cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1884209.08fu
title: SH1884209.08FU

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/sh2861254.08fu
title: SH2861254.08FU

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/sh2861255.08fu
title: SH2861255.08FU

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/sh2861256.08fu
title: SH2861256.08FU

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/sh1884210.08fu
title: SH1884210.08FU

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/sh1884211.08fu
title: SH1884211.08FU

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.20079156.v1
title: Additional file 3 of Genome-wide identification, phylogeny and expression analysis of the SPL gene family and its important role in salt stress in Medicago sativa L.

description: Additional file 3: Table S3. Cis_elements contained in the MsSPL genes promoter region.
DOI: 10.6084/m9.figshare.20079159
title: Additional file 4 of Genome-wide identification, phylogeny and expression analysis of the SPL gene family and its important role in salt stress in Medicago sativa L.

description: Additional file 4: Table S4. The primer sequences of qRT-PCR.
DOI: 10.6084/m9.figshare.17981950.v1
title: Additional file 8 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 8: Cluster detection at the known gene loci under positive selection from the human 1000 Genomes Project genotype datasets.
DOI: 10.6084/m9.figshare.13787635
title: Additional file 2 of Efficient CRISPR/Cas9 mediated Pooled-sgRNAs assembly accelerates targeting multiple genes related to male sterility in cotton

description: Additional file 2. List of the selected sgRNAs and their corresponding genes.
DOI: 10.6084/m9.figshare.20079150
title: Additional file 1 of Genome-wide identification, phylogeny and expression analysis of the SPL gene family and its important role in salt stress in Medicago sativa L.

description: Additional file 1: Table S1. List of the 76 MsSPL genes identified in this study.
DOI: 10.6084/m9.figshare.17981926.v1
title: Additional file 1 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 1: Table S1. The list of all segregating SNPs in the core genome of S. pyogenes. Table S2. The list of 46 strains of S. pyogenes used for variant detection. Table S3. SNP clusters identified by SweepCluster from all segregating SNPs of S. pyogenes. Table S4. The list of SNPs from S. pyogenes associated with the disease phenotype acute rheumatic fever (p-value ≤ 0.05). Table S5. SNP clusters identified by SweepCluster from the SNPs associated with the disease phenotype acute rheumatic fever for S. pyogenes.
DOI: 10.6084/m9.figshare.17981932.v1
title: Additional file 2 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 2: Table S6. The list of all segregating SNPs in the core genome of S. suis. Table S7. The list of 209 strains of S. suis used for variant detection. Table S8. SNP clusters identified by SweepCluster from all segregating SNPs of S. suis. Table S9. The list of SNPs from S. suis associated with the subpopulation differentiation (p-value ≤ 0.05). Table S10. SNP clusters identified by SweepCluster from the SNPs associated with population differentiation for S. suis.
DOI: 10.6084/m9.figshare.17981941.v1
title: Additional file 5 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 5: Clusters detected by SweepCluster for chromosome 2 variants between EUR-EAS selected at a series of Fst cutoff (0.4, 0.43, 0.45, 0.5, 0.55, 0.6, 0.65, and 0.7).
DOI: 10.6084/m9.figshare.17981944.v1
title: Additional file 6 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 6: Clusters detected by SweepCluster for chromosome 10 variants between EUR-EAS selected at a series of Fst cutoff (0.4, 0.43, 0.45, 0.5, 0.55, 0.6, 0.65, and 0.7).
DOI: 10.6084/m9.figshare.17981947.v1
title: Additional file 7 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 7: Clusters detected by SweepCluster for chromosome 10 variants between AFR-EAS selected at a series of Fst cutoff (0.4, 0.43, 0.45, 0.5, 0.55, 0.6, 0.65, and 0.7).
DOI: 10.6084/m9.figshare.17981950
title: Additional file 8 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 8: Cluster detection at the known gene loci under positive selection from the human 1000 Genomes Project genotype datasets.
DOI: 10.6084/m9.figshare.13787593
title: Additional file 9 of Genome-wide analysis of the apple CaCA superfamily reveals that MdCAX proteins are involved in the abiotic stress response as calcium transporters

