cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.y8sb5q
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mozambique",
 "TaxonKey is Ochna dolicharthros F.M.Crawford & I.Darbysh."
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013462-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.za3ay2
title: Occurrence Download

description: A dataset containing 5854 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is one of (Bangladesh, Malaysia, Indonesia, Philippines, Thailand, Brunei Darussalam, India, Viet Nam, Sri Lanka, Myanmar, Cambodia, Lao People’s Democratic Republic, Singapore, China)",
 "TaxonKey is Dipterocarpus C.F.Gaertn.",
 "Year 1761-2024"
 ]
}

 The dataset includes 5854 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013463-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vyaezm
title: Occurrence Download

description: A dataset containing 634 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Boophis tephraeomystax (Duméril, 1853)"
 ]
}

 The dataset includes 634 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013464-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6hxeya
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alosa volgensis (Berg, 1913)",
 "Country is Russian Federation"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013465-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yywqru
title: Occurrence Download

description: A dataset containing 2665 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acer platanoides L.)",
 "Country is Ukraine"
 ]
}

 The dataset includes 2665 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013466-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dsmawd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alosa volgensis (Berg, 1913)",
 "Country is Kazakhstan"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013468-241007104925546/datasets/export for details.
DOI: 10.5281/zenodo.13928128
title: Colonial trade linkages: Trade policy and imports in South and Southeast Asia colonial markets (1874-1913).
DOI: 10.5281/zenodo.13928129
title: Colonial trade linkages: Trade policy and imports in South and Southeast Asia colonial markets (1874-1913).
DOI: 10.6084/m9.figshare.27194547
title: Global Viridian tree

description: The global Viridian tree from the October 2024 preprint of "Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny". We provide the same tree in two formats: JSONL and .pb.
DOI: 10.15468/dl.3d5f4k
title: Occurrence Download

description: A dataset containing 39593 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Mellicta athalia (von Rottemburg, 1775)",
 "PhylumKey is Arthropoda",
 "Year is greater than or equal to 1992",
 "Year is less than or equal to 2012",
 "Geometry POLYGON((-26 34, 42 34, 42 70, -26 70, -26 34))"
 ]
}

 The dataset includes 39593 records from 365 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013467-241007104925546/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.27222996
title: <b>Optimal design of multi-biomaterials mixed extrusion nozzle for 3D bioprinting considering cell activity</b>

description: In this research, the flow and mixing process of SA solution in the mixing extrusion nozzle were simulated and analyzed by using finite element simulation software COMSOL and CFD method, as well, the effects of nozzle structure on the shear stress in the channel and mixing efficiency of the mixer were investigated.
DOI: 10.6084/m9.figshare.26861957
title: Epigenetic identification of LTBP4 as a putative tumor suppressor in breast cancer

description: <b>Aim:</b> To explore the LTBP4’s expression, prognostic significance and molecular mechanism of action in breast cancer (BC). <b>Methods:</b> On the basis of omics datasets and experiments, we conducted a synthetical analysis of LTBP4 in BC. <b>Results & conclusion:</b> LTBP4 was downregulated in BC with high promoter methylation and low genetic alteration. DNA methylation was negatively associated with LTBP4 mRNA expression. Higher LTBP4 associated with better survival. LTBP4 was enrichment in extracellular matrix receptor interactions, cell adhesion molecules, cell cycle and MAPK pathway. LTBP4 expression and methylation were positively and negatively associated with tumor infiltrating immune cells, respectively. In conclusion, LTBP4 is a putative tumor suppressor in BC, which expression is regulated by DNA methylation and relates with prognosis. We evaluated the mRNA and protein expression profiles of LTBP4 using multiple datasets and we found LTBP4 was downregulated in breast cancer (BC) tissues and cell lines. Genetic and epigenetic analysis revealed frequently promoter methylation of LTBP4 in BC tissues and cell lines. The high LTBP4 expression was significantly associated with better survival in BC and correlated with clinical pathological parameters. Based on bioinformatic tools, we found LTBP4 may be involved in cell cycle, MAPK pathway and the tumor immune microenvironment.
DOI: 10.6084/m9.figshare.26861957.v1
title: Epigenetic identification of LTBP4 as a putative tumor suppressor in breast cancer

