cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12544049.v1
title: Additional file 1 of Genome-wide identification and characterization of SnRK family genes in Brassica napus

description: Additional file 1: Table S1. The information of A. thaliana SnRKs in queries. Table S2. Characteristics of SnRK family in B.napus. Table S3. List of the 114 BnSnRK genes identified in this study. Table S4. Conserved amino acid motifs and annotation of BnSnRKs. Table S5. Syntenic blocks and Ka/Ks values of BnSnRK genes. Table S6. One-to-one orthologous relationships between B.napus and A.thaliana. Table S7. The expression profiles (log2-based values) of the BnSnRKs under different tissues. Table S8. The expression profiles (ratio to control values) of the BnSnRKs under different abiotic stresses. Table S9. List of the BnSnRK SNPs identified in this study.
DOI: 10.6084/m9.figshare.12543989
title: Additional file 3 of Overexpression of HOXA10 is associated with unfavorable prognosis of acute myeloid leukemia

description: Additional file 3: Table S3. The detail list of exonic DMRs.
DOI: 10.6084/m9.figshare.12543989.v1
title: Additional file 3 of Overexpression of HOXA10 is associated with unfavorable prognosis of acute myeloid leukemia

description: Additional file 3: Table S3. The detail list of exonic DMRs.
DOI: 10.6084/m9.figshare.12543977
title: Additional file 1 of Overexpression of HOXA10 is associated with unfavorable prognosis of acute myeloid leukemia

description: Additional file 1: Table S1. GSEA results associated with HOXA10 expression derived from TCGA database.
DOI: 10.6084/m9.figshare.12543983
title: Additional file 2 of Overexpression of HOXA10 is associated with unfavorable prognosis of acute myeloid leukemia

description: Additional file 2: Table S2. ORA results of HOXA10 associated DEGs.
DOI: 10.6084/m9.figshare.12543983.v1
title: Additional file 2 of Overexpression of HOXA10 is associated with unfavorable prognosis of acute myeloid leukemia

description: Additional file 2: Table S2. ORA results of HOXA10 associated DEGs.
DOI: 10.6084/m9.figshare.12543971
title: Additional file 7 of Comprehensive evaluation of targeted multiplex bisulphite PCR sequencing for validation of DNA methylation biomarker panels

description: Additional file 7: Table S1.
DOI: 10.6084/m9.figshare.12543977.v1
title: Additional file 1 of Overexpression of HOXA10 is associated with unfavorable prognosis of acute myeloid leukemia

description: Additional file 1: Table S1. GSEA results associated with HOXA10 expression derived from TCGA database.
DOI: 10.6084/m9.figshare.12543971.v1
title: Additional file 7 of Comprehensive evaluation of targeted multiplex bisulphite PCR sequencing for validation of DNA methylation biomarker panels

description: Additional file 7: Table S1.
DOI: 10.6084/m9.figshare.12543836
title: Time series of COVID-19 severe cases and deaths, corrected using nowcasting, by Regional Health Department of São Paulo State, Brazil, as of 2020-06-11

description: Time series of severe (hospitalized) SARS and COVID-19 cases and deaths, corrected using nowcasting, by Regional Health Department (DRS) of São Paulo State, Brazil.<br>Primary data was obtained from the national database SIVEP-Gripe, which is a compulsory notification of hospitalized SARS cases and includes identification of test results for COVID-19. The extraction was made on 2020-06-11.<br>Nowcasting was performed using the R package NobBS. Results are shown both by notification and symptom/death dates.<br>The files are organized by DRS, with which set of tables in a separate subfolder.<br>
DOI: 10.6084/m9.figshare.12543857
title: Lipidomic_Metabolomic MVDz Source Data

description: Source data for publication on lipidomic patterns associated with microvascular dysfunction.
DOI: 10.6084/m9.figshare.12543854
title: Data from 'Transnational Plastics: An Australian Case For Global Action'. doi: 10.3389/fenvs.2020.00115

description: This fileset underpins the data analysis described in Galaiduk, R., Lebreton, L., Techera, E. and Reisser, J., 2020. Transnational Plastics: An Australian Case for Global Action. <i>Frontiers in Environmental Science</i>, <i>8</i>, p.115. doi: 10.3389/fenvs.2020.00115<br>For comments/enquiries, please contact r.galaiduk@aims.gov.au
DOI: 10.6084/m9.figshare.12543836.v1
title: Time series of COVID-19 severe cases and deaths, corrected using nowcasting, by Regional Health Department of São Paulo State, Brazil, as of 2020-06-11

