cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24987972
title: Additional file 2 of An ovalbumin fusion strategy to increase recombinant protein secretion in chicken eggs

description: Additional file 2: Supplemental Table 1. Germline transmission of OVAL-EGFP F0 chimera. Supplemental Table 2. Size and volume data of eggs from wild-type and OVAL-E3-EGFP chicken. Supplemental Table 3. off-target effects detection in ovalbumin targeting chicken DNA (This data is a large list and thus list in another individual file.)
DOI: 10.6084/m9.figshare.24987972.v1
title: Additional file 2 of An ovalbumin fusion strategy to increase recombinant protein secretion in chicken eggs

description: Additional file 2: Supplemental Table 1. Germline transmission of OVAL-EGFP F0 chimera. Supplemental Table 2. Size and volume data of eggs from wild-type and OVAL-E3-EGFP chicken. Supplemental Table 3. off-target effects detection in ovalbumin targeting chicken DNA (This data is a large list and thus list in another individual file.)
DOI: 10.6084/m9.figshare.24993663
title: Additional file 1 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 1. General summary of simulated community 1a. MAGICIAN output summarizing general information on one of the simulation runs for community 1a. BBTools’ stats output is summarized in the “BBstats” sheet, CheckM output is summarized in the “CheckM” sheet, and dRep compare output is summarized in the “dRep” sheet. Explanations of terminology are given in the “explanations” sheet.
DOI: 10.6084/m9.figshare.24993663.v1
title: Additional file 1 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 1. General summary of simulated community 1a. MAGICIAN output summarizing general information on one of the simulation runs for community 1a. BBTools’ stats output is summarized in the “BBstats” sheet, CheckM output is summarized in the “CheckM” sheet, and dRep compare output is summarized in the “dRep” sheet. Explanations of terminology are given in the “explanations” sheet.
DOI: 10.6084/m9.figshare.24993781
title: Additional file 2 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 2. Bin-focused summary of simulated community 1a. MAGICIAN output comparing bins to the input genomes they have the highest ANI to for one of the simulation runs for community 1a. Comparisons are shown in the “summary” sheet, while explanations are given in the “explanations” sheet.
DOI: 10.6084/m9.figshare.24993781.v1
title: Additional file 2 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 2. Bin-focused summary of simulated community 1a. MAGICIAN output comparing bins to the input genomes they have the highest ANI to for one of the simulation runs for community 1a. Comparisons are shown in the “summary” sheet, while explanations are given in the “explanations” sheet.
DOI: 10.6084/m9.figshare.26666773
title: Additional file 3 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 3. dRep compare Nucmer outputs for simulated community 1a subsamples. Raw outputs of nucleotide-based ANI comparisons by dRep compare for three replicates of simulated community 1a in which 1% of already sorted and filtered reads have been randomly removed in order to investigate the impact of fluctuations in depth on the ability to bin scaffolds from an organism which could not be binned in the original dataset.
DOI: 10.6084/m9.figshare.26666773.v1
title: Additional file 3 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 3. dRep compare Nucmer outputs for simulated community 1a subsamples. Raw outputs of nucleotide-based ANI comparisons by dRep compare for three replicates of simulated community 1a in which 1% of already sorted and filtered reads have been randomly removed in order to investigate the impact of fluctuations in depth on the ability to bin scaffolds from an organism which could not be binned in the original dataset.
DOI: 10.6084/m9.figshare.26666779
title: Additional file 5 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 5: Supplementary Table 1. Compositions of the simulated metagenomic communities.
DOI: 10.6084/m9.figshare.26666779.v1
title: Additional file 5 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 5: Supplementary Table 1. Compositions of the simulated metagenomic communities.
DOI: 10.6084/m9.figshare.26666782
title: Additional file 6 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 6: Supplementary Table 2. Coverage of original genomes by reconstructed MAGs as determined by Nucmer alignment.
DOI: 10.6084/m9.figshare.26666782.v1
title: Additional file 6 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 6: Supplementary Table 2. Coverage of original genomes by reconstructed MAGs as determined by Nucmer alignment.
DOI: 10.6084/m9.figshare.26666785
title: Additional file 7 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 7: Supplementary Table 3. Performance characteristics of ResFinder on simulated MAGs.
DOI: 10.6084/m9.figshare.26666785.v1
title: Additional file 7 of MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

