cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26991193.v1
title: Additional file 16 of Transcriptional and epigenetic changes during tomato yellow leaf curl virus infection in tomato

description: Additional file 16. Datasets. Dataset S1. Total reads from RNAseq, sRNAseq and WGBS-seq. Dataset S2. Gene Set Enrichment Analysis (GSEA) of the differentially expressed genes. Dataset S3. Clustering of the differentially expressed genes. Dataset S4. sRNA-seq statistics. Dataset S5. Differentially expressed tomato siRNA loci (21-, 22- and 24-nt) overlapped with genes at 7 dpi. Dataset S6. Differentially expressed tomato siRNA loci (21-, 22- and 24-nt) overlapped with genes at 14 dpi. Dataset S7. Differentially expressed tomato siRNA loci (21-, 22- and 24-nt) overlapped with genes at 21 dpi. Dataset S8. Differentially expressed tomato siRNA loci (21-, 22- and 24-nt) overlapped with TEs/repeats at 7 dpi. Dataset S9. Differentially expressed tomato siRNA loci (21-, 22- and 24-nt) overlapped with TEs/repeats at 14 dpi. Dataset S10. Differentially expressed tomato siRNA loci (21-, 22- and 24-nt) overlapped with TEs/repeats at 21 dpi. Dataset S11. miRNAs expressed in tomato during TYLCV infection. Dataset S12. Degradome-seq analysis in tomato during TYLCV infection. Dataset S13. Predicted target genes for the sRNAs. Dataset S14. Differentially expressed phasiRNAs in tomato during TYLCV infection. Dataset S15. WGBS statistics.
DOI: 10.6084/m9.figshare.26991256
title: Additional file 6 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.26991259.v1
title: Additional file 7 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.26991268
title: Additional file 10 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 10
DOI: 10.6084/m9.figshare.26991238
title: Additional file 1 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26991241
title: Additional file 2 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26991244
title: Additional file 3 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26991271
title: Additional file 1 of Ribosomal profiling of human endogenous retroviruses in healthy tissues

description: Additional file 1: Supplemental Table 1.
DOI: 10.6084/m9.figshare.26991274
title: Additional file 2 of Ribosomal profiling of human endogenous retroviruses in healthy tissues

description: Additional file 2: Supplemental Table 2.
DOI: 10.6084/m9.figshare.26991238.v1
title: Additional file 1 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26991241.v1
title: Additional file 2 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26991244.v1
title: Additional file 3 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26991247.v1
title: Additional file 4 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.26991223
title: Additional file 2 of Benchmarking splice variant prediction algorithms using massively parallel splicing assays

description: Additional file 2: Table S1. Measured splicing scores and splicing outcomes as well as predicted scores for each of the eight algorithms evaluated for the six benchmarked datasets. Predicted scores from the eight bioinformatic tools for each of the 500,000 randomly selected exonic and near-exonic background variants. SpliceAI predictions against the FGFR2b and FGFR2c annotations for FGFR2 exon IIIc.
DOI: 10.6084/m9.figshare.26991277.v1
title: Additional file 3 of Ribosomal profiling of human endogenous retroviruses in healthy tissues

description: Additional file 3: Supplemental Table 3.
DOI: 10.6084/m9.figshare.26991262.v1
title: Additional file 8 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 8
DOI: 10.6084/m9.figshare.26991268.v1
title: Additional file 10 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 10
DOI: 10.6084/m9.figshare.26991277
title: Additional file 3 of Ribosomal profiling of human endogenous retroviruses in healthy tissues

description: Additional file 3: Supplemental Table 3.
DOI: 10.6084/m9.figshare.26991274.v1
title: Additional file 2 of Ribosomal profiling of human endogenous retroviruses in healthy tissues

description: Additional file 2: Supplemental Table 2.
DOI: 10.6084/m9.figshare.26991229.v1
title: Additional file 4 of Benchmarking splice variant prediction algorithms using massively parallel splicing assays

