cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13047246
title: Additional file 2 of Effect of vitamin A on intestinal mucosal injury in pediatric patients receiving hematopoietic stem cell transplantation and chemotherapy: a quasai-randomized trial

description: Additional file 2: Raw data of the results in the study.
DOI: 10.6084/m9.figshare.13047251
title: Additional file 2 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 2. Module Preservation Stats.xlsx: Summary of composite and individual module preservation statistics.
DOI: 10.6084/m9.figshare.13047248.v1
title: Additional file 1 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 1. Mapping Stats.xlsx: Summary of sequencing read alignments to the reference genome for both RNA-Sequencing and Whole-Genome Bisulfite-Sequencing.
DOI: 10.6084/m9.figshare.13047248
title: Additional file 1 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 1. Mapping Stats.xlsx: Summary of sequencing read alignments to the reference genome for both RNA-Sequencing and Whole-Genome Bisulfite-Sequencing.
DOI: 10.6084/m9.figshare.13047263
title: Additional file 6 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 6. Gene Methylation level and Network Properties Measurements.xlsx: Summary of statistics at gene level including differential coexpression score, connectivity, module eigengenes, count of differentially methylated cytosines and methylation levels.
DOI: 10.6084/m9.figshare.13047246.v1
title: Additional file 2 of Effect of vitamin A on intestinal mucosal injury in pediatric patients receiving hematopoietic stem cell transplantation and chemotherapy: a quasai-randomized trial

description: Additional file 2: Raw data of the results in the study.
DOI: 10.6084/m9.figshare.13047257
title: Additional file 4 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 4. Gene CpG Count by Region.xlsx: Count of cytosines (CpG context) evaluated in each of the six genomic regions per gene.
DOI: 10.6084/m9.figshare.13047257.v1
title: Additional file 4 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 4. Gene CpG Count by Region.xlsx: Count of cytosines (CpG context) evaluated in each of the six genomic regions per gene.
DOI: 10.6084/m9.figshare.13047260
title: Additional file 5 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 5. Associations of Differentially Methylated CpGs.xlsx: List of differentially methylated cytosines.
DOI: 10.6084/m9.figshare.13047260.v1
title: Additional file 5 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 5. Associations of Differentially Methylated CpGs.xlsx: List of differentially methylated cytosines.
DOI: 10.6084/m9.figshare.13047254
title: Additional file 3 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 3. Overrepresentation Summary.xlsx: List of significant functional terms.
DOI: 10.6084/m9.figshare.13047263.v1
title: Additional file 6 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 6. Gene Methylation level and Network Properties Measurements.xlsx: Summary of statistics at gene level including differential coexpression score, connectivity, module eigengenes, count of differentially methylated cytosines and methylation levels.
DOI: 10.6084/m9.figshare.13047251.v1
title: Additional file 2 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 2. Module Preservation Stats.xlsx: Summary of composite and individual module preservation statistics.
DOI: 10.6084/m9.figshare.13047272
title: Additional file 2 of TWIST1 DNA methylation is a cell marker of airway and parenchymal lung fibroblasts that are differentially methylated in asthma

description: Additional file 2. Supplementary Tables 1-8
DOI: 10.6084/m9.figshare.13047254.v1
title: Additional file 3 of Differential network analysis of bovine muscle reveals changes in gene coexpression patterns in response to changes in maternal nutrition

description: Additional file 3. Overrepresentation Summary.xlsx: List of significant functional terms.
DOI: 10.6084/m9.figshare.13047272.v1
title: Additional file 2 of TWIST1 DNA methylation is a cell marker of airway and parenchymal lung fibroblasts that are differentially methylated in asthma

description: Additional file 2. Supplementary Tables 1-8
DOI: 10.6084/m9.figshare.13047269
title: Additional file 1 of TWIST1 DNA methylation is a cell marker of airway and parenchymal lung fibroblasts that are differentially methylated in asthma

description: Additional file 1. QPCR generated gene expression of paired airway and parenchymal fibroblasts for TWIST1, HLX and SKAP2.
DOI: 10.6084/m9.figshare.13047269.v1
title: Additional file 1 of TWIST1 DNA methylation is a cell marker of airway and parenchymal lung fibroblasts that are differentially methylated in asthma

