cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12285194
title: Additional file 5 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 5: Table S5. Resistance genes found using IslandViewer for all nine V. alginolyticus strains from the Kiel-Fjord. Even though this table shows the locus tags for strain K04M3 only, all other strains have been found to contain the exact same resistance genes.
DOI: 10.6084/m9.figshare.12285191
title: Additional file 4 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 4: Table S4. Functional annotation of Kiel specific gene clusters (core genome [C], accessory genes [A], singletons [S], i.e. gene cluster which was only found within the Kiel alginolyticus ecotype with the resulting COG assignments.
DOI: 10.6084/m9.figshare.12285194.v1
title: Additional file 5 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 5: Table S5. Resistance genes found using IslandViewer for all nine V. alginolyticus strains from the Kiel-Fjord. Even though this table shows the locus tags for strain K04M3 only, all other strains have been found to contain the exact same resistance genes.
DOI: 10.6084/m9.figshare.12285185
title: Additional file 3 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 3: Table S3. Functional characterization of all protein-coding sequences found on the Genomic Regions (using the eggNOG-mapper v2 software) with the resulting COG assignments. Similar to Table S2 we used strain K10K4 as reference for chromosome 1 and strain K04M3 as reference for chromosome 2. The column Kiel Specific indicates whether the GR is unique for the Kiel alginolyticus ecotype.
DOI: 10.6084/m9.figshare.12285179
title: Additional file 2 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 2: Table S2. Genomic regions (GRs) unique for the nine V. alginolyticus strains from the Kiel-Fjord. For chromosome 1 (left) we used K10K4 as a reference, as this strain has more integrated prophages than the other Kiel isolates. For the same reason, we used strain K04M3 as a reference for chromosome 2. For a detailed comparison of GRs among all nine strains, see Fig. 3 main manuscript.
DOI: 10.6084/m9.figshare.12285185.v1
title: Additional file 3 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 3: Table S3. Functional characterization of all protein-coding sequences found on the Genomic Regions (using the eggNOG-mapper v2 software) with the resulting COG assignments. Similar to Table S2 we used strain K10K4 as reference for chromosome 1 and strain K04M3 as reference for chromosome 2. The column Kiel Specific indicates whether the GR is unique for the Kiel alginolyticus ecotype.
DOI: 10.6084/m9.figshare.12285191.v1
title: Additional file 4 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 4: Table S4. Functional annotation of Kiel specific gene clusters (core genome [C], accessory genes [A], singletons [S], i.e. gene cluster which was only found within the Kiel alginolyticus ecotype with the resulting COG assignments.
DOI: 10.6084/m9.figshare.12285173
title: Additional file 1 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 1: Table S1.Vibrio genomes accessed from NCBI 3.12.2019 used for PyANI analysis.
DOI: 10.6084/m9.figshare.12285179.v1
title: Additional file 2 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 2: Table S2. Genomic regions (GRs) unique for the nine V. alginolyticus strains from the Kiel-Fjord. For chromosome 1 (left) we used K10K4 as a reference, as this strain has more integrated prophages than the other Kiel isolates. For the same reason, we used strain K04M3 as a reference for chromosome 2. For a detailed comparison of GRs among all nine strains, see Fig. 3 main manuscript.
DOI: 10.6084/m9.figshare.12285167
title: Additional file 5 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 5: Table S4. Hub genes correlated with Gleason score via WGCNA analysis.
DOI: 10.6084/m9.figshare.12285173.v1
title: Additional file 1 of Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements

description: Additional file 1: Table S1.Vibrio genomes accessed from NCBI 3.12.2019 used for PyANI analysis.
DOI: 10.6084/m9.figshare.12285167.v1
title: Additional file 5 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 5: Table S4. Hub genes correlated with Gleason score via WGCNA analysis.
DOI: 10.6084/m9.figshare.12285158
title: Additional file 3 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 3: Table S3. Differentially expressed genes in TCGA-PRAD.
DOI: 10.6084/m9.figshare.12285158.v1
title: Additional file 3 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 3: Table S3. Differentially expressed genes in TCGA-PRAD.
DOI: 10.6084/m9.figshare.12285140
title: Additional file 15 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 15: Table S9. Correlation between risk score and immune cells infiltration.
DOI: 10.6084/m9.figshare.12285137
title: Additional file 4 of MyoMiner: explore gene co-expression in normal and pathological muscle