description: Additional file 4: Table S3. Optimal score thresholds for each tool within the benchmarked datasets and across variant classes as defined in Figure 1B.
DOI: 10.6084/m9.figshare.26991259
title: Additional file 7 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.26991256.v1
title: Additional file 6 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.26991265
title: Additional file 9 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 9
DOI: 10.6084/m9.figshare.26991271.v1
title: Additional file 1 of Ribosomal profiling of human endogenous retroviruses in healthy tissues

description: Additional file 1: Supplemental Table 1.
DOI: 10.6084/m9.figshare.26991265.v1
title: Additional file 9 of Conservation genetics and potential geographic distribution modeling of Corybas taliensis, a small ‘sky Island’ orchid species in China

description: Supplementary Material 9
DOI: 10.6084/m9.figshare.26991223.v1
title: Additional file 2 of Benchmarking splice variant prediction algorithms using massively parallel splicing assays

description: Additional file 2: Table S1. Measured splicing scores and splicing outcomes as well as predicted scores for each of the eight algorithms evaluated for the six benchmarked datasets. Predicted scores from the eight bioinformatic tools for each of the 500,000 randomly selected exonic and near-exonic background variants. SpliceAI predictions against the FGFR2b and FGFR2c annotations for FGFR2 exon IIIc.
DOI: 10.6084/m9.figshare.26991295
title: Additional file 1 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 1: Table S1. MR-PRESSO analysis for the association between gut microbiota and outcomes.
DOI: 10.6084/m9.figshare.26991298
title: Additional file 2 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 2: Table S2. The heterogeneity of gut microbiota instrumental variables.
DOI: 10.6084/m9.figshare.26991298.v1
title: Additional file 2 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 2: Table S2. The heterogeneity of gut microbiota instrumental variables.
DOI: 10.6084/m9.figshare.26991301
title: Additional file 3 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 3: Table S3. The heterogeneity of gut microbiota instrumental variables (28-day survival outcomes for sepsis).
DOI: 10.6084/m9.figshare.26991301.v1
title: Additional file 3 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 3: Table S3. The heterogeneity of gut microbiota instrumental variables (28-day survival outcomes for sepsis).
DOI: 10.6084/m9.figshare.26991304
title: Additional file 4 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 4: Table S4. MR estimates for the association between gut microbiota and other sepsis related infections.
DOI: 10.6084/m9.figshare.26991304.v1
title: Additional file 4 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 4: Table S4. MR estimates for the association between gut microbiota and other sepsis related infections.
DOI: 10.6084/m9.figshare.26991307
title: Additional file 5 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 5: Table S5. The heterogeneity of gut microbiota instrumental variables (other sepsis related infections).
DOI: 10.6084/m9.figshare.26991307.v1
title: Additional file 5 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 5: Table S5. The heterogeneity of gut microbiota instrumental variables (other sepsis related infections).
DOI: 10.6084/m9.figshare.26991310
title: Additional file 6 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 6: Table S6. Directional horizontal pleiotropy assessed by intercept term in MR Egger regression of the association between gut microbiota and outcomes.
DOI: 10.6084/m9.figshare.26991313
title: Additional file 7 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 7: Table S7. The correspondence between SNP and gene.
DOI: 10.6084/m9.figshare.26991310.v1
title: Additional file 6 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 6: Table S6. Directional horizontal pleiotropy assessed by intercept term in MR Egger regression of the association between gut microbiota and outcomes.
DOI: 10.6084/m9.figshare.26991313.v1
title: Additional file 7 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 7: Table S7. The correspondence between SNP and gene.
DOI: 10.34740/kaggle/dsv/9367632
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.6084/m9.figshare.26991295.v1
title: Additional file 1 of Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

description: Additional file 1: Table S1. MR-PRESSO analysis for the association between gut microbiota and outcomes.
DOI: 10.6084/m9.figshare.26991367
title: Additional file 1 of Transcriptional profiling of human cartilage endplate cells identifies novel genes and cell clusters underlying degenerated and non-degenerated phenotypes

