.6084/m9.figshare.c.3642458_d3.v1
title: Additional file 1: of Bicycle helmet laws and persistent racial and ethnic helmet use disparities among urban high school students: a repeated cross-sectional analysis

description: Appendix C: Analysis Code. (RTF 10Â kb)
DOI: 10.5519/qd.7i9yfdmh
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (18 records)
DOI: 10.21227/ddfa-mf77
title: Maternal Health and High-Risk Pregnancy Dataset.

description: This dataset provides a comprehensive collection of maternal health data, focusing on key health indicators throughout pregnancy. It includes essential details such as the mother’s age, gravida (number of pregnancies), weight, height, blood pressure, gestational age, and fetal health status. In addition to these primary metrics, the dataset captures important medical test results, including anemia, blood sugar levels, and fetal heart rate, providing a thorough overview of both maternal and fetal well-being. The dataset categorizes pregnancies into high-risk and non-high-risk based on various factors such as abnormal blood pressure readings, test results, and fetal health conditions. This classification can be vital for prenatal care and early risk detection, facilitating interventions for at-risk pregnancies. Collected manually from healthcare records, the dataset ensures data accuracy and reliability. Each entry has been anonymized to protect patient privacy and guarantee ethical standards. This dataset serves as an invaluable resource for research in maternal health, predictive analytics, and pregnancy outcome studies. It can be used for developing models to assess pregnancy risks, guide healthcare interventions, and improve prenatal care strategies globally. Researchers, healthcare professionals, and data scientists can leverage this dataset to gain deeper insights into pregnancy-related health trends and explore potential factors influencing maternal and fetal health outcomes.
DOI: 10.6084/m9.figshare.c.3642476_d1.v1
title: Additional file 2: Table S1. of A combination of TERT promoter mutation and MGMT methylation status predicts clinically relevant subgroups of newly diagnosed glioblastomas

description: Molecular and clinical characteristics of Cohort 1 (n = 758). Table S2. Molecular and clinical characteristics of GBM cohort (n = 453). Table S3. Univariate and multivariate Cox regression analyses for Group A (IDH mutated-TERT mutated) tumors in Cohort 1 (n = 155). Table S4. Univariate and multivariate Cox regression analyses for Group B (IDH mutated-TERT wild-type) tumors in Cohort 1 (n = 131). Table S5. Univariate and multivariate Cox regression analyses for Group C (IDH wild-type-TERT wild-type) tumors in Cohort 1 (n = 237). Table S6. Univariate and multivariate Cox regression analyses for Group D (IDH wild-type-TERT mutated) tumors in Cohort 1 (n = 235). Table S7. Univariate and multivariate Cox regression analyses for GBM in Cohort 1 (n = 260). Table S8. Univariate and multivariate Cox regression analyses for GBM in Cohort 2 (n = 193). Table S9. Background of combined GBM cohort stratified by TERT and MGMT status (n = 453). Table S10. Survival time and WHO grade in each molecular subgroup of Cohort 1 (n = 758). (XLSX 254 kb)
DOI: 10.6084/m9.figshare.c.3642503_d2.v1
title: Additional file 2: of Nationwide study of factors associated with publicâ  s willingness to use home self-test kit for dengue fever in Malaysia

description: Dengue Public Nationwide. (SAV 1.07 mb)
DOI: 10.6084/m9.figshare.c.3642512_d1.v1
title: Additional file 1: Figure S1. of 
                     Mycobacterium tuberculosis secretory proteins downregulate T cell activation by interfering with proximal and downstream T cell signalling events

