cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive134249.20190402.4
title: Bacillus acidiceler

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134250.20190402.4
title: Alkalibacterium indicireducens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134251.20190402.4
title: Virgibacillus chiguensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134252.20190402.4
title: Salimicrobium luteum

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134253.20190402.4
title: Anderseniella baltica

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134254.20190402.4
title: Marinobacter segnicrescens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135063.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135064.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135065.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135066.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135067.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135068.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135069.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135070.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135071.20190402.4
title: Corynebacterium diphtheriae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135867.20190402.4
title: Klebsiella pneumoniae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135868.20190402.4
title: Paenibacillus polymyxa

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135869.20190402.4
title: Neisseria gonorrhoeae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135870.20190402.4
title: Neisseria meningitidis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135871.20190402.4
title: Haemophilus influenzae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135872.20190402.4
title: Klebsiella pneumoniae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135873.20190402.4
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135874.20190402.4
title: Mycobacterium goodii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive135875.20190402.4
title: Pasteurella multocida

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136652.20190402.4
title: Salmonella enterica subsp. arizonae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136653.20190402.4
title: Salmonella enterica subsp. arizonae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136654.20190402.4
title: Staphylococcus aureus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136655.20190402.4
title: Citrobacter youngae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136656.20190402.4
title: Pseudomonas aeruginosa

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136657.20190402.4
title: Salmonella enterica subsp. arizonae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136658.20190402.4
title: Salmonella enterica subsp. arizonae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136659.20190402.4
title: Salmonella enterica subsp. arizonae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136660.20190402.4
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive136661.20190402.4
title: Salmonella enterica subsp. arizonae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive131777.20190402.4
title: Methylobacterium sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.6084/m9.figshare.20069921
title: GRDC - CCDM/CIC genomic prediction report

description: <strong> S1Data-simulated.tar.gz </strong>- These are simulated data evaluating prediction accuracy for different traits, number of markers, numbers of samples on different testing scenarios. <br> <br> Other files are example results of the SelectML methods. These are the combined results of the optimise and predict scripts. The compressed folders are named by the simulated dataset that they correspond to and the model. <br> The trait is first (e.g. A1 means an additive trait with 1 causal marker), N1000 means 1000 samples (in the training population), M1000 means 1000 markers sampled, "_CAUSAL" means that the causal loci were included in the sampled markers (note that this means for M1000 all markers sampled did have a genuine effect), and the final section before ".tar.gz" indicates the model used (e.g. sgd, xgb, BGLR). <br> Inside each of these compressed folders are the following files. From the `selectml optimise` command: <br> <strong>regression_*_best.json </strong>- the best performing combination of hyper parameters for these data and model type. <strong>regression_*_results.tsv </strong>- The optuna running logs showing sampled parameters and average mean squared error (of cross validated samples) of models from that parameter set. <strong>regression_*_full_results.tsv</strong> - Like _results.tsv but includes other statistics relevant to the task, such as pearsons correlation. <br> And from `selectml predict`: <strong>regression_*_model.pkl </strong>- a stored version of the trained model given the best parameters from optimise, trained from the complete train dataset. <strong>regression_*_predictions.tsv </strong>- predicted results for all training datasets. <strong>regression_*_stats.tsv </strong>- summary statistics (e.g. MSE, pearsons correlation) for the model in different test populations.
DOI: 10.6084/m9.figshare.20070745
title: Additional file 1 of Older adults’ facial characteristics compared to young adults’ in correlation with edentulism: a cross sectional study

description: Additional file 1.
DOI: 10.6084/m9.figshare.20070745.v1
title: Additional file 1 of Older adults’ facial characteristics compared to young adults’ in correlation with edentulism: a cross sectional study

description: Additional file 1.
DOI: 10.6084/m9.figshare.20070757
title: Additional file 1 of Knowledge and practice of nursing students regarding bioterrorism and emergency preparedness: comparison of the effects of simulations and workshop