description: <b>Aim:</b> To explore the LTBP4’s expression, prognostic significance and molecular mechanism of action in breast cancer (BC). <b>Methods:</b> On the basis of omics datasets and experiments, we conducted a synthetical analysis of LTBP4 in BC. <b>Results & conclusion:</b> LTBP4 was downregulated in BC with high promoter methylation and low genetic alteration. DNA methylation was negatively associated with LTBP4 mRNA expression. Higher LTBP4 associated with better survival. LTBP4 was enrichment in extracellular matrix receptor interactions, cell adhesion molecules, cell cycle and MAPK pathway. LTBP4 expression and methylation were positively and negatively associated with tumor infiltrating immune cells, respectively. In conclusion, LTBP4 is a putative tumor suppressor in BC, which expression is regulated by DNA methylation and relates with prognosis. We evaluated the mRNA and protein expression profiles of LTBP4 using multiple datasets and we found LTBP4 was downregulated in breast cancer (BC) tissues and cell lines. Genetic and epigenetic analysis revealed frequently promoter methylation of LTBP4 in BC tissues and cell lines. The high LTBP4 expression was significantly associated with better survival in BC and correlated with clinical pathological parameters. Based on bioinformatic tools, we found LTBP4 may be involved in cell cycle, MAPK pathway and the tumor immune microenvironment.
DOI: 10.15468/dl.fvxvtm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anabarilius macrolepis Yih & Wu, 1964",
 "Country is China"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013469-241007104925546/datasets/export for details.
DOI: 10.6084/m9.figshare.26928005
title: Integrated epigenomic exposure signature discovery

description: <b>Aim:</b> The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. <b>Materials & methods:</b> Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES). <b>Results:</b> Signatures were developed for seven exposures including <i>Staphylococcus aureus</i>, human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and <i>Bacillus anthracis</i> vaccinations. ESs differed in the assays and features selected and predictive value. <b>Conclusion:</b> Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment. This article introduces ESDA, a new analytic tool for integrating multiple data types to identify the most distinguishing features following an exposure. Using the ESDA, we were able to identify signatures of infectious diseases. The results of the study indicate that integration of multiple types of large datasets can be used to identify distinguishing features for infectious diseases. Understanding the changes from different exposures will enable development of diagnostic tests for infectious diseases that target responses from the patient. Using the ESDA, we will be able to build a database of human response signatures to different infections and simplify diagnostic testing in the future. The exposure signature discovery algorithm simplifies diagnostic target discovery from integrating epigenomic and transcriptomic data sets enabling rapid diagnostics based on host response to exposure. Integration and parsing of multi-omic data generates precise exposure signatures. The number of features in the ESDA model is not strongly correlated with signature performance, but depends on the underlying biology. The low sample size for some exposure types contributes to instability in some model predictions (BA), and therefore, high variability in accuracy metrics during LOOCV. Ensemble results are robust for most exposure types. The most prominent combination of epigenetic methods deployed in the ESDA models were EPIC array for DNA methylation, RNAseq, H3K4me1 and H3K4me3 histone modification assays. Explosives (PETN) imprint the epigenome and result in a signature that can be detected 6–8 weeks after exposure. ESDA-developed SARS-CoV-2 signatures track with acute SARS-CoV-2 with 89% performance. Individuals with convalescent SARS-CoV-2 have a distinct signature that indicates immune epigenetic remodeling. ESDA-derived <i>S. aureus</i> signature can discriminate robustly between MRSA and MSSA in <i>S. aureus</i> infections. An exposure signature database can enable a universal diagnostic test for exposure health that can distinguish infectious diseases and chemical exposures.
DOI: 10.6084/m9.figshare.26928005.v1
title: Integrated epigenomic exposure signature discovery