description: Additional file 9. Sequences of the promoter regions (− 1500 bp) of MdCAX genes.
DOI: 10.6084/m9.figshare.17982016
title: Additional file 1 of Genome-wide association study identifies SNPs for growth performance and serum indicators in Valgus-varus deformity broilers (Gallus gallus) using ddGBS sequencing

description: Additional file 1: Table S1. The phenotypic information of VVD and sound broile. Table S2. Annotated candidate genes to VVD trait. Table S3. Annotated candidate genes to ALP trait. Table S4. GO enrichment analysis of the candidate genes for VVD trait in Valgus-varus Deformity Broilers. Table S5. KEGG enrichment analysis of the candidate genes for VVD trait. Table S6. GO enrichment analysis of the candidate genes for ALP trait in Valgus-varus Deformity Broilers. Table S7. KEGG enrichment analysis of the candidate genes for ALP trait in Valgus-varus Deformity Broilers.
DOI: 10.6084/m9.figshare.13787635.v1
title: Additional file 2 of Efficient CRISPR/Cas9 mediated Pooled-sgRNAs assembly accelerates targeting multiple genes related to male sterility in cotton

description: Additional file 2. List of the selected sgRNAs and their corresponding genes.
DOI: 10.6084/m9.figshare.17982185.v1
title: Additional file 3 of Complete chloroplast genomes of Rubus species (Rosaceae) and comparative analysis within the genus

description: Additional file 3: Table S3. Taxonomic and accession information for samples used in the study.
DOI: 10.6084/m9.figshare.17982191
title: Additional file 5 of Complete chloroplast genomes of Rubus species (Rosaceae) and comparative analysis within the genus

description: Additional file 5: Table S5. Statistics of longer repeats in each species of Rubus. (XLSX 94 kb)
DOI: 10.6084/m9.figshare.20078712.v1
title: Additional file 8 of MMP2 and MMP9 contribute to lung ischemia–reperfusion injury via promoting pyroptosis in mice

description: Additional file 8: Lung injury score data. (Figure 3B)
DOI: 10.6084/m9.figshare.13787641.v1
title: Additional file 3 of Efficient CRISPR/Cas9 mediated Pooled-sgRNAs assembly accelerates targeting multiple genes related to male sterility in cotton

description: Additional file 3. List of primers sequences used in this study.
DOI: 10.6084/m9.figshare.20078694
title: Additional file 2 of MMP2 and MMP9 contribute to lung ischemia–reperfusion injury via promoting pyroptosis in mice

description: Additional file 2: The dataset of GSE9634 which is recorded the rat lung ischemia–reperfusion tissue RNA-Seq data after IR-30min, in the GEO database. (Figure 1C)
DOI: 10.6084/m9.figshare.17982188.v1
title: Additional file 4 of Complete chloroplast genomes of Rubus species (Rosaceae) and comparative analysis within the genus

description: Additional file 4: Table S4. Statistics of simple sequence repeats in each species of Rubus. (XLSX 116 kb)
DOI: 10.6084/m9.figshare.20078694.v1
title: Additional file 2 of MMP2 and MMP9 contribute to lung ischemia–reperfusion injury via promoting pyroptosis in mice

description: Additional file 2: The dataset of GSE9634 which is recorded the rat lung ischemia–reperfusion tissue RNA-Seq data after IR-30min, in the GEO database. (Figure 1C)
DOI: 10.6084/m9.figshare.20079153.v1
title: Additional file 2 of Genome-wide identification, phylogeny and expression analysis of the SPL gene family and its important role in salt stress in Medicago sativa L.

description: Additional file 2: Table S2. One-to-one orthologous relationships between Medicago sativa L. and other plants.
DOI: 10.6084/m9.figshare.20079159.v1
title: Additional file 4 of Genome-wide identification, phylogeny and expression analysis of the SPL gene family and its important role in salt stress in Medicago sativa L.

