cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh2846788.08fu
title: SH2846788.08FU

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/sh2846789.08fu
title: SH2846789.08FU

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/sh2846790.08fu
title: SH2846790.08FU

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/sh1869715.08fu
title: SH1869715.08FU

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/sh1869716.08fu
title: SH1869716.08FU

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/sh2846791.08fu
title: SH2846791.08FU

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/sh2846792.08fu
title: SH2846792.08FU

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/sh1869717.08fu
title: SH1869717.08FU

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/sh1869718.08fu
title: SH1869718.08FU

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/sh1869719.08fu
title: SH1869719.08FU

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: 10.6084/m9.figshare.20267227
title: Additional file 2 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 2: Table S1. ChIP-seq datasets analyzed in this study.
DOI: 10.6084/m9.figshare.20267227.v1
title: Additional file 2 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 2: Table S1. ChIP-seq datasets analyzed in this study.
DOI: 10.6084/m9.figshare.20267230.v1
title: Additional file 3 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 3: Table S2. GEO and ENCODE FASTQ identification numbers per cell line for the WGBS and DNase-seq data that were used to train JAMS models.
DOI: 10.6084/m9.figshare.20267230
title: Additional file 3 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 3: Table S2. GEO and ENCODE FASTQ identification numbers per cell line for the WGBS and DNase-seq data that were used to train JAMS models.
DOI: 10.6084/m9.figshare.20267233
title: Additional file 4 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 4: Table S3. High-confidence JAMS models selected for each TF.
DOI: 10.6084/m9.figshare.20267233.v1
title: Additional file 4 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 4: Table S3. High-confidence JAMS models selected for each TF.
DOI: 10.6084/m9.figshare.20267239
title: Additional file 5 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 5: Table S4. Pearson correlation (r) between observed and predicted TF-binding across cell types.
DOI: 10.6084/m9.figshare.20267239.v1
title: Additional file 5 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 5: Table S4. Pearson correlation (r) between observed and predicted TF-binding across cell types.
DOI: 10.6084/m9.figshare.20267242
title: Additional file 6 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 6: Table S5. TFs with high-quality JAMS models, stratified by methyl-binding preference and whether they belong to the KRAB-ZF family.
DOI: 10.6084/m9.figshare.20267242.v1
title: Additional file 6 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 6: Table S5. TFs with high-quality JAMS models, stratified by methyl-binding preference and whether they belong to the KRAB-ZF family.
DOI: 10.6084/m9.figshare.20267245
title: Additional file 7 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 7: Table S6. GEO and ENCODE FASTQ identification numbers per cell line for the data that were used to identify differential TF peaks.
DOI: 10.6084/m9.figshare.20267245.v1
title: Additional file 7 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding

description: Additional file 7: Table S6. GEO and ENCODE FASTQ identification numbers per cell line for the data that were used to identify differential TF peaks.
DOI: 10.6084/m9.figshare.20267278
title: Additional file 2 of Ink and support characterization of typologically established papyrus groups from the Palau-Ribes collection

description: Additional file 2. Table S1: list of sampled papyri together with metadata and analysis results.
DOI: 10.6084/m9.figshare.20267278.v1
title: Additional file 2 of Ink and support characterization of typologically established papyrus groups from the Palau-Ribes collection

description: Additional file 2. Table S1: list of sampled papyri together with metadata and analysis results.
DOI: 10.6084/m9.figshare.20267296
title: Additional file 1 of A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

description: Additional file 1: Table S1. Plant material for RNA samples for Iso-Seq. Table S2. Read statistics for Iso-seq libraries. Table S3A and B. Number and percentage of splice junctions with sequencing mismatches in positions L1 to L30 for A) upstream (left) and B) downstream (right) of splice junctions. Table S4. Position Weight Matrix scores for consensus splice site sequences of introns. Table S5A and B. Filtering of SJs on basis of mismatches in each position. Table S6. Sequence motifs for validation of TSS and TES sites. Table S7. Number of genes and transcripts contributed to AtIso from each Iso-seq library. Table S8. Saturation curve of the number of unique genes and transcripts added to AtIso with the addition of each library. Table S9. AtRTD3 - Transcript characteristics and translations from TransFeat. Table S10A. TranSuite output of AtRTD3 for mono-exonic/multi-exonic genes with single or multiple transcript isoforms; B Comparison of TranSuite output of AtRTD3 gene and transcript characterisation. Table S11. AtRTD3 - novel genes. Table S12. Functional analysis of transcripts from novel genes in AtRTD3 with TRAPID 2.0. Table S13. AtRTD3 - Chimeric Genes and transcripts. Table S14. Frequency of AS event type among AtRTD3, AtIso and Araport11. Table S15A. Frequency of AS event type among AtRTD3, AtIso and Araport11. Table S15B. Gene descriptions of genes containing non-stop RNAs.
DOI: 10.6084/m9.figshare.20267296.v1
title: Additional file 1 of A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