description: Additional file 7: Supplementary Table 3. Performance characteristics of ResFinder on simulated MAGs.
DOI: 10.6084/m9.figshare.24993756
title: Additional file 1 of Downregulation of PTPRT elevates the expression of survivin and promotes the proliferation, migration, and invasion of lung adenocarcinoma

description: Additional file 1: Supplementary Table S1. Gene primers used in this study. Supplementary Table S2. siRNA sequence used in this study. Supplementary Table S3. Different expressed genes (DEGs) between PTPRT-high and PTPRT-low subgroups in TCGA-LUAD cohort. Supplementary Table S4. DEGs between PTPRT-high and PTPRT-low subgroups in TCGA-LUSC cohort. Supplementary Table S5. KEGG enrichment of DEGs (N=1376) specific to LUAD cohort. Supplementary Table S6. Gene Ontology enrichment of DEGs (N=1376) specific to LUAD cohort. Supplementary Table S7. The TMB and TPM of each sample in TCGA LUAD cohort. Supplementary Table S8. The TNB and TPM of each sample in TCGA LUAD cohort. Supplementary Table S9. The TMB and TPM of each sample in TCGA LUSC cohort. Supplementary Table S10. The TNB and TPM of each sample in TCGA LUSC cohort.
DOI: 10.6084/m9.figshare.24993756.v1
title: Additional file 1 of Downregulation of PTPRT elevates the expression of survivin and promotes the proliferation, migration, and invasion of lung adenocarcinoma

description: Additional file 1: Supplementary Table S1. Gene primers used in this study. Supplementary Table S2. siRNA sequence used in this study. Supplementary Table S3. Different expressed genes (DEGs) between PTPRT-high and PTPRT-low subgroups in TCGA-LUAD cohort. Supplementary Table S4. DEGs between PTPRT-high and PTPRT-low subgroups in TCGA-LUSC cohort. Supplementary Table S5. KEGG enrichment of DEGs (N=1376) specific to LUAD cohort. Supplementary Table S6. Gene Ontology enrichment of DEGs (N=1376) specific to LUAD cohort. Supplementary Table S7. The TMB and TPM of each sample in TCGA LUAD cohort. Supplementary Table S8. The TNB and TPM of each sample in TCGA LUAD cohort. Supplementary Table S9. The TMB and TPM of each sample in TCGA LUSC cohort. Supplementary Table S10. The TNB and TPM of each sample in TCGA LUSC cohort.
DOI: 10.6084/m9.figshare.24993788
title: Additional file 2 of Exosomes derived from cancer-associated fibroblasts promote tumorigenesis, metastasis and chemoresistance of colorectal cancer by upregulating circ_0067557 to target Lin28

description: Supplementary Material 2: Supplementary Table 2. The list of identified target mRNAs of the DECs
DOI: 10.6084/m9.figshare.24993788.v1
title: Additional file 2 of Exosomes derived from cancer-associated fibroblasts promote tumorigenesis, metastasis and chemoresistance of colorectal cancer by upregulating circ_0067557 to target Lin28

description: Supplementary Material 2: Supplementary Table 2. The list of identified target mRNAs of the DECs
DOI: 10.6084/m9.figshare.24993688
title: Additional file 1 of A cautionary tale of low-pass sequencing and imputation with respect to haplotype accuracy