description: Additional file 1.
DOI: 10.6084/m9.figshare.20070757.v1
title: Additional file 1 of Knowledge and practice of nursing students regarding bioterrorism and emergency preparedness: comparison of the effects of simulations and workshop

description: Additional file 1.
DOI: 10.6084/m9.figshare.20070780.v1
title: Additional file 2 of Potential risk factors for the presence of anti-Toxoplasma gondii antibodies in finishing pigs on conventional farms in the Netherlands

description: Additional file 2. Toxoplasma data of questionnaire.
DOI: 10.6084/m9.figshare.20070780
title: Additional file 2 of Potential risk factors for the presence of anti-Toxoplasma gondii antibodies in finishing pigs on conventional farms in the Netherlands

description: Additional file 2. Toxoplasma data of questionnaire.
DOI: 10.6084/m9.figshare.20070805.v1
title: Additional file 2 of Genetic architecture of end-use quality traits in soft white winter wheat

description: Additional file 2: Table S1. Summary of GWAS for 14 end-use quality in softwhite winter wheat using mixed linear model (MLM). Table S2. Summary of GWAS for 14 end-use quality in soft whitewinter wheat using Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model. Table S3. Annotated genes within the genomic regions of large-effect markers identified in this study for end-use quality traits in soft white winter wheat. Table S4. Previously identified QTL within the genomic regions of Marker-Trait-Associations identified in this study.
DOI: 10.6084/m9.figshare.20070805
title: Additional file 2 of Genetic architecture of end-use quality traits in soft white winter wheat

description: Additional file 2: Table S1. Summary of GWAS for 14 end-use quality in softwhite winter wheat using mixed linear model (MLM). Table S2. Summary of GWAS for 14 end-use quality in soft whitewinter wheat using Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model. Table S3. Annotated genes within the genomic regions of large-effect markers identified in this study for end-use quality traits in soft white winter wheat. Table S4. Previously identified QTL within the genomic regions of Marker-Trait-Associations identified in this study.
DOI: 10.6084/m9.figshare.20070886.v1
title: Additional file 1 of Genome-wide investigation of histone acetyltransferase gene family and its responses to biotic and abiotic stress in foxtail millet (Setaria italica [L.] P. Beauv)

description: Additional file 1: Table S1. Basic physicochemical properties, Secondary structure prediction and subcellular localization of HATs in Setaria italica.
DOI: 10.6084/m9.figshare.20070886
title: Additional file 1 of Genome-wide investigation of histone acetyltransferase gene family and its responses to biotic and abiotic stress in foxtail millet (Setaria italica [L.] P. Beauv)

description: Additional file 1: Table S1. Basic physicochemical properties, Secondary structure prediction and subcellular localization of HATs in Setaria italica.
DOI: 10.6084/m9.figshare.20070952
title: Additional file 6 of Play, Learn, and Teach Outdoors—Network (PLaTO-Net): terminology, taxonomy, and ontology

description: Additional file 6.
DOI: 10.6084/m9.figshare.20070946
title: Additional file 4 of Play, Learn, and Teach Outdoors—Network (PLaTO-Net): terminology, taxonomy, and ontology

description: Additional file 4.
DOI: 10.6084/m9.figshare.20070946.v1
title: Additional file 4 of Play, Learn, and Teach Outdoors—Network (PLaTO-Net): terminology, taxonomy, and ontology

description: Additional file 4.
DOI: 10.6084/m9.figshare.20070952.v1
title: Additional file 6 of Play, Learn, and Teach Outdoors—Network (PLaTO-Net): terminology, taxonomy, and ontology

description: Additional file 6.
DOI: 10.6084/m9.figshare.20070955.v1
title: Additional file 7 of Play, Learn, and Teach Outdoors—Network (PLaTO-Net): terminology, taxonomy, and ontology