description: Time series of severe (hospitalized) SARS and COVID-19 cases and deaths, corrected using nowcasting, by Regional Health Department (DRS) of São Paulo State, Brazil.<br>Primary data was obtained from the national database SIVEP-Gripe, which is a compulsory notification of hospitalized SARS cases and includes identification of test results for COVID-19. The extraction was made on 2020-06-11.<br>Nowcasting was performed using the R package NobBS. Results are shown both by notification and symptom/death dates.<br>The files are organized by DRS, with which set of tables in a separate subfolder.<br>
DOI: 10.6084/m9.figshare.12543857.v1
title: Lipidomic_Metabolomic MVDz Source Data

description: Source data for publication on lipidomic patterns associated with microvascular dysfunction.
DOI: 10.6084/m9.figshare.12543680
title: JVASP-34289 to JVASP-35225

description: JARVIS-DFT input/output files
DOI: 10.6084/m9.figshare.12543689
title: JVASP-35945 to JVASP-36523

description: JARVIS-DFT input/output files
DOI: 10.6084/m9.figshare.12543677
title: Prunus_avium_gene_annotation_Tieton_chromosome.gff3

description: Gene annotation file for the Chromosome of Tieton genome
DOI: 10.6084/m9.figshare.12543854.v1
title: Data from 'Transnational Plastics: An Australian Case For Global Action'

description: This fileset underpins the data analysis described in Galaiduk et al., 2020. Transnational Plastics: An Australian Case For Global Action.<br>For comments/enquiries, please contact r.galaiduk@aims.gov.au
DOI: 10.6084/m9.figshare.12543554
title: Helium Bubbles in X-750

description: Datasets used for the testing and training of a neural network used for the detection of helium bubbles in irradiated inconel X750
DOI: 10.6084/m9.figshare.12543677.v2
title: Prunus_avium_gene_annotation_Tieton_chromosome.gff3

description: Gene annotation file for the Chromosome of Tieton genome
DOI: 10.6084/m9.figshare.12543854.v2
title: Data from 'Transnational Plastics: An Australian Case For Global Action'. doi: 10.3389/fenvs.2020.00115

description: This fileset underpins the data analysis described in Galaiduk, R., Lebreton, L., Techera, E. and Reisser, J., 2020. Transnational Plastics: An Australian Case for Global Action. <i>Frontiers in Environmental Science</i>, <i>8</i>, p.115. doi: 10.3389/fenvs.2020.00115<br>For comments/enquiries, please contact r.galaiduk@aims.gov.au
DOI: 10.6084/m9.figshare.12543677.v1
title: Prunus_avium_gene_annotation_Tieton_chromosome.gff3

description: Gene annotation file for the Chromosome of Tieton genome
DOI: 10.6084/m9.figshare.12543587.v1
title: UI logs

description: This is the collection of UI logs used in the evaluation in the research paper: "Candidate routines identification from unsegmented UI logs". The real-life logs are in CSV format and recorded via Action Logger. The synthetic logs are in XES format and generated from colored Petri net models. The models are attached.
DOI: 10.6084/m9.figshare.12543488
title: Supplemental-Material-Dadabacteria-Global-Oceans

description: Supplemental Figures, Tables, and Data accompanying the bioRxiv initial journal submission for "Marine Dadabacteria exhibit genome streamlining and phototrophy-driven niche partitioning"
DOI: 10.6084/m9.figshare.12543488.v1
title: Supplemental-Material-Dadabacteria-Global-Oceans

description: Supplemental Figures, Tables, and Data accompanying the bioRxiv initial journal submission for "Marine Dadabacteria exhibit genome streamlining and phototrophy-driven niche partitioning"
DOI: 10.6084/m9.figshare.12543473.v1
title: Figure 1a In Silico Mixture Data

description: Source data underlying Figure 1a of manuscript. In Silico mixtures which are deconvolved.<br>Row names:CellType - Cell type spiked in at a particular fraction<br>SpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types<br><br>Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns<br>
DOI: 10.6084/m9.figshare.12543473.v2
title: Source Data Underlying Manuscript Figures

description: <b>Fig1aSupplementaryDataMixture.xlsx</b><br>Source data underlying Figure 1a of manuscript. In Silico mixtures which are deconvolved.<br>Row names:CellType - Cell type spiked in at a particular fraction<br>SpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types<br><br>Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns<br><b>Fig1aSupplementaryDataDeconvolution.xlsx<br></b><br>Source data underlying Figure 1a of manuscript. Results of deconvolution of in silico mixtures.<br>Column names:Method - Method used for deconvolution<br>CellType - Cell type spiked in at a particular fractionSpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method.<br>
DOI: 10.6084/m9.figshare.12543398
title: Figure 1a Deconvolution Data