description: Additional file 1: Table S1. Number of publications, search terms, and PubMed IDs for all identified papers for all genes in each tissue of interest.
DOI: 10.6084/m9.figshare.26991376
title: Additional file 4 of Transcriptional profiling of human cartilage endplate cells identifies novel genes and cell clusters underlying degenerated and non-degenerated phenotypes

description: Additional file 4: Table S7. Percentage expressed and scaled expressed of differentially expressed genes from bulk RNA sequencing analysis, by cluster.
DOI: 10.6084/m9.figshare.26991379
title: Additional file 5 of Transcriptional profiling of human cartilage endplate cells identifies novel genes and cell clusters underlying degenerated and non-degenerated phenotypes

description: Additional file 5: Table S8. Functional enrichment values and gene lists for Gene Ontology pathways, in chondrocytes.
DOI: 10.6084/m9.figshare.26991382
title: Additional file 6 of Transcriptional profiling of human cartilage endplate cells identifies novel genes and cell clusters underlying degenerated and non-degenerated phenotypes

description: Additional file 6: Table S9. Functional enrichment values and gene lists for Gene Ontology pathways, in progenitor cells.
DOI: 10.6084/m9.figshare.26991430
title: Additional file 2 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 2. Table S1: List of Primers used in qRT-PCR.
DOI: 10.6084/m9.figshare.26991430.v1
title: Additional file 2 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 2. Table S1: List of Primers used in qRT-PCR.
DOI: 10.6084/m9.figshare.26991433
title: Additional file 3 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 3. Table S2: List of all DEGs (up- and downregulated) from the 8- and 72-h timepoints for all breast cancer cell line datasets.
DOI: 10.6084/m9.figshare.26991433.v1
title: Additional file 3 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 3. Table S2: List of all DEGs (up- and downregulated) from the 8- and 72-h timepoints for all breast cancer cell line datasets.
DOI: 10.6084/m9.figshare.26991436
title: Additional file 4 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 4. Table S3: The full list of coherence scores of 14 experimental conditions.
DOI: 10.6084/m9.figshare.26991439.v1
title: Additional file 5 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 5. Table S4: A. The full list of gene set enrichment scores of 14 experimental conditions (corresponding to Fig. S3E).
DOI: 10.6084/m9.figshare.26991442.v1
title: Additional file 6 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 6. Table S4: B. AUC data corresponding to Fig. S3F.
DOI: 10.6084/m9.figshare.26991445.v1
title: Additional file 7 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 7. Table S5: List of CSL binding sites GO annotation and KEGG pathways analysis of the 20-gene signature.
DOI: 10.6084/m9.figshare.26991436.v1
title: Additional file 4 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 4. Table S3: The full list of coherence scores of 14 experimental conditions.
DOI: 10.6084/m9.figshare.26991439
title: Additional file 5 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 5. Table S4: A. The full list of gene set enrichment scores of 14 experimental conditions (corresponding to Fig. S3E).
DOI: 10.6084/m9.figshare.26991442
title: Additional file 6 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 6. Table S4: B. AUC data corresponding to Fig. S3F.
DOI: 10.6084/m9.figshare.26991445
title: Additional file 7 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 7. Table S5: List of CSL binding sites GO annotation and KEGG pathways analysis of the 20-gene signature.
DOI: 10.6084/m9.figshare.26991448
title: Additional file 8 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 8. Table S6: A. List of all identified Notch signatures used and the corresponding signature genes.
DOI: 10.6084/m9.figshare.26991448.v1
title: Additional file 8 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 8. Table S6: A. List of all identified Notch signatures used and the corresponding signature genes.
DOI: 10.6084/m9.figshare.26991451
title: Additional file 9 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 9. Table S6: B. Similarity scores for previously published Notch signatures, as indicated.
DOI: 10.6084/m9.figshare.26991451.v1
title: Additional file 9 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 9. Table S6: B. Similarity scores for previously published Notch signatures, as indicated.
DOI: 10.6084/m9.figshare.26991454
title: Additional file 10 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 10. Table S6: C. Centrality scores for previously published Notch signatures, as indicated and distance measurements for individual genes of each signature.