description: Additional file 1. QPCR generated gene expression of paired airway and parenchymal fibroblasts for TWIST1, HLX and SKAP2.
DOI: 10.6084/m9.figshare.13047285.v1
title: Additional file 4 of PALMER: improving pathway annotation based on the biomedical literature mining with a constrained latent block model

description: Additional file 4. Identification of new pathway-modulating genes with 172 GO terms and 537 genes.
DOI: 10.6084/m9.figshare.13047279.v1
title: Additional file 2 of PALMER: improving pathway annotation based on the biomedical literature mining with a constrained latent block model

description: Additional file 2. Reconstruction of known pathways with 47 GO terms and 99 genes.
DOI: 10.6084/m9.figshare.13047282
title: Additional file 3 of PALMER: improving pathway annotation based on the biomedical literature mining with a constrained latent block model

description: Additional file 3. Disjoint gene assignment between pathways with 196 GO terms and 227 genes.
DOI: 10.6084/m9.figshare.13047279
title: Additional file 2 of PALMER: improving pathway annotation based on the biomedical literature mining with a constrained latent block model

description: Additional file 2. Reconstruction of known pathways with 47 GO terms and 99 genes.
DOI: 10.6084/m9.figshare.13047285
title: Additional file 4 of PALMER: improving pathway annotation based on the biomedical literature mining with a constrained latent block model

description: Additional file 4. Identification of new pathway-modulating genes with 172 GO terms and 537 genes.
DOI: 10.6084/m9.figshare.13047282.v1
title: Additional file 3 of PALMER: improving pathway annotation based on the biomedical literature mining with a constrained latent block model

description: Additional file 3. Disjoint gene assignment between pathways with 196 GO terms and 227 genes.
DOI: 10.6084/m9.figshare.13047330
title: Additional file 1 of Proteomic profiles of unilateral cryptorchidism in pigs at different ages using MALDI-TOF mass spectrometry and in-gel digestion coupled with mass spectrometry (GeLC-MS/MS) approaches

description: Additional file 1: Supplementary Table S1. Relative expression levels of divergent proteins in undescended testes in the abdominal cavity (UDT), descended testes in cryptorchid pigs (DT) and normal testes of healthy pigs (NT) at different ages, shown as log2 intensities
DOI: 10.6084/m9.figshare.13047333
title: Additional file 2 of Proteomic profiles of unilateral cryptorchidism in pigs at different ages using MALDI-TOF mass spectrometry and in-gel digestion coupled with mass spectrometry (GeLC-MS/MS) approaches

description: Additional file 2: Supplementary Table S2. Groups of proteins differentially expressed in undescended testes in the abdominal cavity (UDT), descended testes in cryptorchid pigs (DT) and normal testes of healthy pigs (NT) at different ages. Asterisks indicate groups, excluding the NT groups
DOI: 10.6084/m9.figshare.13047333.v1
title: Additional file 2 of Proteomic profiles of unilateral cryptorchidism in pigs at different ages using MALDI-TOF mass spectrometry and in-gel digestion coupled with mass spectrometry (GeLC-MS/MS) approaches

description: Additional file 2: Supplementary Table S2. Groups of proteins differentially expressed in undescended testes in the abdominal cavity (UDT), descended testes in cryptorchid pigs (DT) and normal testes of healthy pigs (NT) at different ages. Asterisks indicate groups, excluding the NT groups
DOI: 10.6084/m9.figshare.13047330.v1
title: Additional file 1 of Proteomic profiles of unilateral cryptorchidism in pigs at different ages using MALDI-TOF mass spectrometry and in-gel digestion coupled with mass spectrometry (GeLC-MS/MS) approaches

description: Additional file 1: Supplementary Table S1. Relative expression levels of divergent proteins in undescended testes in the abdominal cavity (UDT), descended testes in cryptorchid pigs (DT) and normal testes of healthy pigs (NT) at different ages, shown as log2 intensities
DOI: 10.6084/m9.figshare.13047450
title: Additional file 4 of Coding transcriptome analyses reveal altered functions underlying immunotolerance of PEG-fused rat sciatic nerve allografts