description: Additional file 4. Table S9. The panel of 20 muscle-relevant genes used for validation of MyoMiner co-expression values. This panel is based on muscle-relevant annotations, and frequency of representation in consensus lists of the Muscle Gene Sets collection.
DOI: 10.6084/m9.figshare.12285140.v1
title: Additional file 15 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 15: Table S9. Correlation between risk score and immune cells infiltration.
DOI: 10.6084/m9.figshare.12285128
title: Additional file 13 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 13: Table S7. The results of GSVA analysis.
DOI: 10.6084/m9.figshare.12285131
title: Additional file 3 of MyoMiner: explore gene co-expression in normal and pathological muscle

description: Additional file 3. Table S8. Complete listing of data series IDs for murine experiments.
DOI: 10.6084/m9.figshare.12285134
title: Additional file 14 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 14: Table S8. CIBERSORT Output matrix.
DOI: 10.6084/m9.figshare.12285137.v1
title: Additional file 4 of MyoMiner: explore gene co-expression in normal and pathological muscle

description: Additional file 4. Table S9. The panel of 20 muscle-relevant genes used for validation of MyoMiner co-expression values. This panel is based on muscle-relevant annotations, and frequency of representation in consensus lists of the Muscle Gene Sets collection.
DOI: 10.6084/m9.figshare.12285128.v1
title: Additional file 13 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 13: Table S7. The results of GSVA analysis.
DOI: 10.6084/m9.figshare.12285122
title: Additional file 2 of MyoMiner: explore gene co-expression in normal and pathological muscle

description: Additional file 2. Table S7. Complete listing of data series IDs for human experiments.
DOI: 10.6084/m9.figshare.12285134.v1
title: Additional file 14 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 14: Table S8. CIBERSORT Output matrix.
DOI: 10.6084/m9.figshare.12285122.v1
title: Additional file 2 of MyoMiner: explore gene co-expression in normal and pathological muscle

description: Additional file 2. Table S7. Complete listing of data series IDs for human experiments.
DOI: 10.6084/m9.figshare.12285131.v1
title: Additional file 3 of MyoMiner: explore gene co-expression in normal and pathological muscle

description: Additional file 3. Table S8. Complete listing of data series IDs for murine experiments.
DOI: 10.6084/m9.figshare.12285119
title: Additional file 12 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 12: Table S6. The results of GSEA analysis.
DOI: 10.6084/m9.figshare.12285119.v1
title: Additional file 12 of A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