description: Additional file 7.
DOI: 10.6084/m9.figshare.20070955
title: Additional file 7 of Play, Learn, and Teach Outdoors—Network (PLaTO-Net): terminology, taxonomy, and ontology

description: Additional file 7.
DOI: 10.6084/m9.figshare.20070671
title: Supplementary Material for: Should More Patients with Kidney Failure Bring Treatment Home? What We Have Learned from COVID-19

description: <b><i>Background:</i></b> The COVID-19 pandemic is challenging healthcare systems worldwide and has placed hospitals and healthcare providers (HCPs) at the center of a global crisis. Disruptions to hospital priorities, and limitations placed on the mobility of societies, have contributed to changes in the way HCPs and patients view and access dialysis for kidney failure, including which dialysis modality is preferred. <b><i>Summary:</i></b> This article explores the dialysis experience within the COVID-19 pandemic environment in the Asia Pacific region and presents evidence that peritoneal dialysis (PD) provides benefits to patients, HCPs, and health systems. As the number of people infected with COVID-19 has increased, the advantages of PD as a dialysis modality for limiting the spread of COVID-19 infection has been recognized. <b><i>Key Message:</i></b> The utility of PD has been demonstrated during the COVID-19 pandemic; thus, ensuring that the usage of PD is maintained and increased in a post-pandemic future is key. Such a scenario could enhance our ability to care for patients without interruption in circumstances of unforeseen obstacles and supports the ability of healthcare systems and patients to overcome barriers to dialysis access.
DOI: 10.5281/zenodo.6637700
title: Data of Water Vapor Flux-Profile Relationship in the Stable Boundary Layer over the Sea Surface

description: data and code for paper 'Water Vapor Flux-Profile Relationship in the Stable Boundary Layer over the Sea Surface'
DOI: 10.6084/m9.figshare.20071145
title: Supplementary Material for: SLC26A2/DTDST Spectrum: A Cohort of 12 Patients Associated with a Comprehensive Review of the Genotype-Phenotype Correlation

description: <b><i>Introduction:</i></b> Pathogenic variants in the <i>SLC26A2/DTDST</i> gene cause the following spectrum of phenotypes: achondrogenesis 1B (ACG1B), atelosteogenesis 2 (AO2), diastrophic dysplasia (DTD), and recessive-multiple epiphyseal dysplasia (rMED), the first 2 being lethal. Here, we report a cohort and a comprehensive literature review on a genotype-phenotype correlation of <i>SLC26A2/DTDST</i>-related disorders. <b><i>Methods:</i></b> The local patients were genotyped by Sanger sequencing or next-generation sequencing (NGS). We reviewed data from the literature regarding phenotype, zygosity, and genotype in parallel. <b><i>Results:</i></b> The local cohort enrolled 12 patients, including one with a Desbuquois-like phenotype. All but one showed biallelic mutations, however, only one allele mutated in a fetus presenting ACG1B was identified. The literature review identified 42 articles and the analyses of genotype and zygosity included the 12 local patients. <b><i>Discussion:</i></b> The R279W variant was the most prevalent among the local patients. It was in homozygosity (hmz) in 2 patients with rMED and in compound heterozygosity (chtz) in 9 patients. The genotype and zygosity review of all patients led to the following conclusions: DTD is the most common phenotype in Finland due to a Finnish mutation (c.727–1G&gt;C). Outside of Finland, rMED is the most prevalent phenotype, usually associated with R279W in hmz. In contrast, DTD’s genotype is usually in chtz. Despite a large number of variants (38), just 8 are recurrent (R279W, C653S, c.−26+2T&gt;C, R178*, K575Sfs*10, V340del, G663R, T512K). The last 3 in hmz lead to lethal phenotypes. The Finnish mutation is found only in chtz outside of Finland, being associated with all 4 classical phenotypes. The p.R178* and p.K575Sfs*10 variants should be viewed as lethal mutations since both were mainly described with lethal phenotypes and were never reported in hmz. The existence of 9 patients with only one mutated allele suggests that other mutations in the other allele of these patients still need to be unveiled.
DOI: 10.6084/m9.figshare.20071145.v1
title: Supplementary Material for: SLC26A2/DTDST Spectrum: A Cohort of 12 Patients Associated with a Comprehensive Review of the Genotype-Phenotype Correlation