description: Additional file 4: Table S2. (Differential_Expression_Results.xlsx). Excel tables showing (Tab S1) all normalized read counts for all samples and associated gene transcripts; (Tab S2) PEG vs NC differential expression results; (Tab S3) PEG vs Unop differential expression results; (Tab S4) NC vs Unop differential expression results.
DOI: 10.6084/m9.figshare.13047444
title: Additional file 2 of Coding transcriptome analyses reveal altered functions underlying immunotolerance of PEG-fused rat sciatic nerve allografts

description: Additional file 2: Table S1. (RNAseq_Reads_Table.xlsx). Read mapping and alignment results for all samples used for RNAseq. The ID of each animal is indicated underneath the sample name in parentheses.
DOI: 10.6084/m9.figshare.13047450.v1
title: Additional file 4 of Coding transcriptome analyses reveal altered functions underlying immunotolerance of PEG-fused rat sciatic nerve allografts

description: Additional file 4: Table S2. (Differential_Expression_Results.xlsx). Excel tables showing (Tab S1) all normalized read counts for all samples and associated gene transcripts; (Tab S2) PEG vs NC differential expression results; (Tab S3) PEG vs Unop differential expression results; (Tab S4) NC vs Unop differential expression results.
DOI: 10.6084/m9.figshare.13047444.v1
title: Additional file 2 of Coding transcriptome analyses reveal altered functions underlying immunotolerance of PEG-fused rat sciatic nerve allografts

description: Additional file 2: Table S1. (RNAseq_Reads_Table.xlsx). Read mapping and alignment results for all samples used for RNAseq. The ID of each animal is indicated underneath the sample name in parentheses.
DOI: 10.6084/m9.figshare.13047453
title: Additional file 5 of Coding transcriptome analyses reveal altered functions underlying immunotolerance of PEG-fused rat sciatic nerve allografts

description: Additional file 5: Table S3. (DEG_Heatmap_Clusters.xlsx). Excel tables showing: (Tab S1) Z-scores of all 2,180 transcripts extracted from the DEG heatmap displayed in Fig. 2A, which heatmap cluster each transcript is associated with (Cluster 1, 2, 3, or 4) and the PEG vs NC differential expression results for each transcript; (Tab S2) all transcripts associated with Cluster 1 and their PEG vs NC differential expression results; (Tab S3) all transcripts associated with Cluster 2 and their PEG vs NC differential expression results; (Tab S4) all transcripts associated with Cluster 3 and their PEG vs NC differential expression results; (Tab S5) all transcripts associated with Cluster 4 and their PEG vs NC differential expression results.
DOI: 10.6084/m9.figshare.13047456
title: Additional file 6 of Coding transcriptome analyses reveal altered functions underlying immunotolerance of PEG-fused rat sciatic nerve allografts

description: Additional file 6: Table S4. (GO_KEGG_InterPro_Clusters.xlsx). Excel tables showing (Tabs S1-S3) GO, KEGG and InterPro results for Cluster 1 (high expression in PEG); (Tabs S4-S6) GO, KEGG and InterPro results for Cluster 2 (high expression in PEG and Unop); (Tabs S7-S9) GO, KEGG and InterPro results for Cluster 3 (high expression in Unop); (Tabs S10-S12) GO, KEGG and InterPro results for Cluster 4 (high expression in NC).
DOI: 10.6084/m9.figshare.13047453.v1
title: Additional file 5 of Coding transcriptome analyses reveal altered functions underlying immunotolerance of PEG-fused rat sciatic nerve allografts

description: Additional file 5: Table S3. (DEG_Heatmap_Clusters.xlsx). Excel tables showing: (Tab S1) Z-scores of all 2,180 transcripts extracted from the DEG heatmap displayed in Fig. 2A, which heatmap cluster each transcript is associated with (Cluster 1, 2, 3, or 4) and the PEG vs NC differential expression results for each transcript; (Tab S2) all transcripts associated with Cluster 1 and their PEG vs NC differential expression results; (Tab S3) all transcripts associated with Cluster 2 and their PEG vs NC differential expression results; (Tab S4) all transcripts associated with Cluster 3 and their PEG vs NC differential expression results; (Tab S5) all transcripts associated with Cluster 4 and their PEG vs NC differential expression results.
DOI: 10.6084/m9.figshare.13047456.v1
title: Additional file 6 of Coding transcriptome analyses reveal altered functions underlying immunotolerance of PEG-fused rat sciatic nerve allografts