description: Additional file 12: Table S6. The results of GSEA analysis.
DOI: 10.6084/m9.figshare.12285065
title: Additional file 9 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 9. In this file we provide the result of C _ score values. For each edge in the bipartite network, we provide the disease cluster and gene cluster corresponding to the edge as well as its C _ score value. In addition, we provide C _ score value of random gene-disease cluster corresponding to each edge which was calculated by 1000 random experiments.
DOI: 10.6084/m9.figshare.12285065.v1
title: Additional file 9 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 9. In this file we provide the result of C _ score values. For each edge in the bipartite network, we provide the disease cluster and gene cluster corresponding to the edge as well as its C _ score value. In addition, we provide C _ score value of random gene-disease cluster corresponding to each edge which was calculated by 1000 random experiments.
DOI: 10.6084/m9.figshare.12285053
title: Additional file 7 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 7. In this file we provide the result of similarities of disease clusters and random disease clusters. In sheet 1 of this file the information of diseases with ID is listed. In sheet 2 of this file the results of disease clusters corresponding to each gene are shown. In sheet 3 of this file the similarity of disease clusters corresponding to each gene and the average similarity of 10,000 random disease clusters with same size are provided. In sheet 4 of this file the average similarity of disease clusters and the average similarity of random disease clusters for each size are given.
DOI: 10.6084/m9.figshare.12285059
title: Additional file 8 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 8. In this file we provide the result of functional similarity of gene clusters and random gene clusters. In sheet 1 of this file the information of genes with ID is listed. In sheet 2 of this file the result of gene clusters corresponding to each disease is given. In sheet 3 of this file the similarity of gene clusters corresponding to each disease and the average similarity of 10,000 random gene clusters with same size are shown. In sheet 4 of this file the average similarity of gene clusters and the average similarity of random gene clusters for each size are provided.
DOI: 10.6084/m9.figshare.12285059.v1
title: Additional file 8 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 8. In this file we provide the result of functional similarity of gene clusters and random gene clusters. In sheet 1 of this file the information of genes with ID is listed. In sheet 2 of this file the result of gene clusters corresponding to each disease is given. In sheet 3 of this file the similarity of gene clusters corresponding to each disease and the average similarity of 10,000 random gene clusters with same size are shown. In sheet 4 of this file the average similarity of gene clusters and the average similarity of random gene clusters for each size are provided.
DOI: 10.6084/m9.figshare.12285047
title: Additional file 6 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 6. In this file we provide the information of raw data. In sheet 1 of this file the serial numbers of genes and diseases are given. In sheet 2 of this file the edges in the bipartite network are given. In sheet 3 of this file the concrete information about the abbreviations of diseases is provided. In sheet 4 of this file the concrete information about the abbreviations of genes is provided.
DOI: 10.6084/m9.figshare.12285053.v1
title: Additional file 7 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 7. In this file we provide the result of similarities of disease clusters and random disease clusters. In sheet 1 of this file the information of diseases with ID is listed. In sheet 2 of this file the results of disease clusters corresponding to each gene are shown. In sheet 3 of this file the similarity of disease clusters corresponding to each gene and the average similarity of 10,000 random disease clusters with same size are provided. In sheet 4 of this file the average similarity of disease clusters and the average similarity of random disease clusters for each size are given.
DOI: 10.6084/m9.figshare.12285047.v1
title: Additional file 6 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 6. In this file we provide the information of raw data. In sheet 1 of this file the serial numbers of genes and diseases are given. In sheet 2 of this file the edges in the bipartite network are given. In sheet 3 of this file the concrete information about the abbreviations of diseases is provided. In sheet 4 of this file the concrete information about the abbreviations of genes is provided.
DOI: 10.6084/m9.figshare.12285035
title: Additional file 7 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 7. List of PBM experiments used.
DOI: 10.6084/m9.figshare.12285038
title: Additional file 5 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 5. In this file we provide the result of 1000 resampling experiments at different thresholds.
DOI: 10.6084/m9.figshare.12285038.v1
title: Additional file 5 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 5. In this file we provide the result of 1000 resampling experiments at different thresholds.
DOI: 10.6084/m9.figshare.12285026
title: Additional file 6 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 6. Annotation of TFs and motifs.
DOI: 10.6084/m9.figshare.12285029
title: Additional file 4 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 4. In this file we provide the datasets used for cross-validation. In sheet 1 of this file the 236 lncRNA-disease associations from the work of Yang are given. In sheet 2 of this file the 1541 lncRNA-disease associations from the Lnc2Cancer 2.0 database are given.
DOI: 10.6084/m9.figshare.12285035.v1
title: Additional file 7 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 7. List of PBM experiments used.
DOI: 10.6084/m9.figshare.12285026.v1
title: Additional file 6 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 6. Annotation of TFs and motifs.
DOI: 10.6084/m9.figshare.12285029.v1
title: Additional file 4 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 4. In this file we provide the datasets used for cross-validation. In sheet 1 of this file the 236 lncRNA-disease associations from the work of Yang are given. In sheet 2 of this file the 1541 lncRNA-disease associations from the Lnc2Cancer 2.0 database are given.
DOI: 10.6084/m9.figshare.12285014
title: Additional file 5 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 5. Interactive t-SNE plots for PBM benchmarks.
DOI: 10.6084/m9.figshare.12285017
title: Additional file 2 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 2. In this file we provide the results of prediction.
DOI: 10.6084/m9.figshare.12285014.v1
title: Additional file 5 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 5. Interactive t-SNE plots for PBM benchmarks.
DOI: 10.6084/m9.figshare.12284996
title: Additional file 3 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 3. Interactive t-SNE plots for HT-SELEX (cut-off 10%).
DOI: 10.6084/m9.figshare.12285002
title: Additional file 4 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 4. Interactive t-SNE plots for HT-SELEX (cut-off 50%).
DOI: 10.6084/m9.figshare.12285017.v1
title: Additional file 2 of Cluster correlation based method for lncRNA-disease association prediction

description: Additional file 2. In this file we provide the results of prediction.
DOI: 10.6084/m9.figshare.12284990
title: Additional file 2 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 2. Interactive t-SNE plots for ChIP-seq benchmarks.
DOI: 10.6084/m9.figshare.12285002.v1
title: Additional file 4 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 4. Interactive t-SNE plots for HT-SELEX (cut-off 50%).
DOI: 10.6084/m9.figshare.12284996.v1
title: Additional file 3 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 3. Interactive t-SNE plots for HT-SELEX (cut-off 10%).
DOI: 10.6084/m9.figshare.12284990.v1
title: Additional file 2 of Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study