description: (A-C) Lymphocyte transformation test for dose optimisation of Ag85A, ESAT-6 and H37Rv by using PBMCs of healthy individuals (N = 10) and pulmonary TB (N = 10) patients using H3-thymidine uptake assay. PHA and PPD were used as positive control and wells with unstimulated cells were taken as control. Lymphoproliferative responses of healthy individuals and pulmaonary TB patients were calculated using different concentration (2.5, 5, 7.5, 10, 15, μg/ml) of antigens. Bar diagram showing mean ± SEM of stimulation indices (S.I) of stimulated PBMC’s with different doses of PHA, PPD, A85A, ESAT-6 and H37Rv. S.I was calculated according to the formula: S I = Mean counts per minute of experimental wells Mean counts per minute of control wells $$ \mathrm{S}\mathrm{I}=\frac{\mathrm{Mean}\ \mathrm{counts}\ \mathrm{per}\ \mathrm{minute}\ \mathrm{of}\ \mathrm{experimental}\ \mathrm{wells}}{\mathrm{Mean}\ \mathrm{counts}\ \mathrm{per}\ \mathrm{minute}\ \mathrm{of}\ \mathrm{control}\ \mathrm{wells}} $$ (ZIP 160 kb)
DOI: 10.6084/m9.figshare.c.3642524_d1.v1
title: Additional file 2: of Multiplicative interaction of functional inflammasome genetic variants in determining the risk of gout

description: Genotype distributions. Excel file with genotype distributions in the European and Polynesian sample sets for each of the single nucleotide polymorphisms (SNPs) studied. (XLSX 20 kb)
DOI: 10.6084/m9.figshare.c.3642521_d1.v1
title: MOESM1 of Systematic review of human immunodeficiency virus (HIV) knowledge measurement instruments used on the Arabian Peninsula

description: Additional file 1: Table S1. Articles on HIV/AIDS knowledge and attitudes questionnaires reviewed.
DOI: 10.6084/m9.figshare.c.3642542_d2.v1
title: Additional file 1: of Prediction of scaffold proteins based on protein interaction and domain architectures

description: It contains gold standard positive set, gold negative set and predicted scaffold proteins with type. (XLSX 106Â kb)
DOI: 10.6084/m9.figshare.c.3642542_d1.v1
title: Additional file 2: of Prediction of scaffold proteins based on protein interaction and domain architectures

description: It contains results of functional enrichment using DAVID. (P-value
DOI: 10.5281/zenodo.14509805
title: ChlOSP output from a CESM2 Ocean Hindcast Simulation

description: This dataset was generated from an ocean–sea-ice hindcast simulation of the Community Earth System Model version 2 (CESM2). These files contain the simulated satellite observations from the Chlorophyll Observation Simulator Package (ChlOSP). The variables include the weighted SST and chlorophyll fields, along with their respective weights.

This simulation utilized the GOMIPECOIAF_JRA-1p4-2018 component set, which uses the JRA55 (version 1.4) atmospheric reanalysis. The JRA forcing starts in 1958 and runs through 2019 (61 years). The model was run through two cycles of the forcing data (i.e., 122 years) to allow the ocean state to adjust to the forcing from the reanalysis atmospheric forcing. We analyze years 2003 to 2016 to compare with satellite data over the same time period.
DOI: 10.5281/zenodo.14509806
title: ChlOSP output from a CESM2 Ocean Hindcast Simulation

description: This dataset was generated from an ocean–sea-ice hindcast simulation of the Community Earth System Model version 2 (CESM2). These files contain the simulated satellite observations from the Chlorophyll Observation Simulator Package (ChlOSP). The variables include the weighted SST and chlorophyll fields, along with their respective weights.

This simulation utilized the GOMIPECOIAF_JRA-1p4-2018 component set, which uses the JRA55 (version 1.4) atmospheric reanalysis. The JRA forcing starts in 1958 and runs through 2019 (61 years). The model was run through two cycles of the forcing data (i.e., 122 years) to allow the ocean state to adjust to the forcing from the reanalysis atmospheric forcing. We analyze years 2003 to 2016 to compare with satellite data over the same time period.
DOI: 10.6084/m9.figshare.c.3642599_d2.v1
title: Additional file 3: Table S3. of Gender-specific effects of intrauterine growth restriction on the adipose tissue of adult rats: a proteomic approach

description: Protein name, gene name and biological process of the proteins identified in the adipose tissue of females. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.c.3642599_d1.v1
title: Additional file 2: Table S2. of Gender-specific effects of intrauterine growth restriction on the adipose tissue of adult rats: a proteomic approach