description: Additional file 1: Table S1. Sequencing coverage summary statistics. Sample ID, gender, coat colour, and sequencing summary statistics for each library sequenced. Table S2. Summary of variant records in VCF files following each filtering step described in Additional file 2: Figure S1. Breakdown of variants tagged with different filtering criteria, and subsequently remaining after each filtering step. Table S3. Reference panels for phasing and imputation. List of dog ID and breeds comprising the full reference panel, with those included in panels 1 and 2 indicated, respectively. Table S4. Summary of variant counts binned by allele frequency, those reported with different depths are derived from the full panel. Breakdown of variant counts per allele frequency bin for the full reference panel, and subset panels 1 and 2. Also provided are variant counts in the imputed data at each sequencing depth based on using the full reference panel for phasing and imputation. Table S5. Linear model coefficient estimates after fitting imputed genotype r2 to MAF, with depth and panel as covariates: lm(r2 ~ MAF + depth + panel). Summary table of coefficient estimates after fitting a linear model of imputed genotype r2 to MAF, including depth and reference panel as covariates. Table S6. Linear model coefficient estimates after fitting SNV imputed dosage r2 to depth, with panel as a covariate: lm(r2 ~ depth + panel). Summary table of coefficient estimates after fitting a linear model of SNV imputed dosage r2 to depth, including reference panel as a covariate. Table S7. Summary of mismatch rates for SNVs arising from different reference panels at each depth of coverage tested. Table of mismatch rates for homozygous reference (RR), heterozygous reference (RA), and homozygous alternate (AA) genotypes of SNVs when comparing each depth of coverage to the genotypes from the 43.5X depth dataset, derived from imputation with each of the reference panels. Table S8. Linear model coefficient estimates after fitting paired Wilcox test p values from comparing region and chromosome depth to region median haplotype count: lm(p ~ haps). Summary table of coefficient estimates after fitting linear model of paired Wilcox test p values from comparing region and chromosome depth to region median haplotype count.
DOI: 10.6084/m9.figshare.24993688.v1
title: Additional file 1 of A cautionary tale of low-pass sequencing and imputation with respect to haplotype accuracy

description: Additional file 1: Table S1. Sequencing coverage summary statistics. Sample ID, gender, coat colour, and sequencing summary statistics for each library sequenced. Table S2. Summary of variant records in VCF files following each filtering step described in Additional file 2: Figure S1. Breakdown of variants tagged with different filtering criteria, and subsequently remaining after each filtering step. Table S3. Reference panels for phasing and imputation. List of dog ID and breeds comprising the full reference panel, with those included in panels 1 and 2 indicated, respectively. Table S4. Summary of variant counts binned by allele frequency, those reported with different depths are derived from the full panel. Breakdown of variant counts per allele frequency bin for the full reference panel, and subset panels 1 and 2. Also provided are variant counts in the imputed data at each sequencing depth based on using the full reference panel for phasing and imputation. Table S5. Linear model coefficient estimates after fitting imputed genotype r2 to MAF, with depth and panel as covariates: lm(r2 ~ MAF + depth + panel). Summary table of coefficient estimates after fitting a linear model of imputed genotype r2 to MAF, including depth and reference panel as covariates. Table S6. Linear model coefficient estimates after fitting SNV imputed dosage r2 to depth, with panel as a covariate: lm(r2 ~ depth + panel). Summary table of coefficient estimates after fitting a linear model of SNV imputed dosage r2 to depth, including reference panel as a covariate. Table S7. Summary of mismatch rates for SNVs arising from different reference panels at each depth of coverage tested. Table of mismatch rates for homozygous reference (RR), heterozygous reference (RA), and homozygous alternate (AA) genotypes of SNVs when comparing each depth of coverage to the genotypes from the 43.5X depth dataset, derived from imputation with each of the reference panels. Table S8. Linear model coefficient estimates after fitting paired Wilcox test p values from comparing region and chromosome depth to region median haplotype count: lm(p ~ haps). Summary table of coefficient estimates after fitting linear model of paired Wilcox test p values from comparing region and chromosome depth to region median haplotype count.
DOI: 10.6084/m9.figshare.24993696
title: Additional file 1 of Detection of low urine output by measuring urinary biomarkers

description: Supplementary Material 1: Original data in the diet study. Lines 1–82 show the measurements performed during the first 4 days of the study, when water intake was habitual, and Lines 84–162 show the second period (Days 8–11) when the ingestion of water was increased
DOI: 10.6084/m9.figshare.24993696.v1
title: Additional file 1 of Detection of low urine output by measuring urinary biomarkers