description: Additional file 6: Table S4. (GO_KEGG_InterPro_Clusters.xlsx). Excel tables showing (Tabs S1-S3) GO, KEGG and InterPro results for Cluster 1 (high expression in PEG); (Tabs S4-S6) GO, KEGG and InterPro results for Cluster 2 (high expression in PEG and Unop); (Tabs S7-S9) GO, KEGG and InterPro results for Cluster 3 (high expression in Unop); (Tabs S10-S12) GO, KEGG and InterPro results for Cluster 4 (high expression in NC).
DOI: 10.6084/m9.figshare.13047465.v1
title: Additional file 2 of Viral ecogenomics across the Porifera

description: Additional file 2. Summary of MEGAN6 genus-level taxonomic assignment of viral genes using BLAST+ comparisons to the viral refseq database.
DOI: 10.6084/m9.figshare.13047462
title: Additional file 1 of Viral ecogenomics across the Porifera

description: Additional file 1. Summary of sampling locations, accessing numbers, sequencing statistics and cellular contamination evaluation of virome datasets. N50 values for each dataset were calculated based on evaluation of unfiltered contigs.
DOI: 10.6084/m9.figshare.13047474.v1
title: Additional file 5 of Viral ecogenomics across the Porifera

description: Additional file 5. ## 1 - Complete phage contigs - category 1 (sure)
DOI: 10.6084/m9.figshare.13047462.v1
title: Additional file 1 of Viral ecogenomics across the Porifera

description: Additional file 1. Summary of sampling locations, accessing numbers, sequencing statistics and cellular contamination evaluation of virome datasets. N50 values for each dataset were calculated based on evaluation of unfiltered contigs.
DOI: 10.6084/m9.figshare.13047465
title: Additional file 2 of Viral ecogenomics across the Porifera

description: Additional file 2. Summary of MEGAN6 genus-level taxonomic assignment of viral genes using BLAST+ comparisons to the viral refseq database.
DOI: 10.6084/m9.figshare.13047471
title: Additional file 4 of Viral ecogenomics across the Porifera

description: Additional file 4. Similarity percentage analysis (SIMPER) of differences in viral metagenomes associated with sponges with and without photosymbionts, based on Bray-Curtis similarity of genus-level taxonomic assignment of predicted genes. The columns two and three identify the average abundance of viral taxa within each sponge group, the fourth and fifth columns represent the Bray Curtis dissimilarity metric between sponges with and without photosymbionts and its standard deviation, respectively. The sixth column shows the percentage of dissimilarity contribution explained by that viral taxa and the seventh column shows the cumulative Bray Curtis dissimilarity metric for the taxa. The eighth and ninth columns represent the natural hosts for the viral group according the International Committee on Taxonomy of Viruses (ICTV).
DOI: 10.6084/m9.figshare.13047471.v1
title: Additional file 4 of Viral ecogenomics across the Porifera

description: Additional file 4. Similarity percentage analysis (SIMPER) of differences in viral metagenomes associated with sponges with and without photosymbionts, based on Bray-Curtis similarity of genus-level taxonomic assignment of predicted genes. The columns two and three identify the average abundance of viral taxa within each sponge group, the fourth and fifth columns represent the Bray Curtis dissimilarity metric between sponges with and without photosymbionts and its standard deviation, respectively. The sixth column shows the percentage of dissimilarity contribution explained by that viral taxa and the seventh column shows the cumulative Bray Curtis dissimilarity metric for the taxa. The eighth and ninth columns represent the natural hosts for the viral group according the International Committee on Taxonomy of Viruses (ICTV).
DOI: 10.6084/m9.figshare.13047474
title: Additional file 5 of Viral ecogenomics across the Porifera

description: Additional file 5. ## 1 - Complete phage contigs - category 1 (sure)
DOI: 10.6084/m9.figshare.13047518
title: Additional file 6 of Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case–control and systems biology study

