cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1378747.10fu
title: SH1378747.10FU

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/sh1378748.10fu
title: SH1378748.10FU

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: 10.5281/zenodo.18227178
title: Soil Texture and Prediction Dataset for Shaanxi, China

description: The dataset includes structured CSV files containing the environmental covariates and target variables required for predicting soil texture at different depths. The target variables — sand, silt, and clay — are expressed in percentage units. These CSV files serve as the primary input for the machine learning modeling process, encompassing all feature variables and corresponding values for each soil texture component.

A supplementary Excel file is provided, which consolidates the performance evaluation results of the predictive models. The file is organized into three separate sheets, labeled sand, silt, and clay, each containing detailed statistical metrics and validation outcomes specific to the corresponding soil texture fraction. This structured format allows for clear and systematic comparison of model accuracy across different soil components.

Spatial predictions of soil texture are delivered in raster format, with each file representing a specific depth interval. The naming convention follows a depth-code system: 05for 0–5 cm, 520for 5–20 cm, 2040for 20–40 cm, 4060for 40–60 cm, and 60100for 60–100 cm.
DOI: 10.5281/zenodo.18227179
title: Soil Texture and Prediction Dataset for Shaanxi, China

description: The dataset includes structured CSV files containing the environmental covariates and target variables required for predicting soil texture at different depths. The target variables — sand, silt, and clay — are expressed in percentage units. These CSV files serve as the primary input for the machine learning modeling process, encompassing all feature variables and corresponding values for each soil texture component.

A supplementary Excel file is provided, which consolidates the performance evaluation results of the predictive models. The file is organized into three separate sheets, labeled sand, silt, and clay, each containing detailed statistical metrics and validation outcomes specific to the corresponding soil texture fraction. This structured format allows for clear and systematic comparison of model accuracy across different soil components.

Spatial predictions of soil texture are delivered in raster format, with each file representing a specific depth interval. The naming convention follows a depth-code system: 05for 0–5 cm, 520for 5–20 cm, 2040for 20–40 cm, 4060for 40–60 cm, and 60100for 60–100 cm.
DOI: 10.15156/bio/sh1378751.10fu
title: SH1378751.10FU

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/sh1378752.10fu
title: SH1378752.10FU

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/sh1378754.10fu
title: SH1378754.10FU

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/sh1378756.10fu
title: SH1378756.10FU

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: 10.15468/dl.g399jd
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.30_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Taiwania flousiana Gaussen"
 ]
}

 The dataset includes 11 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022457-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yhktza
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002085-160822134323880/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7bu66f
title: Occurrence Download