description: <b>Aim:</b> The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. <b>Materials & methods:</b> Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES). <b>Results:</b> Signatures were developed for seven exposures including <i>Staphylococcus aureus</i>, human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and <i>Bacillus anthracis</i> vaccinations. ESs differed in the assays and features selected and predictive value. <b>Conclusion:</b> Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment. This article introduces ESDA, a new analytic tool for integrating multiple data types to identify the most distinguishing features following an exposure. Using the ESDA, we were able to identify signatures of infectious diseases. The results of the study indicate that integration of multiple types of large datasets can be used to identify distinguishing features for infectious diseases. Understanding the changes from different exposures will enable development of diagnostic tests for infectious diseases that target responses from the patient. Using the ESDA, we will be able to build a database of human response signatures to different infections and simplify diagnostic testing in the future. The exposure signature discovery algorithm simplifies diagnostic target discovery from integrating epigenomic and transcriptomic data sets enabling rapid diagnostics based on host response to exposure. Integration and parsing of multi-omic data generates precise exposure signatures. The number of features in the ESDA model is not strongly correlated with signature performance, but depends on the underlying biology. The low sample size for some exposure types contributes to instability in some model predictions (BA), and therefore, high variability in accuracy metrics during LOOCV. Ensemble results are robust for most exposure types. The most prominent combination of epigenetic methods deployed in the ESDA models were EPIC array for DNA methylation, RNAseq, H3K4me1 and H3K4me3 histone modification assays. Explosives (PETN) imprint the epigenome and result in a signature that can be detected 6–8 weeks after exposure. ESDA-developed SARS-CoV-2 signatures track with acute SARS-CoV-2 with 89% performance. Individuals with convalescent SARS-CoV-2 have a distinct signature that indicates immune epigenetic remodeling. ESDA-derived <i>S. aureus</i> signature can discriminate robustly between MRSA and MSSA in <i>S. aureus</i> infections. An exposure signature database can enable a universal diagnostic test for exposure health that can distinguish infectious diseases and chemical exposures.
DOI: 10.15468/dl.w68fvn
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mozambique",
 "TaxonKey is Afrocanthium racemulosum (S.Moore) Lantz"
 ]
}

 The dataset includes 12 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013470-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5518/465
title: Dataset associated with Tandem fluorescence and Raman (fluoRaman) characterisation of a novel photosensitiser in colorectal cancer cell line SW480

description: Raw data associated with the Raman and fluorescence confocal results shown in the publication
DOI: 10.15468/dl.s7xerx
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anatolichthys splendens Kosswig & Sözer, 1945",
 "Country is Türkiye"
 ]
}

 The dataset includes 4 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013471-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g2ex5v
title: Occurrence Download

description: A dataset containing 127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Indonesia",
 "HasCoordinate is true",
 "License is CC-BY-NC 4.0",
 "PublishingOrg is f891104a-681f-48df-b6a1-68fd1938b44f",
 "TaxonKey is Vaccinium L."
 ]
}

 The dataset includes 127 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013473-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k6qty6
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Atherinella callida Chernoff, 1986",
 "Country is Mexico"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013474-241007104925546/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.27194652
title: Non-tree Viridian consensus sequences, batch 2

description: Second batch of Viridian consensus sequences from samples that are not in the global tree, from the October 2024 version of the preprint "Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny". These are included for completeness, since they were excluded from the tree for various (mostly QC-fail) reasons.The first batch of sequences, from the May 2024 version of the preprint, is here: https://figshare.com/articles/dataset/Non-tree_Viridian_consensus_sequences/25713342
DOI: 10.6084/m9.figshare.27194652.v1
title: Non-tree Viridian consensus sequences, batch 2

description: Second batch of Viridian consensus sequences from samples that are not in the global tree, from the October 2024 version of the preprint "Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny". These are included for completeness, since they were excluded from the tree for various (mostly QC-fail) reasons.The first batch of sequences, from the May 2024 version of the preprint, is here: https://figshare.com/articles/dataset/Non-tree_Viridian_consensus_sequences/25713342
DOI: 10.5281/zenodo.12593795
title: Topology Bench: Systematic Graph Based Benchmarking for Optical Networks

