cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0184563.10fu
title: SH0184563.10FU

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/sh0184564.10fu
title: SH0184564.10FU

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/sh0184565.10fu
title: SH0184565.10FU

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.3d9p9j
title: Occurrence Download

description: A dataset containing 25773 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Psilocybe (Fr.) P.Kumm.",
 "HasCoordinate is true",
 "BasisOfRecord is Human Observation"
 ]
}

 The dataset includes 25773 records from 232 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068467-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/btwpwh8292.3
title: d13CairCO2_LOESS_Interpolation

description: This is a smoothed curve of d13C in atmospheric CO2 from 16100 BCE to 2010 CE, based on data from Antarctic ice-cores (Eyer & Leuenberger, pers. comm.; Francey et al., 1999; Indermühle et al., 1999;Leuenberger et al., 1992) and flask data from two Antarctic stations (Halley Bay and Palmer Station) of the NOAA ESRL Carbon Cycle Cooperative Global Air Sampling Network.

If you use the interpolation curve, please ALWAYS refer to:
1) the NOAA ESRL Carbon Cycle Cooperative Global Air Sampling Network:
https://gml.noaa.gov/aftp/data/trace_gases/co2c13/flask/README_surface_flask_co2c13.html
2) the original publication of the interpolation curve:
Ferrio JP, Araus JL, Buxó R, Voltas J, Bort J (2005) Water management practices and climate in ancient agriculture: inference from the stable isotope composition of archaeobotanical remains. Vegetation History and Archaeobotany 14:510-517

Please cite also the original references of ice-core data:
Francey RJ, Allison CE, Etheridge DM, Trudinger CM, Enting IG, Leuenberger M, Langenfelds RL, Michel E, Steele LP (1999) A 1000-year high precision record of delta C-13 in atmospheric CO2. Tellus B 51:170-193 
Indermühle A, Stocker TF, Joos F, Fischer H, Smith HJ, Wahlen M, Deck B, Mastroianni D, Tschumi J, Blunier T, Meyer R, Stauffer B (1999) Holocene carbon-cycle dynamics based on CO2 trapped in ice at Taylor Dome, Antarctica. Nature 398:121-126
Leuenberger M, Siegenthaler U, Langway CC (1992) Carbon isotope composition of atmospheric CO2 during the last ice age from an Antartic ice core. Nature 357:488-490 

IMPORTANT NOTE: this dataset should be only used to apply the interpolation curve, 
e.g. as reference for d13C in archaeobotanical, wood charcoal or tree-rings
Original values from ice-cores and NOAA ESRL should be retrieved (and cited) from their original sources

BEAR IN MIND THAT THIS IS AN APPROXIMATION:
1) Ice core data, particularly regarding trapped CO2, has considerably dating errors
2) The data is based on Antarctic ice cores only. Considerable spatial variability in CO2 is expected 

METHODS:
Due to the much higher time resolution available for the last 2 centuries, the smoothing was performed dividing the data in two overlapping sections (-16100 to 1800) and (1760-2003).
The smoothing was done by fitting locally weighted least squares (LOESS) regression curves (Cleveland 1979) with a span of 0.1 and 0.4 for the first and second section, respectively.

References
Cleveland WS (1979) Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association 74:829-836

Contact: https://www.juanpedroferrio.com/
DOI: 10.15468/dl.mz2ad7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.119599 -32.256943, 149.119599 -32.259189, 149.12409 -32.259189, 149.12409 -32.256943, 149.119599 -32.256943))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065717-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26564136
title: Additional file 2 of Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis

description: Additional file 2: Table S1. Excel file containing this table is attached. Clinical characteristics of COPD participants vary across clusters. The variables are sorted by descending significance. P-values were calculated with a Kruskal-Wallis test for continuous and ordinal variables and or a Chi-squared test for discrete and binary variables and asses if there are differences in variable distribution among clusters. Variable means (standard deviations) are also reported for all COPD participants overall, each COPD cluster, and all control subjects for comparison.
DOI: 10.15468/dl.gtt635
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.250706 -36.589089, 144.250706 -36.591335, 144.248461 -36.591335, 144.248461 -36.593581, 144.255198 -36.593581, 144.255198 -36.589089, 144.250706 -36.589089))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065718-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26643934
title: Additional file 1 of Exploration of key drug target proteins highlighting their related regulatory molecules, functional pathways and drug candidates associated with delirium: evidence from meta-data analyses