description: A dataset containing 208116449 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Specimen",
 "BasisOfRecord is Fossil",
 "BasisOfRecord is Living Specimen",
 "BasisOfRecord is Unknown evidence"
 ]
 },
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 208116449 records from 22772 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063504-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3q8zsw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((151.7422 19.2682, 166.6545 19.2682, 166.6545 47.74255, 151.7422 47.74255, 151.7422 19.2682))",
 "ScientificName is one of (species, Potamogeton gramineus, Allium cepa, Cardamine pratensis, Draba alpina, Silene uralensis, Medicago sativa, Pisum sativum, Quercus lobata, Quercus suber, Pinguicula vulgaris, Viola mirabilis, Carex arctogena, Carex scirpoidea, Luzula spicata, Calamagrostis purpurea, Morus notabilis, Equisetum scirpoides, Lemna minor, Lemna trisulca, Hydrocharis morsus-ranae, Najas marina, Potamogeton alpinus, Potamogeton berchtoldii, Potamogeton friesii, Potamogeton natans, Potamogeton obtusifolius, Potamogeton perfoliatus, Potamogeton praelongus, Stuckenia filiformis, Stuckenia vaginata, Zannichellia palustris, Triantha occidentalis, Daucus carota, Pimpinella saxifraga, Elaeis guineensis, Allium schoenoprasum, Asparagus officinalis, Achillea millefolium, Artemisia absinthium, Artemisia vulgaris, Bidens cernua, Carduus crispus, Cirsium arvense, Cirsium heterophyllum, Cirsium oleraceum, Doronicum pardalianches, Erigeron canadensis, Helianthus annuus, Lactuca sativa, Leontodon hispidus, Omalotheca norvegica, Saussurea alpina, Scorzoneroides autumnalis, Sonchus arvensis, Campanula latifolia, Myosotis arvensis, Brassica napus, Brassica oleracea, Cardamine bulbifera, Cochlearia danica, Cochlearia officinalis, Raphanus sativus, Cerastium maximum, Minuartia stricta, Sagina alexandrae, Sagina caespitosa, Sagina nodosa, Saponaria officinalis, Silene flos-cuculi, Silene ostenfeldii, Spinacia oleracea)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001011-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.29146562
title: Additional file 3 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 3. Table S2. Cell line data used in analyses of allelic expression status and associations with drug response.
DOI: 10.6084/m9.figshare.29146562.v1
title: Additional file 3 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 3. Table S2. Cell line data used in analyses of allelic expression status and associations with drug response.
DOI: 10.6084/m9.figshare.29146565
title: Additional file 4 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 4. Table S3. List of 108 CCLE cell lines with matching RNA-seq, WES, and copy number data which were included in the analysis of allelic expression patterns, and available drug response information for each cell line.
DOI: 10.6084/m9.figshare.29146565.v1
title: Additional file 4 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 4. Table S3. List of 108 CCLE cell lines with matching RNA-seq, WES, and copy number data which were included in the analysis of allelic expression patterns, and available drug response information for each cell line.
DOI: 10.6084/m9.figshare.29146571
title: Additional file 6 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 6. Table S4. Top 60 genes which were not included in the initial list of 94 imprinted genes and were found to have predominantly monoallelic expression in the pancancer analysis of 108 CCLE cell lines.
DOI: 10.6084/m9.figshare.29146571.v1
title: Additional file 6 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 6. Table S4. Top 60 genes which were not included in the initial list of 94 imprinted genes and were found to have predominantly monoallelic expression in the pancancer analysis of 108 CCLE cell lines.
DOI: 10.6084/m9.figshare.29146574
title: Additional file 7 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 7. Table S5. Numbers of agents included in association analyses of in vitro drug response with allelic expression patterns and overall expression levels of isoforms.
DOI: 10.6084/m9.figshare.29146574.v1
title: Additional file 7 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 7. Table S5. Numbers of agents included in association analyses of in vitro drug response with allelic expression patterns and overall expression levels of isoforms.
DOI: 10.6084/m9.figshare.29146589
title: Additional file 12 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 12. Table S6. Gene level allelic expression patterns of the previously reported 94 imprinted genes among 108 CCLE cell lines.
DOI: 10.6084/m9.figshare.29146595
title: Additional file 14 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 14. Table S7. Average proportions (%) of transcriptome-wide allelic expression patterns of genes, isoforms, and individual exons with heterozygous SNVs in 108 CCLE cell lines .
DOI: 10.6084/m9.figshare.29146595.v1
title: Additional file 14 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 14. Table S7. Average proportions (%) of transcriptome-wide allelic expression patterns of genes, isoforms, and individual exons with heterozygous SNVs in 108 CCLE cell lines .
DOI: 10.6084/m9.figshare.29146589.v1