description: Additional file 4: Table S4. The primer sequences of qRT-PCR.
DOI: 10.6084/m9.figshare.17982185
title: Additional file 3 of Complete chloroplast genomes of Rubus species (Rosaceae) and comparative analysis within the genus

description: Additional file 3: Table S3. Taxonomic and accession information for samples used in the study.
DOI: 10.6084/m9.figshare.17982188
title: Additional file 4 of Complete chloroplast genomes of Rubus species (Rosaceae) and comparative analysis within the genus

description: Additional file 4: Table S4. Statistics of simple sequence repeats in each species of Rubus. (XLSX 116 kb)
DOI: 10.6084/m9.figshare.20078691
title: Additional file 1 of MMP2 and MMP9 contribute to lung ischemia–reperfusion injury via promoting pyroptosis in mice

description: Additional file 1: The dataset of GSE9634 which is recorded the rat lung ischemia–reperfusion tissue RNA-Seq data after IR-3h, in the GEO database. (Figure 1E)
DOI: 10.6084/m9.figshare.20078712
title: Additional file 8 of MMP2 and MMP9 contribute to lung ischemia–reperfusion injury via promoting pyroptosis in mice

description: Additional file 8: Lung injury score data. (Figure 3B)
DOI: 10.6084/m9.figshare.17982179.v1
title: Additional file 2 of Complete chloroplast genomes of Rubus species (Rosaceae) and comparative analysis within the genus

description: Additional file 2: Table S2. Synonymous (Ks) and nonsynonymous (Ka) analysis of the eight species based on shared unique CDS genes, with Rubus tephrodes as the reference.
DOI: 10.6084/m9.figshare.17982205.v1
title: Additional file 3 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 3: Table S4. Previously validated fusions found in the MCF-7, K562, HCT-116, A549 and SK-BR-3 cancer cells lines.
DOI: 10.6084/m9.figshare.17982208
title: Additional file 4 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 4: Table S5. Output from JAFFAL applied to the MCF-7, K562, HCT-116 and A549 ONT datasets.
DOI: 10.6084/m9.figshare.17982211.v1
title: Additional file 5 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 5: Table S6. Output from JAFFAL applied to the MCF-7, HCT-116 and SK-BR-3 Pacbio datasets.
DOI: 10.6084/m9.figshare.19029521
title: Additional file 4 of Open chromatin interaction maps reveal functional regulatory elements and chromatin architecture variations during wheat evolution

description: Additional file 4: Table S5 The triads with chromatin interaction bias.
DOI: 10.6084/m9.figshare.17982208.v1
title: Additional file 4 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 4: Table S5. Output from JAFFAL applied to the MCF-7, K562, HCT-116 and A549 ONT datasets.
DOI: 10.6084/m9.figshare.17982214
title: Additional file 6 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 6: Table S8. Output from JAFFAL applied to the single-cell ONT dataset of five cancer cell lines mixed.
DOI: 10.6084/m9.figshare.20078691.v1
title: Additional file 1 of MMP2 and MMP9 contribute to lung ischemia–reperfusion injury via promoting pyroptosis in mice

description: Additional file 1: The dataset of GSE9634 which is recorded the rat lung ischemia–reperfusion tissue RNA-Seq data after IR-3h, in the GEO database. (Figure 1E)
DOI: 10.6084/m9.figshare.17982191.v1
title: Additional file 5 of Complete chloroplast genomes of Rubus species (Rosaceae) and comparative analysis within the genus

description: Additional file 5: Table S5. Statistics of longer repeats in each species of Rubus. (XLSX 94 kb)
DOI: 10.6084/m9.figshare.20078715.v1
title: Additional file 9 of MMP2 and MMP9 contribute to lung ischemia–reperfusion injury via promoting pyroptosis in mice

description: Additional file 9: The sample Cq value in RT-qPCR. (Figure 2A)
DOI: 10.6084/m9.figshare.17982179
title: Additional file 2 of Complete chloroplast genomes of Rubus species (Rosaceae) and comparative analysis within the genus

description: Additional file 2: Table S2. Synonymous (Ks) and nonsynonymous (Ka) analysis of the eight species based on shared unique CDS genes, with Rubus tephrodes as the reference.
DOI: 10.6084/m9.figshare.20078697.v1
title: Additional file 3 of MMP2 and MMP9 contribute to lung ischemia–reperfusion injury via promoting pyroptosis in mice