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26643934.v1
title: Additional file 1 of Exploration of key drug target proteins highlighting their related regulatory molecules, functional pathways and drug candidates associated with delirium: evidence from meta-data analyses

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26588292
title: Additional file 2 of Association of gut microbial dysbiosis with disease severity, response to therapy and disease outcomes in Indian patients with COVID-19

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26588292.v1
title: Additional file 2 of Association of gut microbial dysbiosis with disease severity, response to therapy and disease outcomes in Indian patients with COVID-19

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26643940
title: Additional file 3 of Exploration of key drug target proteins highlighting their related regulatory molecules, functional pathways and drug candidates associated with delirium: evidence from meta-data analyses

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26643940.v1
title: Additional file 3 of Exploration of key drug target proteins highlighting their related regulatory molecules, functional pathways and drug candidates associated with delirium: evidence from meta-data analyses

description: Supplementary Material 3
DOI: 10.15468/dl.ddfs2b
title: Occurrence Download

description: A dataset containing 2256 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Issue is one of (Country mismatch, The taxon ID was not used in backbone matching, The scientific name differs on the record from that found in the checklist, The backbone match found using the taxon IDs differs from what would be found if using the scientific names , Individual count invalid, Individual count conflicts with occurrence status)",
 "OccurrenceStatus is Present",
 "TaxonKey is Apolemichthys Burton, 1934"
 ]
}

 The dataset includes 2256 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065719-240626123714530/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.26588247
title: Additional file 6 of Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.26588244
title: Additional file 5 of Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.26588244.v1
title: Additional file 5 of Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.26588247.v1
title: Additional file 6 of Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.26564139.v1
title: Additional file 3 of Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis

description: Additional file 3: Table S2. Excel file containing this table is attached. Differences in clinical characteristics between clusters 0 and 1. The variables are sorted by descending significance. P-values were calculated with a Wilcoxon rank sum test for continuous and ordinal variables and or a Chi-squared test for discrete and binary variables and asses if there are differences in variable distribution between these clusters.
DOI: 10.6084/m9.figshare.26643973
title: Additional file 1 of Logic-based modeling and drug repurposing for the prediction of novel therapeutic targets and combination regimens against E2F1-driven melanoma progression

description: Supplementary Material 1: Identification and prioritization of motifs to derive a core regulatory network: (1a) FBLs in E2F1 map and ranking score (1b) top-ranked FBLs in melanoma (1c) weighting scenarios for motif prioritization and (1d) regulatory core interactions
DOI: 10.6084/m9.figshare.26643973.v1
title: Additional file 1 of Logic-based modeling and drug repurposing for the prediction of novel therapeutic targets and combination regimens against E2F1-driven melanoma progression

description: Supplementary Material 1: Identification and prioritization of motifs to derive a core regulatory network: (1a) FBLs in E2F1 map and ranking score (1b) top-ranked FBLs in melanoma (1c) weighting scenarios for motif prioritization and (1d) regulatory core interactions
DOI: 10.6084/m9.figshare.26643976
title: Additional file 2 of Logic-based modeling and drug repurposing for the prediction of novel therapeutic targets and combination regimens against E2F1-driven melanoma progression

description: Supplementary Material 2: Safety profile assessment of candidate drugs and prediction of binding affinity: (2a) Prediction of ADMET risk, pharmacokinetics, drug-likeness, and medicinal friendliness score of FDA-approved candidate drugs docked to protein signatures AKT1 and MDM2. (2b) binding affinity of AKT1 to candidate drugs and (2c) binding affinity of MDM2 to candidate drugs
DOI: 10.6084/m9.figshare.26643976.v1
title: Additional file 2 of Logic-based modeling and drug repurposing for the prediction of novel therapeutic targets and combination regimens against E2F1-driven melanoma progression

description: Supplementary Material 2: Safety profile assessment of candidate drugs and prediction of binding affinity: (2a) Prediction of ADMET risk, pharmacokinetics, drug-likeness, and medicinal friendliness score of FDA-approved candidate drugs docked to protein signatures AKT1 and MDM2. (2b) binding affinity of AKT1 to candidate drugs and (2c) binding affinity of MDM2 to candidate drugs
DOI: 10.6084/m9.figshare.26643985
title: Additional file 2 of Changes in physicochemical properties and microbial community succession during leaf stacking fermentation