description: Additional file 6: File S3. The list of LINC00961 mutations across breast cancer datasets, obtained using the ICGC portal.
DOI: 10.6084/m9.figshare.13047515
title: Additional file 5 of Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case–control and systems biology study

description: Additional file 5: File S2. The expression level of the co-expressed genes with LINC00961.
DOI: 10.6084/m9.figshare.13047524
title: Additional file 8 of Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case–control and systems biology study

description: Additional file 8: File S4. Some of the significant GO terms associated to biological process, molecular function and cellular component of the LINC00961 co-expressed genes, obtained using DAVID database.
DOI: 10.6084/m9.figshare.13047512.v1
title: Additional file 4 of Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case–control and systems biology study

description: Additional file 4: File S1. The list of co-expressed genes with LINC00961, across luminal A and B samples.
DOI: 10.6084/m9.figshare.13047515.v1
title: Additional file 5 of Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case–control and systems biology study

description: Additional file 5: File S2. The expression level of the co-expressed genes with LINC00961.
DOI: 10.6084/m9.figshare.13047518.v1
title: Additional file 6 of Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case–control and systems biology study

description: Additional file 6: File S3. The list of LINC00961 mutations across breast cancer datasets, obtained using the ICGC portal.
DOI: 10.6084/m9.figshare.13047512
title: Additional file 4 of Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case–control and systems biology study

description: Additional file 4: File S1. The list of co-expressed genes with LINC00961, across luminal A and B samples.
DOI: 10.6084/m9.figshare.13047524.v1
title: Additional file 8 of Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case–control and systems biology study

description: Additional file 8: File S4. Some of the significant GO terms associated to biological process, molecular function and cellular component of the LINC00961 co-expressed genes, obtained using DAVID database.
DOI: 10.21227/09pz-bs15
title: Coronavirus (COVID-19) Global Sentiment Trend

description: This dataset gives a cursory glimpse at the overall sentiment trend of the public discourse regarding the COVID-19 pandemic on Twitter. The live scatter plot of this dataset is available as The Overall Trend block at https://live.rlamsal.com.np. The trend graph reveals multiple peaks and drops that need further analysis. The n-grams during those peaks and drops can prove beneficial for better understanding the discourse.The dataset will be updated weekly and will continue until the development of the Coronavirus (COVID-19) Tweets Dataset is ongoing.A quick overview of the datasetThe sentiment scores are defined in the range [-1,0), 0, and (0,+1] for negative sentiment, neutral sentiment, and positive sentiment. Since the number of negative sentiment tweets is always less than the combined number of neutral and positive sentiment tweets, the majority of the time, the average sentiment falls pretty close to +0.05. So if we consider +0.05 as the neutral point for average sentiment score, then any score greater than +0.1 (peaks) and smaller than 0 (drops) can be regarded as a point of interest for further scrutinizing. Following are the dates when the Twitter stream (based on the tweets present in the Coronavirus (COVID-19) Tweets Dataset) experienced those peaks and drops:Positive peaks: In 2020 (April 30, May 3, May 23, May 24, May 25, May 26, June 2, June 22, June 28, July 3, July 12, July 26, August 15, August 16, August 18, August 21, August 24, August 31, September 1, September 2, September 4, September 5, September 9, September 21, September 23)Negative Peaks: In 2020 (May 28, May 30, May 31, June 1, June 2, June 7, June 8, June 12, June 13, June 14, June 15, June 21, June 24, june 25, July 6, July 7, July 10, August 26, September 1, September 3, September 13, September 17, September 25, September 26, September 28)What's inside the dataset files?Tweets collected every 10 minutes are sampled together, and an average sentiment score is computed. This dataset contains TXT files, each with two columns: (i) date/time and (ii) average sentiment. The first column is date/time and is by default in Unix timestamp (in ms). You can use this formula =cell/1000/60/60/24 + DATE(1970,1,1) in Spreadsheets, or this pd.to_datetime(dataframe_name[column],unit='ms') if you're comfortable with Python, to convert the Unix timestamp to human-readable format. There are 44 instances where the average sentiment score is NULL because of networking issues with the cloud service.