description: Additional file 1: Table S1. Plant material for RNA samples for Iso-Seq. Table S2. Read statistics for Iso-seq libraries. Table S3A and B. Number and percentage of splice junctions with sequencing mismatches in positions L1 to L30 for A) upstream (left) and B) downstream (right) of splice junctions. Table S4. Position Weight Matrix scores for consensus splice site sequences of introns. Table S5A and B. Filtering of SJs on basis of mismatches in each position. Table S6. Sequence motifs for validation of TSS and TES sites. Table S7. Number of genes and transcripts contributed to AtIso from each Iso-seq library. Table S8. Saturation curve of the number of unique genes and transcripts added to AtIso with the addition of each library. Table S9. AtRTD3 - Transcript characteristics and translations from TransFeat. Table S10A. TranSuite output of AtRTD3 for mono-exonic/multi-exonic genes with single or multiple transcript isoforms; B Comparison of TranSuite output of AtRTD3 gene and transcript characterisation. Table S11. AtRTD3 - novel genes. Table S12. Functional analysis of transcripts from novel genes in AtRTD3 with TRAPID 2.0. Table S13. AtRTD3 - Chimeric Genes and transcripts. Table S14. Frequency of AS event type among AtRTD3, AtIso and Araport11. Table S15A. Frequency of AS event type among AtRTD3, AtIso and Araport11. Table S15B. Gene descriptions of genes containing non-stop RNAs.
DOI: 10.6084/m9.figshare.20267332
title: Additional file 13 of Distinct cell type-specific protein signatures in GRN and MAPT genetic subtypes of frontotemporal dementia

description: Additional file 13 Overview of unique proteins detected and quantified within temporal cortical tissues for AD and unique proteins detected and quantified within temporal cortical tissues for both AD and the FTD-MAPT subtype. Proteins were selected using quality filtering on peptide level (q ≤10-3 in at least 50% of samples per group, i.e. NDC or AD). For every protein, the raw fold change and raw p-value are given for the statistical comparison between NDC and AD, and NDC and FTD-MAPT. In addition, columns are included which note whether a protein has passed statistical multiple testing comparison (q &lt; 0.05) and whether differential protein expression is in a similar direction in AD and FTD-MAPT.
DOI: 10.6084/m9.figshare.20267332.v1
title: Additional file 13 of Distinct cell type-specific protein signatures in GRN and MAPT genetic subtypes of frontotemporal dementia

description: Additional file 13 Overview of unique proteins detected and quantified within temporal cortical tissues for AD and unique proteins detected and quantified within temporal cortical tissues for both AD and the FTD-MAPT subtype. Proteins were selected using quality filtering on peptide level (q ≤10-3 in at least 50% of samples per group, i.e. NDC or AD). For every protein, the raw fold change and raw p-value are given for the statistical comparison between NDC and AD, and NDC and FTD-MAPT. In addition, columns are included which note whether a protein has passed statistical multiple testing comparison (q &lt; 0.05) and whether differential protein expression is in a similar direction in AD and FTD-MAPT.
DOI: 10.6084/m9.figshare.20267335
title: Additional file 14 of Distinct cell type-specific protein signatures in GRN and MAPT genetic subtypes of frontotemporal dementia

description: Additional file 14 Lists of significant GO enrichment analysis results for proteins differentially expressed in both temporal cortical FTD-MAPT vs NDC and AD vs NDC. GO enrichment analysis was performed for proteins differentially expressed at q &lt; 0.05 in both temporal cortical AD and FTD-MAPT vs NDC, and for proteins that are only differentially expressed (q &lt; 0.05) in temporal cortical FTD-MAPT vs NDC. Differentially expressed proteins are divided into lower and higher expressed proteins. For every GO term, the corresponding GO group is listed, as well as whether the GO term is considered to be a ‘Best Per Parent’ term.
DOI: 10.6084/m9.figshare.20267335.v1
title: Additional file 14 of Distinct cell type-specific protein signatures in GRN and MAPT genetic subtypes of frontotemporal dementia

description: Additional file 14 Lists of significant GO enrichment analysis results for proteins differentially expressed in both temporal cortical FTD-MAPT vs NDC and AD vs NDC. GO enrichment analysis was performed for proteins differentially expressed at q &lt; 0.05 in both temporal cortical AD and FTD-MAPT vs NDC, and for proteins that are only differentially expressed (q &lt; 0.05) in temporal cortical FTD-MAPT vs NDC. Differentially expressed proteins are divided into lower and higher expressed proteins. For every GO term, the corresponding GO group is listed, as well as whether the GO term is considered to be a ‘Best Per Parent’ term.
DOI: 10.6084/m9.figshare.20267338
title: Additional file 15 of Distinct cell type-specific protein signatures in GRN and MAPT genetic subtypes of frontotemporal dementia

description: Additional file 15 Lists of SynGO enrichment analysis results for proteins differentially expressed in both temporal cortical FTD-MAPT vs NDC and AD vs NDC. SynGO enrichment analysis was performed for proteins differentially expressed at q &lt; 0.05, with proteins divided into lower and higher expressed proteins. For every SynGO term, the proteins within that term that were measured in the different FTD subtypes are given, as well the raw and multiple testing corrected p-value for the enrichment analysis.
DOI: 10.6084/m9.figshare.20267338.v1
title: Additional file 15 of Distinct cell type-specific protein signatures in GRN and MAPT genetic subtypes of frontotemporal dementia

description: Additional file 15 Lists of SynGO enrichment analysis results for proteins differentially expressed in both temporal cortical FTD-MAPT vs NDC and AD vs NDC. SynGO enrichment analysis was performed for proteins differentially expressed at q &lt; 0.05, with proteins divided into lower and higher expressed proteins. For every SynGO term, the proteins within that term that were measured in the different FTD subtypes are given, as well the raw and multiple testing corrected p-value for the enrichment analysis.