title: Additional file 12 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 12. Table S6. Gene level allelic expression patterns of the previously reported 94 imprinted genes among 108 CCLE cell lines.
DOI: 10.6084/m9.figshare.29146598
title: Additional file 15 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 15. Table S8. Gene level allelic expression patterns of non-imprinted control genes.
DOI: 10.6084/m9.figshare.29146598.v1
title: Additional file 15 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 15. Table S8. Gene level allelic expression patterns of non-imprinted control genes.
DOI: 10.6084/m9.figshare.29146604
title: Additional file 17 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 17. Table S9. Allelic expression patterns of isoforms of the 94 imprinted genes.
DOI: 10.6084/m9.figshare.29146604.v1
title: Additional file 17 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 17. Table S9. Allelic expression patterns of isoforms of the 94 imprinted genes.
DOI: 10.6084/m9.figshare.29146610
title: Additional file 19 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 19. Table S10. Numbers and proportions of monoallelically and biallelically expressed isoforms of PLAGL1 in different cancer categories.
DOI: 10.6084/m9.figshare.29146610.v1
title: Additional file 19 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 19. Table S10. Numbers and proportions of monoallelically and biallelically expressed isoforms of PLAGL1 in different cancer categories.
DOI: 10.6084/m9.figshare.29146613
title: Additional file 20 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 20. Table S11. Concordance among isoform level allelic expression of CCLE cell lines in our study with previously reported whole gene level results of Martin-Trujillo et al. (2017) in matching COSMIC cell lines.
DOI: 10.6084/m9.figshare.29146613.v1
title: Additional file 20 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 20. Table S11. Concordance among isoform level allelic expression of CCLE cell lines in our study with previously reported whole gene level results of Martin-Trujillo et al. (2017) in matching COSMIC cell lines.
DOI: 10.6084/m9.figshare.29146622
title: Additional file 23 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 23. Table S12. Associations of allelic expression patterns of isoform groups of imprinted genes and other genes with predominantly monoallelic expression with in vitro drug response satisfying pFDR &lt; 0.125.
DOI: 10.6084/m9.figshare.29146622.v1
title: Additional file 23 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 23. Table S12. Associations of allelic expression patterns of isoform groups of imprinted genes and other genes with predominantly monoallelic expression with in vitro drug response satisfying pFDR &lt; 0.125.
DOI: 10.6084/m9.figshare.29146625
title: Additional file 24 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 24. Table S13. Spearman correlation of log(IC50) and mean allelic expression levels of isoform groups of imprinted genes and other genes with predominantly monoallelic expression with in vitro drug response satisfying pFDR &lt; 0.125.
DOI: 10.6084/m9.figshare.29146625.v1
title: Additional file 24 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 24. Table S13. Spearman correlation of log(IC50) and mean allelic expression levels of isoform groups of imprinted genes and other genes with predominantly monoallelic expression with in vitro drug response satisfying pFDR &lt; 0.125.
DOI: 10.6084/m9.figshare.29146628
title: Additional file 25 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 25. Table S14. Associations of allelic expression patterns of isoform groups of imprinted genes and other genes with predominantly monoallelic expression with isoform expression satisfying pFDR &lt; 0.125.
DOI: 10.6084/m9.figshare.29146628.v1
title: Additional file 25 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 25. Table S14. Associations of allelic expression patterns of isoform groups of imprinted genes and other genes with predominantly monoallelic expression with isoform expression satisfying pFDR &lt; 0.125.
DOI: 10.6084/m9.figshare.29146631
title: Additional file 26 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 26. Table S15. Counts of the expressed allele in monoallelically expressed genes and isoforms and of both alleles in the genomic data for heterozygous SNVs located within 94 imprinted genes and 60 additional genes with predominantly monoallelic expression.
DOI: 10.6084/m9.figshare.29146631.v1
title: Additional file 26 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 26. Table S15. Counts of the expressed allele in monoallelically expressed genes and isoforms and of both alleles in the genomic data for heterozygous SNVs located within 94 imprinted genes and 60 additional genes with predominantly monoallelic expression.
DOI: 10.6084/m9.figshare.29146634
title: Additional file 27 of Allelic expression patterns of imprinted and non-imprinted genes in cancer cell lines from multiple histologies

description: Supplementary Material 27. Table S16. Results of the two-sided binomial test for preferential monoallelic expression of sequence variants.