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26643985.v1
title: Additional file 2 of Changes in physicochemical properties and microbial community succession during leaf stacking fermentation

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26644006
title: Additional file 3 of Impact of the COVID-19 pandemic on internal medicine training in the United States: results from a national survey

description: Additional file 3.
DOI: 10.6084/m9.figshare.26644006.v1
title: Additional file 3 of Impact of the COVID-19 pandemic on internal medicine training in the United States: results from a national survey

description: Additional file 3.
DOI: 10.15468/dl.3rcx9m
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-178.53896 -74.91951,-178.76948 -89.21185,-171.39279 -85.75402,-174.38957 -74.22795,-178.53896 -74.91951))",
 "TaxonKey is Sarcoptiformes"
 ]
}

 The dataset includes 52 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065720-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yefxj2
title: Occurrence Download

description: A dataset containing 348 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((149.409307 -32.243468, 149.409307 -32.245714, 149.404815 -32.245714, 149.404815 -32.250206, 149.402569 -32.250206, 149.402569 -32.254697, 149.416044 -32.254697, 149.416044 -32.259189, 149.41829 -32.259189, 149.41829 -32.261435, 149.416044 -32.261435, 149.416044 -32.265926, 149.425027 -32.265926, 149.425027 -32.259189, 149.420536 -32.259189, 149.420536 -32.254697, 149.41829 -32.254697, 149.41829 -32.252451, 149.416044 -32.252451, 149.416044 -32.243468, 149.409307 -32.243468)), ((149.416044 -32.259189, 149.404815 -32.259189, 149.404815 -32.261435, 149.402569 -32.261435, 149.402569 -32.26368, 149.411553 -32.26368, 149.411553 -32.261435, 149.416044 -32.261435, 149.416044 -32.259189)))"
 ]
}

 The dataset includes 348 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065721-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7xrmab
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((143.835234 -36.591335, 143.837479 -36.591335, 143.837479 -36.593581, 143.8532 -36.593581, 143.8532 -36.598072, 143.855446 -36.598072, 143.855446 -36.595827, 143.859937 -36.595827, 143.859937 -36.591335, 143.857692 -36.591335, 143.857692 -36.586843, 143.835234 -36.586843, 143.835234 -36.591335)), ((143.835234 -36.591335, 143.830742 -36.591335, 143.830742 -36.598072, 143.835234 -36.598072, 143.835234 -36.591335)), ((143.857692 -36.586843, 143.859937 -36.586843, 143.859937 -36.584598, 143.857692 -36.584598, 143.857692 -36.586843)), ((143.859937 -36.584598, 143.864429 -36.584598, 143.864429 -36.582352, 143.859937 -36.582352, 143.859937 -36.584598)), ((143.864429 -36.582352, 143.866675 -36.582352, 143.866675 -36.575614, 143.864429 -36.575614, 143.864429 -36.582352)))"
 ]
}

 The dataset includes 45 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065722-240626123714530/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.26644018
title: Additional file 2 of Identifying the driver miRNAs with somatic copy number alterations driving dysregulated ceRNA networks in cancers

description: Additional file 2. Table S1. Hallmark functional enrichment of reversely dysregulated expression targets induced by SCNA driving miRNA.
DOI: 10.6084/m9.figshare.26644018.v1
title: Additional file 2 of Identifying the driver miRNAs with somatic copy number alterations driving dysregulated ceRNA networks in cancers

description: Additional file 2. Table S1. Hallmark functional enrichment of reversely dysregulated expression targets induced by SCNA driving miRNA.
DOI: 10.6084/m9.figshare.26644021
title: Additional file 3 of Identifying the driver miRNAs with somatic copy number alterations driving dysregulated ceRNA networks in cancers

description: Additional file 3. Table S2. Hallmark functional enrichment analysis of dysregulated active targets of driver miRNAs.
DOI: 10.6084/m9.figshare.26644021.v1
title: Additional file 3 of Identifying the driver miRNAs with somatic copy number alterations driving dysregulated ceRNA networks in cancers

