cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26713900.v1
title: Additional file 1 of Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project

description: Additional file 1. Supplementary Information (Methodology of participating teams, Reanalysis of highly ranked variants by top performing teams in solved families, Supplemental Figures 1–2, and Supplemental References).
DOI: 10.6084/m9.figshare.26577179
title: Additional file 1 of Motor imagery EEG signal classification with a multivariate time series approach

description: Additional file 1. Results supporting the box-plots of precision, sensitivity and specificity along with additional metrics and graphs are available.
DOI: 10.6084/m9.figshare.26577179.v1
title: Additional file 1 of Motor imagery EEG signal classification with a multivariate time series approach

description: Additional file 1. Results supporting the box-plots of precision, sensitivity and specificity along with additional metrics and graphs are available.
DOI: 10.6084/m9.figshare.26618845.v1
title: Additional file 1 of Characterization of tumor microenvironment and tumor immunology based on the double-stranded RNA-binding protein related genes in cervical cancer

description: Additional file 1: Figure S1. Identification of dsRBPs expression feature correlated with HPV infection in CESC samples from TCGA-CESC cohort. Comparison in the ssGSEA scores of each dsRBP subtype in CESC samples classified by HPV status (A), hierarchical HPV call (B), hierarchical HPV clade (C) and HPV integration status (D). dsRBPs: double-stranded RNA-binding proteins; ssGSEA: single sample Gene Set Enrichment Analysis. *p &lt; 0.05; **p &lt; 0.01; ***p &lt; 0.001; ****p &lt; 0.0001; ns: non-significant. Figure S2. Tumor immunity related to dsRBPs expression patterns in cervical cancer. Analysis of the correlation between the expression seven dsRBPs subtypes and the level of immune score (A), tumor-infiltrated immune cells (B) and immune checkpoints (C). *p &lt; 0.05; **p &lt; 0.01; ***p &lt; 0.001; ****p &lt; 0.0001. Figure S3. Boxplot showed the different expression levels of ADAR and DDR subfamily members among CESC samples with different HPV infection status in the TCGA-CESC cohort. ADAR: adenosine deaminases acting on RNA, DDR: Dicer, Drosha, and Argonautes. *p &lt; 0.05; ns: non-significant. Figure S4. The correlation between clinical parameters and different clusters, such as age, T stage, N stage, M stage, and neoplasm disease stage. Figure S5. The distribution of HPV-infection patients in different dsRBP clusters. Figure S6. The Kaplan-Meier plots of overall survival stratified by age (≤ 60/&gt; 60), T stage (T1–2/T3–4), N stage (N0/N1+), M stage (M0/M1), and neoplasm disease stage (stage I–II/stage III–IV). Figure S7. Univariate and multivariate Cox regression analysis of risk score and clinicopathological parameters. Figure S8. Comparison the of dsRBPs signature risk scores among CESC patients with different HPV infection status. *p &lt; 0.05; **p &lt; 0.01; ns: non-significant. Difference in the dsRBPs signature risk scores between CESC samples classified by HPV status (A), hierarchical HPV call (B), hierarchical HPV clade (C) and HPV integration status (D). Figure S9. Oncoplot of the genomic alterations in hub genes identified in the cervical cancer samples from the TCGA database.
DOI: 10.6084/m9.figshare.26618848
title: Additional file 2 of Characterization of tumor microenvironment and tumor immunology based on the double-stranded RNA-binding protein related genes in cervical cancer

description: Additional file 2: Table S1. 35 dsRBPs colected and applied in current study. Table S2. Clinical characteristics of cervical cancer samples within different dsRBP clusters. Table S3. List of dsRBP cluster-associated DEGs. Table S4. List of prognostic dsRBP cluster-associated DEGs. Table S5. List of further achieved prognostic dsRBP cluster-associated DEGs after multistep filtering. Table S6. performance of signature in the TCGA-CESC cohort, GSE44001 cohort and CGCI-HTMCP-CC cohort. Table S7. Patients information stratified by the signature in the TCGA-CESC cohort. Table S8. Clinical feature information of the high- and low-risk group. Table S9. Sample information stratified by the signature in the GSE44001 validation cohort. Table S10. Sample information stratified by the signature in the CGCI-HTMCP-CC validation cohort. Table S11. Differentially expressed genes between Scissor+ and Scissor− cells.
DOI: 10.6084/m9.figshare.26618848.v1
title: Additional file 2 of Characterization of tumor microenvironment and tumor immunology based on the double-stranded RNA-binding protein related genes in cervical cancer

description: Additional file 2: Table S1. 35 dsRBPs colected and applied in current study. Table S2. Clinical characteristics of cervical cancer samples within different dsRBP clusters. Table S3. List of dsRBP cluster-associated DEGs. Table S4. List of prognostic dsRBP cluster-associated DEGs. Table S5. List of further achieved prognostic dsRBP cluster-associated DEGs after multistep filtering. Table S6. performance of signature in the TCGA-CESC cohort, GSE44001 cohort and CGCI-HTMCP-CC cohort. Table S7. Patients information stratified by the signature in the TCGA-CESC cohort. Table S8. Clinical feature information of the high- and low-risk group. Table S9. Sample information stratified by the signature in the GSE44001 validation cohort. Table S10. Sample information stratified by the signature in the CGCI-HTMCP-CC validation cohort. Table S11. Differentially expressed genes between Scissor+ and Scissor− cells.
DOI: 10.6084/m9.figshare.26618845
title: Additional file 1 of Characterization of tumor microenvironment and tumor immunology based on the double-stranded RNA-binding protein related genes in cervical cancer