description: Protein name, gene name and biological process of the proteins identified in the adipose tissue of males. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.c.3642599_d3.v1
title: Additional file 1: Table S1. of Gender-specific effects of intrauterine growth restriction on the adipose tissue of adult rats: a proteomic approach

description: Optic density of the spots with significant differences between the control and the restricted groups. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.c.3642614_d1.v1
title: Additional file 1: of Revisiting the taxonomical classification of Porcine Circovirus type 2 (PCV2): still a real challenge

description: Spreadsheet containing the datasets used in the present study. For ORF2, the clustering according to NJ and ML phylogenetic trees is included. The list of Acc.Num of reference strains is also reported. (XLS 313 kb)
DOI: 10.6084/m9.figshare.c.3642623_d1.v1
title: Additional file 6: of Exploring transcriptomic diversity in muscle revealed that cellular signaling pathways mainly differentiate five Western porcine breeds

description: EASE systematic functional annotation for the 683 unique differentially expressed genes. Detailed functional information were obtained from EASE (Expression Analysis Systematic Explorer) from DAVID (Database for Annotation, Visualization and Integrated Discovery) is given for each known gene when available: Official Gene Symbol, Gene identifiers (the human ortholog), Gene Name, Gene Ontology for Biological Process, Cellular Component and Molecular Function, KEGG pathway and a Function Summary (XLSX 178Â kb)
DOI: 10.6084/m9.figshare.c.3642617_d1.v1
title: Additional file 1: of Impact of prognostic nutritional index on long-term outcomes in patients with breast cancer

description: The raw data of this study.
DOI: 10.6084/m9.figshare.c.3642623_d2.v1
title: Additional file 5: of Exploring transcriptomic diversity in muscle revealed that cellular signaling pathways mainly differentiate five Western porcine breeds

description: 228 spots (171 unique genes) allow the discrimination between the five lines. These genes were identified as differentially expressed from one line against the others or were identified in the sPLS-DA or Random Forest analysis. The 15 discriminant genes with the three methods are highlighted. DU: Duroc; LWF: Large White dam line; LWM: Large White sire line; LR: Landrace; PI: PiĂŠtrain. (XLSX 69Â kb)
DOI: 10.6084/m9.figshare.c.3642623_d4.v1
title: Additional file 2: of Exploring transcriptomic diversity in muscle revealed that cellular signaling pathways mainly differentiate five Western porcine breeds

description: Annotation of the regulated genes. This list of probes corresponds to the differential probes from the linear mixed model, the pairwise analysis and the discriminating analysis. From this list, 1,394 probes were localized on porcine chromosomes (XLSX 650Â kb)
DOI: 10.6084/m9.figshare.c.3642623_d5.v1
title: Additional file 1: of Exploring transcriptomic diversity in muscle revealed that cellular signaling pathways mainly differentiate five Western porcine breeds

description: 1,859 genes were identified to be differentially expressed between five breeds according to statistical analysis. 1,703 were differentially expressed with a linear mixed model (FDR
DOI: 10.6084/m9.figshare.c.3642623_d3.v1
title: Additional file 3: of Exploring transcriptomic diversity in muscle revealed that cellular signaling pathways mainly differentiate five Western porcine breeds

description: Differentially expressed genes on autosomes. Only probes with an alignment on the porcine genome Sscrofa10.2 are reported with the corresponding annotation from Ensembl. The global and pairwise statistics are given for all the comparisons. DU: Duroc; LWF: Large White dam line; LWM: Large sire Male line; LR: Landrace; PI: PiĂŠtrain (XLSX 689Â kb)
DOI: 10.6084/m9.figshare.c.3642623_d6.v1
title: Additional file 4: of Exploring transcriptomic diversity in muscle revealed that cellular signaling pathways mainly differentiate five Western porcine breeds

description: 70 pathways enriched to explain the biologically diversity of five pig breeds. These pathways have been identified with the free software GeneCodis. These pathways concerned the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways which included the signaling and metabolic pathways. The pathways declared enriched have an adjusted p-value
DOI: 10.6084/m9.figshare.c.3642665_d2.v1
title: Additional file 4: of Effective strategies to reduce commercial tobacco use in Indigenous communities globally: A systematic review