description: <b><i>Introduction:</i></b> Pathogenic variants in the <i>SLC26A2/DTDST</i> gene cause the following spectrum of phenotypes: achondrogenesis 1B (ACG1B), atelosteogenesis 2 (AO2), diastrophic dysplasia (DTD), and recessive-multiple epiphyseal dysplasia (rMED), the first 2 being lethal. Here, we report a cohort and a comprehensive literature review on a genotype-phenotype correlation of <i>SLC26A2/DTDST</i>-related disorders. <b><i>Methods:</i></b> The local patients were genotyped by Sanger sequencing or next-generation sequencing (NGS). We reviewed data from the literature regarding phenotype, zygosity, and genotype in parallel. <b><i>Results:</i></b> The local cohort enrolled 12 patients, including one with a Desbuquois-like phenotype. All but one showed biallelic mutations, however, only one allele mutated in a fetus presenting ACG1B was identified. The literature review identified 42 articles and the analyses of genotype and zygosity included the 12 local patients. <b><i>Discussion:</i></b> The R279W variant was the most prevalent among the local patients. It was in homozygosity (hmz) in 2 patients with rMED and in compound heterozygosity (chtz) in 9 patients. The genotype and zygosity review of all patients led to the following conclusions: DTD is the most common phenotype in Finland due to a Finnish mutation (c.727–1G&gt;C). Outside of Finland, rMED is the most prevalent phenotype, usually associated with R279W in hmz. In contrast, DTD’s genotype is usually in chtz. Despite a large number of variants (38), just 8 are recurrent (R279W, C653S, c.−26+2T&gt;C, R178*, K575Sfs*10, V340del, G663R, T512K). The last 3 in hmz lead to lethal phenotypes. The Finnish mutation is found only in chtz outside of Finland, being associated with all 4 classical phenotypes. The p.R178* and p.K575Sfs*10 variants should be viewed as lethal mutations since both were mainly described with lethal phenotypes and were never reported in hmz. The existence of 9 patients with only one mutated allele suggests that other mutations in the other allele of these patients still need to be unveiled.
DOI: 10.15468/dl.v344mx
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-102.19768 19.6341,-102.0971 19.64648,-102.04287 19.67328,-102.02584 19.72108,-102.03104 19.73221,-102.02698 19.74418,-102.0316 19.76949,-102.03771 19.79199,-102.06175 19.80739,-102.0917 19.80586,-102.10203 19.78891,-102.10969 19.80579,-102.11895 19.83256,-102.1388 19.85514,-102.15346 19.82538,-102.16389 19.81968,-102.17755 19.83093,-102.19848 19.82518,-102.2134 19.81945,-102.21745 19.7912,-102.21714 19.76726,-102.21249 19.75039,-102.24652 19.69276,-102.19768 19.6341))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 1980-2024"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064558-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.43wg6k
title: Occurrence Download

description: A dataset containing 595 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Orobanche salviae F.W.Schultz"
 ]
}

 The dataset includes 595 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064559-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x8ejrk
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ophiorrhiza ensiformis H.S.Lo"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064560-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yyn2nv
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ochna polyarthra Verdc."
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064562-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j53w5g
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hydrophis platurus (Linnaeus, 1766)",
 "Geometry POLYGON((-124.756451627043 24.5232175268442, -124.756451627043 49.3844869955705, -66.9490903544593 49.3844869955705, -66.9490903544593 24.5232175268442, -124.756451627043 24.5232175268442))"
 ]
}

 The dataset includes 53 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064561-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.