description: TopologyBench is a systematic graph theoretical approach to benchmarking optical network topologies. Network datasets are combined with their corresponding graph theoretical analysis to provide a systematic methodology for selecting diverse sets of optical networks for benchmarking. This topology benchmark is comprised of a network dataset and a systematic graph theoretic analysis. The dataset provides (a) 105 real optical networks and (b) synthetic topologies, generated by the SNR-BA model, divided into (i) Syn-small of 900 synthetic networks and (ii) Syn-large of 270,000 synthetic networks. The systematic graph theoretical analysis identifies and analyses structural, spatial and spectral properties of both the real world and synthetic networks. The graph theoretical correlation analysis reveal network design strategies leading to sparse yet efficient networks. An outlier analysis identifies networks that deviate from standard network designs. The analysis also identifies the limitations of real data in terms of network diversity and provides a justification for using synthetic data to complement the real dataset. We conclude the paper by providing a systematic methodology to cluster networks based on unsupervised machine learning and to select a diverse set of topologies for benchmarking. TopologyBench is a novel, high-quality and unified benchmark designed to facilitate research collaborations in long-haul fibre infrastructure by providing a systematic graph theoretical approach to benchmarking optical networks.
DOI: 10.5281/zenodo.13921213
title: Topology Bench: Systematic Graph Based Benchmarking for Optical Networks

description: TopologyBench is a systematic graph theoretical approach to benchmarking optical network topologies. Network datasets are combined with their corresponding graph theoretical analysis to provide a systematic methodology for selecting diverse sets of optical networks for benchmarking. This topology benchmark is comprised of a network dataset and a systematic graph theoretic analysis. The dataset provides (a) 105 real optical networks and (b) synthetic topologies, generated by the SNR-BA model, divided into (i) Syn-small of 900 synthetic networks and (ii) Syn-large of 270,000 synthetic networks. The systematic graph theoretical analysis identifies and analyses structural, spatial and spectral properties of both the real world and synthetic networks. The graph theoretical correlation analysis reveal network design strategies leading to sparse yet efficient networks. An outlier analysis identifies networks that deviate from standard network designs. The analysis also identifies the limitations of real data in terms of network diversity and provides a justification for using synthetic data to complement the real dataset. We conclude the paper by providing a systematic methodology to cluster networks based on unsupervised machine learning and to select a diverse set of topologies for benchmarking. TopologyBench is a novel, high-quality and unified benchmark designed to facilitate research collaborations in long-haul fibre infrastructure by providing a systematic graph theoretical approach to benchmarking optical networks.
DOI: 10.34740/kaggle/dsv/9621234
title: World Weather Repository ( Daily Updating )
DOI: 10.15468/dl.6p5fyb
title: Occurrence Download

description: A dataset containing 72078 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-103.08494 -58.64223,-33.4179 -58.64223,-33.4179 5.16495,-103.08494 5.16495,-103.08494 -58.64223))",
 "Geometry POLYGON((-172.10086 12.97808,-59.7872 12.97808,-59.46166 68.32103,-59.7872 89.48158,-172.10086 89.48158,-172.10086 12.97808))",
 "Geometry POLYGON((-55.22955 61.8101,-12.90847 61.8101,-12.90847 81.34291,-55.22955 81.34291,-55.22955 61.8101))",
 "Geometry POLYGON((10.06939 75.29149,27.03288 75.29149,27.03288 86.38301,10.06939 86.38301,10.06939 75.29149))",
 "Geometry POLYGON((110.06574 -51.75897,178.56556 -51.75897,178.56556 -10.96125,110.06574 -10.96125,110.06574 -51.75897))",
 "Geometry POLYGON((-6.00672 4.32093,169.53105 4.32093,169.53105 73.02395,-6.00672 73.02395,-12.02225 42.95795,-6.00672 4.32093))"
 ]
 },
 "TaxonKey is Equisetum hyemale L."
 ]
}

 The dataset includes 72078 records from 892 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013472-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.em7ymr
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Barbodes amarus Herre, 1924",
 "Country is Philippines"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013475-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.