description: Title of data: Intervention Activity and Outcome Efficacy Data. Description of data: Summary comparison of intervention characteristics and efficacy data for the seven outcomes. (XLSX 18 kb)
DOI: 10.6084/m9.figshare.c.3642680_d4.v1
title: MOESM2 of The chicken erythrocyte epigenome

description: Additional file 2. Gene ranking according to expression levels in chicken polychromatic erythrocytes. All 5479 genes from the galGal3 RefSeq database were placed in order of their level of expression (mean RPKM from two biological samples) and were then divided into five 20th-percentile classes in relation to expression level. First 20 %-ile (red filled), second 20 %-ile (green filled), third 20 %-ile (blue filled), fourth 20 %-ile (dark blue filled) and fifth 20 %-ile (violet filled).
DOI: 10.6084/m9.figshare.c.3642680_d1.v1
title: MOESM5 of The chicken erythrocyte epigenome

description: Additional file 5. Sense and antisense transcript reads for the 1095 genes from the galGal3 RefSeq database belonging to the first 20th-percentile.
DOI: 10.6084/m9.figshare.c.3642680_d3.v1
title: MOESM8 of The chicken erythrocyte epigenome

description: Additional file 8. Table with information regarding all sequencing tracks shown in this study (total read counts, mapped read counts, MAPQ threshold and median, percentage of reads uniquely mapped).
DOI: 10.6084/m9.figshare.c.3642680_d5.v1
title: MOESM3 of The chicken erythrocyte epigenome

description: Additional file 3. Validation of RNA-seq data by RT-qPCR. Comparison of RPKM values from RNA-seq analyses with RNA levels determined by RT-qPCR assays for specific genes. Transcript levels were normalized to 18S rRNA levels. * Three RT-qPCR assays were done on three different RNA preparations from Sample 3.
DOI: 10.6084/m9.figshare.c.3642731_d1.v1
title: Additional file 2: Figure S1. of Properties of Boolean dynamics by node classification using feedback loops in a network

description: Comparison between groups of NFD and non-NFD genes in random networks with respect to the proportions of essential genes, disease genes, and drug targets. In each subfigure, a set of 100 random networks were generated by rewiring the interactions of the signaling networks such that the in-degree and the out-degree of all nodes are conserved. (A) Result of random networks shuffled from KEGG network. The average numbers of NFD and non-NFD genes were 509 and 1150, respectively. The average proportions of essential genes in the NFD and the non-NFD groups were 0.2849 and 0.2852, respectively. The proportions of disease genes in the NFD and the non-NFD groups were 0.2417 and 0.2435, respectively. The proportions of drug-targets in the NFD and the non-NFD groups were 0.2141 and 0.2122, respectively. (B) Result of random networks shuffled from WANG network. The average numbers of NFD and non-NFD genes were 1544 and 4761, respectively. The proportions of essential genes in the NFD and the non-NFD groups were 0.2390 and 0.2413, respectively. The proportions of disease genes in the NFD and the non-NFD groups were 0.2455 and 0.2472, respectively. The proportions of drug-targets in the NFD and the non-NFD groups were 0.1768 and 0.1769, respectively. Figure S2. Changes in the proportion of functionally important genes over the threshold value of the perturbation-sustainable probability in random networks. In each subfigure, a set of 100 random networks were generated by rewiring the interactions of the signaling network such that the in-degree and the out-degree of all nodes are conserved. Given a threshold value β, the y-axis values indicate the average proportions of essential genes, disease genes, and drug targets over the set of candidate genes whose perturbation-sustainable probability is larger than or equal to β in random networks. (A) Results in random networks shuffled from KEGG network. For a reliable comparison, the maximal β was set to 0.0266 which generates 131 candidate genes on average. (B) Results in random networks shuffled from WANG network. The maximal β was set to 0.0908, which results in 121 candidate genes on average. (ZIP 362 kb)