description: Additional file 3. Table S2. Hallmark functional enrichment analysis of dysregulated active targets of driver miRNAs.
DOI: 10.6084/m9.figshare.26644024
title: Additional file 4 of Identifying the driver miRNAs with somatic copy number alterations driving dysregulated ceRNA networks in cancers

description: Additional file 4. Table S3. Reported driver miRNAs that play important cancer-related functions in vivo or in vitro.
DOI: 10.6084/m9.figshare.26644024.v1
title: Additional file 4 of Identifying the driver miRNAs with somatic copy number alterations driving dysregulated ceRNA networks in cancers

description: Additional file 4. Table S3. Reported driver miRNAs that play important cancer-related functions in vivo or in vitro.
DOI: 10.6084/m9.figshare.26588349
title: Additional file 2 of Expression of S100A8 protein on B cells is associated with disease activity in patients with systemic lupus erythematosus

description: Additional file 2: Supplementary Table 2. Detailed information of the registered patients. Detailed information of the SLE patients enrolled in the proteomics (LC-MSMS) and transcriptomics (DNA microarray) analysis. The samples of six patients were used for both proteomics and transcriptomics (SLE P1, P3, P5, P10, P11 and P14). *SLEDAI-2K ≥ 6 was defined as active. **Clinically diagnosed withoutrenal biopsy. Glucocorticoid dose was calculated as prednisolone-equivalent. AZA:azathioprine, MZB: mizoribine, RTX: rituximab.
DOI: 10.6084/m9.figshare.26588349.v1
title: Additional file 2 of Expression of S100A8 protein on B cells is associated with disease activity in patients with systemic lupus erythematosus

description: Additional file 2: Supplementary Table 2. Detailed information of the registered patients. Detailed information of the SLE patients enrolled in the proteomics (LC-MSMS) and transcriptomics (DNA microarray) analysis. The samples of six patients were used for both proteomics and transcriptomics (SLE P1, P3, P5, P10, P11 and P14). *SLEDAI-2K ≥ 6 was defined as active. **Clinically diagnosed withoutrenal biopsy. Glucocorticoid dose was calculated as prednisolone-equivalent. AZA:azathioprine, MZB: mizoribine, RTX: rituximab.
DOI: 10.15468/dl.6rnhes
title: Occurrence Download

description: A dataset containing 33796 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Country mismatch, The taxon ID was not used in backbone matching, The scientific name differs on the record from that found in the checklist, The backbone match found using the taxon IDs differs from what would be found if using the scientific names , Individual count invalid, Individual count conflicts with occurrence status)",
 "OccurrenceStatus is Present",
 "TaxonKey is Centropyge Kaup, 1860"
 ]
}

 The dataset includes 33796 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065723-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13312692
title: Fürth Luisen-Apotheke (ca. 1924/1947)

description: Historical questionnaire/s 1924/1948 and index cards, partly selected enclosures regarding the history of a German pharmacy, catalogued via Kalliope portal (Historischer Fragebogen 1924/1948 und Karteikarten, ggf. gemeinfreie Anlagen zur Apothekengeschichte; als Katalog dient das Nachlassportal Kalliope): https://kalliope-verbund.info/DE-611-BF-70963 [Funktion: Im Findbuch anzeigen]Please note: The Kalliope catalogue entry might indicate related material in the archival folder which cannot be published due to copyright or other legal restrictions (NB: Das Katalogisat bei Kalliope kann auch auf Materialien - teils erheblichen Umfangs - verweisen, die aus archiv- oder urheberrechtlichen Gründen nicht veröffentlicht werden dürfen).
DOI: 10.6084/m9.figshare.26564220
title: Additional file 2 of FT-GPI, a highly sensitive and accurate predictor of GPI-anchored proteins, reveals the composition and evolution of the GPI proteome in Plasmodium species

description: Additional file 2: Table S2. FT-GPI parameter sets. A. FT-GPI combination of FT-GPI parameters values used form the analysis of Plasmodium proteomes. Seven parameters were set according to FT-GPI and TMPred options available in the FT-GPI software. B. FT-GPI software options. Parameters are available as options of the software. Colours establish the correspondance between A and B tables. Green corresponds to the options fixing the N-terminal TM parameters. Blue indicates C-terminal TM detection parameters corresponding options. Pink indicates the central TM score and brown shows TMpred TM specific parameters.