description: Additional file 3: The dataset of GSE127003 which is recorded before and after human lung transplantation RNA-Seq data of lung tissue, in the GEO database. (Figure 1A)
DOI: 10.6084/m9.figshare.17982199
title: Additional file 2 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 2: Table S1. Output from JAFFAL applied to the NA12878 nanopore cDNA and direct RNA datasets.
DOI: 10.6084/m9.figshare.17982199.v1
title: Additional file 2 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 2: Table S1. Output from JAFFAL applied to the NA12878 nanopore cDNA and direct RNA datasets.
DOI: 10.6084/m9.figshare.17982211
title: Additional file 5 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 5: Table S6. Output from JAFFAL applied to the MCF-7, HCT-116 and SK-BR-3 Pacbio datasets.
DOI: 10.6084/m9.figshare.17982214.v1
title: Additional file 6 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 6: Table S8. Output from JAFFAL applied to the single-cell ONT dataset of five cancer cell lines mixed.
DOI: 10.6084/m9.figshare.17982205
title: Additional file 3 of JAFFAL: detecting fusion genes with long-read transcriptome sequencing

description: Additional file 3: Table S4. Previously validated fusions found in the MCF-7, K562, HCT-116, A549 and SK-BR-3 cancer cells lines.
DOI: 10.6084/m9.figshare.13787524.v1
title: Additional file 10 of Genome-wide analysis of the apple CaCA superfamily reveals that MdCAX proteins are involved in the abiotic stress response as calcium transporters

description: Additional file 10: Table S3. Cis-elements identified in the promoter regions of MdCAX genes in apple. Plus and minus signs indicate whether the cis-element was located either the plus or minus strand.
DOI: 10.6084/m9.figshare.5400559
title: Sequential Design for Functional Calibration of Computer Models

description: The calibration of computer models using physical experimental data has received a compelling interest in the last decade. Recently, multiple works have addressed the functional calibration of computer models, where the calibration parameters are functions of the observable inputs rather than taking a set of fixed values as traditionally treated in the literature. While much of the recent work on functional calibration was focused on estimation, the issue of sequential design for functional calibration still presents itself as an open question. Addressing the sequential design issue is thus the focus of this article. We investigate different sequential design approaches and show that the simple separate design approach has its merit in practical use when designing for functional calibration. Analysis is carried out on multiple simulated and real-world examples.
DOI: 10.7298/azf0-hc03
title: Data and scripts from: Room temperature optically detected magnetic resonance of single spins in GaN
DOI: 10.5255/ukda-sn-856918
title: Perceiving Greater Commitment Increases Selfishness Among Disagreeable People, 2014-2022

description: The extent to which people believe their partners are committed to the relationship (i.e., perceived partner commitment) may influence the extent to which people behave in a selfish manner in their relationships; however, theory and research make competing predictions about the direction of this influence. On the one hand, people may behave less selfishly toward partners who they perceive are highly committed because they may reason that those committed partners would be more likely to reciprocate such selfless behavior compared to less committed partners. On the other hand, given that partners are more likely to minimize transgressions and less likely to end a relationship to the extent that they are committed to that relationship, people may behave more selfishly toward partners who they perceive are highly committed because they may expect fewer harmful consequences from behaving selfishly toward committed partners compared to less committed partners. Given these competing theoretical predictions, the current research seeks to identify whether perceived partner commitment increases or decreases intimates’ selfishness. One correlational study consisting of a highly diverse sample of individuals (n = 307), one observational study of newlywed couples (n = 202), and one experiment with undergraduate couples (n = 252) examined whether the implications of perceived partner commitment for selfish behaviors depend on agreeableness. Results demonstrated that perceiving high commitment resulted in more selfish behavior among disagreeable participants (Studies 1-3), but less selfish behavior among agreeable participants (Studies 1 and 3). Together, these results suggest that signaling commitment to disagreeable partners may backfire in romantic relationships.