DOI: 10.6084/m9.figshare.26991454.v1
title: Additional file 10 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 10. Table S6: C. Centrality scores for previously published Notch signatures, as indicated and distance measurements for individual genes of each signature.
DOI: 10.6084/m9.figshare.26991460
title: Additional file 12 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 12. Table S8: List of coherence scores of published signatures in the various patient cohorts (TCGA-BRCA, METABRIC and Oslo2).
DOI: 10.6084/m9.figshare.26991457
title: Additional file 11 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 11. Table S7: A list of the signatures significantly enriched by GSEA (p.adj &lt; 0.05) in the six-cell line training cohort and the larger 19-cell line cohort.
DOI: 10.6084/m9.figshare.26991457.v1
title: Additional file 11 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 11. Table S7: A list of the signatures significantly enriched by GSEA (p.adj &lt; 0.05) in the six-cell line training cohort and the larger 19-cell line cohort.
DOI: 10.6084/m9.figshare.26991463
title: Additional file 13 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 13. Table S9: A. Signature and coherence scores of the 20-gene signature and previously published signatures in all PAM50 subtypes in the various patient cohorts (TCGA-BRCA, METABRIC and Oslo2).
DOI: 10.6084/m9.figshare.26991466
title: Additional file 14 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 14. Table S9: B. Signature scores of the 20-gene signature and previously published signatures in individual samples in the six- and 19-cell line panel and in individual samples of the various patient cohorts (TCGA-BRCA, METABRIC and Oslo2) as well as patient characteristics.
DOI: 10.6084/m9.figshare.26991466.v1
title: Additional file 14 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 14. Table S9: B. Signature scores of the 20-gene signature and previously published signatures in individual samples in the six- and 19-cell line panel and in individual samples of the various patient cohorts (TCGA-BRCA, METABRIC and Oslo2) as well as patient characteristics.
DOI: 10.6084/m9.figshare.26991469.v1
title: Additional file 15 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 15. Table S10: Full list of analysis of tumour purity, stromal and immune infiltration for the different Notch signatures.
DOI: 10.6084/m9.figshare.26991460.v1
title: Additional file 12 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 12. Table S8: List of coherence scores of published signatures in the various patient cohorts (TCGA-BRCA, METABRIC and Oslo2).
DOI: 10.6084/m9.figshare.26991469
title: Additional file 15 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 15. Table S10: Full list of analysis of tumour purity, stromal and immune infiltration for the different Notch signatures.
DOI: 10.6084/m9.figshare.26991472
title: Additional file 16 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 16. Table S11: A. Correlation of signature score of the Notch core signature to published signatures in the cell line and TCGA, METABRIX and Oslo2 patient datasets.
DOI: 10.6084/m9.figshare.26991472.v1
title: Additional file 16 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 16. Table S11: A. Correlation of signature score of the Notch core signature to published signatures in the cell line and TCGA, METABRIX and Oslo2 patient datasets.
DOI: 10.6084/m9.figshare.26991475
title: Additional file 17 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 17. Table S11: B. cBioportal annotations of Notch mutations in the TCGA cohort, ROC analysis and pair-wise correlation results of published signatures in relation to Notch alteration state.
DOI: 10.6084/m9.figshare.26991475.v1
title: Additional file 17 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 17. Table S11: B. cBioportal annotations of Notch mutations in the TCGA cohort, ROC analysis and pair-wise correlation results of published signatures in relation to Notch alteration state.
DOI: 10.6084/m9.figshare.26991478
title: Additional file 18 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 18. Table S12: Ground-state signature score changes of the 20-gene signature and published signatures in the 19 breast cancer cell line cohort.
DOI: 10.6084/m9.figshare.26991478.v1
title: Additional file 18 of Identification of a Notch transcriptomic signature for breast cancer

description: Additional file 18. Table S12: Ground-state signature score changes of the 20-gene signature and published signatures in the 19 breast cancer cell line cohort.