description: Additional file 2. Interactive t-SNE plots for ChIP-seq benchmarks.
DOI: 10.6084/m9.figshare.12284852
title: Additional file 3 of Defining the relative and combined contribution of CTCF and CTCFL to genomic regulation

description: Table S2. HiC-bench filter stats. The filter stats of HiC experiments using all transgenes (CTCF, CTCFL, CLC, LCL) under conditions of U, I, D and ID.
DOI: 10.6084/m9.figshare.12284852.v1
title: Additional file 3 of Defining the relative and combined contribution of CTCF and CTCFL to genomic regulation

description: Table S2. HiC-bench filter stats. The filter stats of HiC experiments using all transgenes (CTCF, CTCFL, CLC, LCL) under conditions of U, I, D and ID.
DOI: 10.6084/m9.figshare.12284843
title: Additional file 2 of Defining the relative and combined contribution of CTCF and CTCFL to genomic regulation

description: Table S1. Differentially expressed genes after CTCF degradation and CTCFL induction. Genes upregulated and downregulated under conditions, CTCF U vs I, CTCFL U vs D and CTCFL U vs ID are listed. Log2 fold change and adjusted p values are given in each case.
DOI: 10.6084/m9.figshare.12284843.v1
title: Additional file 2 of Defining the relative and combined contribution of CTCF and CTCFL to genomic regulation

description: Table S1. Differentially expressed genes after CTCF degradation and CTCFL induction. Genes upregulated and downregulated under conditions, CTCF U vs I, CTCFL U vs D and CTCFL U vs ID are listed. Log2 fold change and adjusted p values are given in each case.
DOI: 10.6084/m9.figshare.12284807
title: Additional file 7 of Sampling time-dependent artifacts in single-cell genomics studies

description: Additional file 7: Table 6. scRNA-seq and scATAC-seq quality control metrics stratified by time, donor and temperature in both experiments (PBMC and CLL).
DOI: 10.6084/m9.figshare.12284807.v1
title: Additional file 7 of Sampling time-dependent artifacts in single-cell genomics studies

description: Additional file 7: Table 6. scRNA-seq and scATAC-seq quality control metrics stratified by time, donor and temperature in both experiments (PBMC and CLL).
DOI: 10.6084/m9.figshare.12284798
title: Additional file 6 of Sampling time-dependent artifacts in single-cell genomics studies

description: Additional file 6: Table 5. Differentially expressed genes in cultured CD4+ T-cells, cytotoxic cells and B-cells activated with anti-CD3 antibody.
DOI: 10.6084/m9.figshare.12284792
title: Additional file 5 of Sampling time-dependent artifacts in single-cell genomics studies

description: Additional file 5: Table 4. Transcription factor binding site motif enrichment analysis at sampling time-sensitive enhancers.
DOI: 10.6084/m9.figshare.12284798.v1
title: Additional file 6 of Sampling time-dependent artifacts in single-cell genomics studies

description: Additional file 6: Table 5. Differentially expressed genes in cultured CD4+ T-cells, cytotoxic cells and B-cells activated with anti-CD3 antibody.
DOI: 10.6084/m9.figshare.12284783
title: Additional file 4 of Sampling time-dependent artifacts in single-cell genomics studies

description: Additional file 4: Table 3. Gene signature associated to storage time in PBMC (measured by scRNA-seq and microarray), CLL (measured by scRNA-seq), and collagenase-dependent tissue dissociation (van den Brink).
DOI: 10.6084/m9.figshare.12284792.v1
title: Additional file 5 of Sampling time-dependent artifacts in single-cell genomics studies

description: Additional file 5: Table 4. Transcription factor binding site motif enrichment analysis at sampling time-sensitive enhancers.
DOI: 10.6084/m9.figshare.12284783.v1
title: Additional file 4 of Sampling time-dependent artifacts in single-cell genomics studies

description: Additional file 4: Table 3. Gene signature associated to storage time in PBMC (measured by scRNA-seq and microarray), CLL (measured by scRNA-seq), and collagenase-dependent tissue dissociation (van den Brink).
DOI: 10.6084/m9.figshare.12284780
title: Additional file 2 of Genome-wide association study of Striga resistance in early maturing white tropical maize inbred lines

description: Additional file 2: Table S1. Summary statistics of the 7224 filtered high-quality SNP markers. Summary statistics of the 7224 filtered high-quality SNP markers obtained from the total 44,470 markers.