description: Additional file 1: Figure S1. Identification of dsRBPs expression feature correlated with HPV infection in CESC samples from TCGA-CESC cohort. Comparison in the ssGSEA scores of each dsRBP subtype in CESC samples classified by HPV status (A), hierarchical HPV call (B), hierarchical HPV clade (C) and HPV integration status (D). dsRBPs: double-stranded RNA-binding proteins; ssGSEA: single sample Gene Set Enrichment Analysis. *p &lt; 0.05; **p &lt; 0.01; ***p &lt; 0.001; ****p &lt; 0.0001; ns: non-significant. Figure S2. Tumor immunity related to dsRBPs expression patterns in cervical cancer. Analysis of the correlation between the expression seven dsRBPs subtypes and the level of immune score (A), tumor-infiltrated immune cells (B) and immune checkpoints (C). *p &lt; 0.05; **p &lt; 0.01; ***p &lt; 0.001; ****p &lt; 0.0001. Figure S3. Boxplot showed the different expression levels of ADAR and DDR subfamily members among CESC samples with different HPV infection status in the TCGA-CESC cohort. ADAR: adenosine deaminases acting on RNA, DDR: Dicer, Drosha, and Argonautes. *p &lt; 0.05; ns: non-significant. Figure S4. The correlation between clinical parameters and different clusters, such as age, T stage, N stage, M stage, and neoplasm disease stage. Figure S5. The distribution of HPV-infection patients in different dsRBP clusters. Figure S6. The Kaplan-Meier plots of overall survival stratified by age (≤ 60/&gt; 60), T stage (T1–2/T3–4), N stage (N0/N1+), M stage (M0/M1), and neoplasm disease stage (stage I–II/stage III–IV). Figure S7. Univariate and multivariate Cox regression analysis of risk score and clinicopathological parameters. Figure S8. Comparison the of dsRBPs signature risk scores among CESC patients with different HPV infection status. *p &lt; 0.05; **p &lt; 0.01; ns: non-significant. Difference in the dsRBPs signature risk scores between CESC samples classified by HPV status (A), hierarchical HPV call (B), hierarchical HPV clade (C) and HPV integration status (D). Figure S9. Oncoplot of the genomic alterations in hub genes identified in the cervical cancer samples from the TCGA database.
DOI: 10.15468/dl.2v9dqe
title: Occurrence Download

description: A dataset containing 64016 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-104.95501 24.92887,-103.31427 24.92887,-103.31427 25.61850,-104.95501 25.61850,-104.95501 24.92887))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 64016 records from 304 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017816-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/d5zvvy
title: Medicinal Herb Garden (CNR-ISB-MGH)

description: The Medicinal Herb Garden (also known as "Giardino dei Semplici") is a botanic collection of more than 100 living plant species, primarily officinal and wild edible (alimurgic) plants. The collection aims to preserve local biodiversity and disseminate knowledge on botany sciences and medicinal plants. It also promotes pharmacological and phytosanitary research to deepen and apply knowledge about the biological properties of herbs and their extracts.Medicinal and wild edible plants are conserved, whose main taxa are dicots, monocots and Ginkgoopsida. Lamiaceae, Asteraceae, Brassicaceae, Myrtaceae, Apiaceae, Caryophyllaceae, Rosaceae, and Plantaginaceae are the main represented families.The main purposes of the collection are: preservation and cultivation; transcriptional and metabolic characterisation; active principles and essential oils extraction; biochemical characterization; pharmacological and phytochemical studies.
DOI: 10.15468/dl.usv7g9
title: Occurrence Download

description: A dataset containing 11858 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Gossypium hirsutum L., Gossypium barbadense L., Gossypium mustelinum Miers, Kokia drynarioides (Seem.) Lewton, Kokia cookei O.Deg., Kokia kauaiensis (Rock) O.Deg. & I.Deg., Gossypioides kirkii (Mast.) Skovst.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 11858 records from 348 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017817-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.22137506
title: Summary calculations of soil P stocks from the McDowell et al. (2023) and Ringeval et al. (2024) databases.

description: Data outline country and continential stocks of Olsen and Total phosphorus and the data used to convert between Olsen and Total phosphorus
DOI: 10.15156/bio/sh0190965.10fu
title: SH0190965.10FU

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/sh0190966.10fu
title: SH0190966.10FU

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/sh0190967.10fu
title: SH0190967.10FU

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/sh0190968.10fu
title: SH0190968.10FU

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/sh0190969.10fu
title: SH0190969.10FU

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/sh0190970.10fu
title: SH0190970.10FU

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/sh0190971.10fu
title: SH0190971.10FU

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/sh0190972.10fu
title: SH0190972.10FU

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/sh0190973.10fu
title: SH0190973.10FU

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/sh0190974.10fu
title: SH0190974.10FU

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.vh72dn
title: Occurrence Download

description: A dataset containing 595614 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is LACM Vertebrate Collection"
 ]
}

 The dataset includes 595614 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043534-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5n4cfj
title: Occurrence Download

description: A dataset containing 5183663 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "Geometry POLYGON((-61.17822 -26.41826,-32.2711 14.61749,-32.2711 15.38019,-92.47498 15.38019,-61.17822 -26.41826))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5183663 records from 1675 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000135-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7cc9nh
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capsicum annuum",
 "Country is Madagascar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 16 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031192-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.whhgg9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alcippe nipalensis",
 "Country is one of (Brunei Darussalam, Indonesia, Philippines, Timor-Leste, Singapore)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031191-250920141307145/datasets/export for details.