description: Supplementary Material 1: Original data in the diet study. Lines 1–82 show the measurements performed during the first 4 days of the study, when water intake was habitual, and Lines 84–162 show the second period (Days 8–11) when the ingestion of water was increased
DOI: 10.6084/m9.figshare.24993791
title: Additional file 2 of Detection of low urine output by measuring urinary biomarkers

description: Supplementary Material 2: Original data in the cross-sectional studies
DOI: 10.6084/m9.figshare.24993791.v1
title: Additional file 2 of Detection of low urine output by measuring urinary biomarkers

description: Supplementary Material 2: Original data in the cross-sectional studies
DOI: 10.6084/m9.figshare.24993733.v1
title: Additional file 1 of Proteomic differences between extracellular vesicles and extracellular vesicle-depleted excretory/secretory products of barber’s pole worm

description: Additional file 1: Table S1. Proteins identified in the small extracellular vesicles (EVs) and EV-depleted excretory/secretory products (ESPs) of Haemonchus contortus.
DOI: 10.6084/m9.figshare.24993733
title: Additional file 1 of Proteomic differences between extracellular vesicles and extracellular vesicle-depleted excretory/secretory products of barber’s pole worm

description: Additional file 1: Table S1. Proteins identified in the small extracellular vesicles (EVs) and EV-depleted excretory/secretory products (ESPs) of Haemonchus contortus.
DOI: 10.6084/m9.figshare.26666881
title: Additional file 4 of Proteomic differences between extracellular vesicles and extracellular vesicle-depleted excretory/secretory products of barber’s pole worm

description: Additional file 4: Table S3. The methodology used to isolate small extracellular vesicles (including exosomes) from the excretory/secretory products of Haemonchus contortus.
DOI: 10.6084/m9.figshare.26666881.v1
title: Additional file 4 of Proteomic differences between extracellular vesicles and extracellular vesicle-depleted excretory/secretory products of barber’s pole worm

description: Additional file 4: Table S3. The methodology used to isolate small extracellular vesicles (including exosomes) from the excretory/secretory products of Haemonchus contortus.
DOI: 10.6084/m9.figshare.26666911
title: Additional file 4 of Renal-protective effects of Chinese medicinal herbs and compounds for diabetic kidney disease in animal models: protocol for systematic review and meta-analysis

description: Additional file 4. Data extraction template.
DOI: 10.6084/m9.figshare.26666911.v1
title: Additional file 4 of Renal-protective effects of Chinese medicinal herbs and compounds for diabetic kidney disease in animal models: protocol for systematic review and meta-analysis

description: Additional file 4. Data extraction template.
DOI: 10.6084/m9.figshare.24993803
title: Additional file 2 of ChIPr: accurate prediction of cohesin-mediated 3D genome organization from 2D chromatin features

description: Additional file 2: Table S1 and Table S2. They contain the regions tested in comparison with other chromatin interaction prediction methods.
DOI: 10.6084/m9.figshare.24993803.v1
title: Additional file 2 of ChIPr: accurate prediction of cohesin-mediated 3D genome organization from 2D chromatin features

description: Additional file 2: Table S1 and Table S2. They contain the regions tested in comparison with other chromatin interaction prediction methods.
DOI: 10.6084/m9.figshare.26666914
title: Additional file 3 of ChIPr: accurate prediction of cohesin-mediated 3D genome organization from 2D chromatin features

description: Additional file 3: Table S3. It contains the results obtained for the grid search for the DNN hyperparameter selection.
DOI: 10.6084/m9.figshare.26666914.v1
title: Additional file 3 of ChIPr: accurate prediction of cohesin-mediated 3D genome organization from 2D chromatin features

description: Additional file 3: Table S3. It contains the results obtained for the grid search for the DNN hyperparameter selection.
DOI: 10.15156/bio/sh0199466.10fu
title: SH0199466.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0199467.10fu
title: SH0199467.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0199468.10fu
title: SH0199468.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0199469.10fu
title: SH0199469.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0199470.10fu
title: SH0199470.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.