description: Source data underlying Figure 1a of manuscript. Results of deconvolution of in silico mixtures.<br>Column names:Method - Method used for deconvolution<br>CellType - Cell type spiked in at a particular fractionSpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method.
DOI: 10.5281/zenodo.3997778
title: Input Data as used in Kreuzer et al., Geoscientific Model Development publication (gmd-2020-230)

description: Input data for the PISM-MOM coupling framework as used in Kreuzer et al., Geoscientific Model Development publication (gmd-2020-230)
description: {"references": ["Le Brocq, A. M., Payne, A. J., and Vieli, A.: An improved Antarctic dataset for high resolution numerical ice sheet models (ALBMAP v1), Earth Syst. Sci. Data, 2, 247\u2013260, https://doi.org/10.5194/essd-2-247-2010, 2010.", "Fretwell et al.: Bedmap2: improved ice bed, surface and thickness datasets for Antarctica, The Cryosphere, 7, 375\u2013393, https://doi.org/10.5194/tc-7-375-2013, 2013.", "Schmidtko, S., Heywood, K. J., Thompson, A. F. and Aoki, S.: Multidecadal warming of Antarctic waters, Science, 346 (6214), 1227-1231, https://doi.org/10.1126/science.1256117, 2014.", "van Wessem et al.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 \u2013 Part 2: Antarctica (1979\u20132016), The Cryosphere, 12, 1479\u20131498, https://doi.org/10.5194/tc-12-1479-2018, 2018."]}
DOI: 10.6084/m9.figshare.12543473.v3
title: Source Data Underlying Manuscript Figures

description: <b>Fig1aSupplementaryDataMixture.xlsx</b><br>Source data underlying Figure 1a of manuscript. In Silico mixtures which are deconvolved.<br>Row names:CellType - Cell type spiked in at a particular fraction<br>SpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types<br><br>Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns<br><b>Fig1aSupplementaryDataDeconvolution.xlsx<br></b><br>Source data underlying Figure 1a of manuscript. Results of deconvolution of in silico mixtures.<br>Column names:Method - Method used for deconvolution<br>CellType - Cell type spiked in at a particular fractionSpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method.<br><b>Fig1bSupplementaryDataDeconvolution.xlsx</b><br><b><br></b>Source data underlying Figure 1b of manuscript. Results of deconvolution of in vitro mixtures.<br>Column names:Method - Method used for deconvolution<br>Mixture - In Vitro mixture name -- this corresponds to the cell type fractions in the mixtureTumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>NoiseCoefficient - Amount of noise added to the mixture<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method.<br>
DOI: 10.6084/m9.figshare.12543350
title: JVASP-29114 tp JVASP-29982

description: JARVIS-DFT input/output files
DOI: 10.6084/m9.figshare.12543353
title: JVASP-31373 to JVASP-34285

description: JARVIS-DFT input/output files
DOI: 10.6084/m9.figshare.12543398.v2
title: Figure 1a Deconvolution Data

description: Source data underlying Figure 1a of manuscript. Results of deconvolution of in silico mixtures.<br>Column names:Method - Method used for deconvolution<br>CellType - Cell type spiked in at a particular fractionSpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method.
DOI: 10.6084/m9.figshare.12543473.v4
title: Source Data Underlying Manuscript Figures

description: <b>Fig1aSupplementaryDataMixture.xlsx</b><br>Source data underlying Figure 1a of manuscript. In Silico mixtures which are deconvolved.<br>Row names:CellType - Cell type spiked in at a particular fraction<br>SpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types<br><br>Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns<br><b>Fig1aSupplementaryDataDeconvolution.xlsx<br></b><br>Source data underlying Figure 1a of manuscript. Results of deconvolution of in silico mixtures.<br>Column names:Method - Method used for deconvolution<br>CellType - Cell type spiked in at a particular fractionSpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method.<br><b>Fig1bSupplementaryDataMixture.xlsx</b><br>Source data underlying Figure 1b of manuscript. In Vitro mixtures which are deconvolved.<br>Row names:Mixture - In Vitro mixture name -- this corresponds to the cell type fractions in the mixtureTumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>NoiseCoefficient - Amount of noise added to the mixture<br>Replicate - Replicate number<br>Cell type names ending in "_GT" are the ground truth percentages of those cell types<br><br>Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns<br><b>Fig1bSupplementaryDataDeconvolution.xlsx</b><br><b><br></b>Source data underlying Figure 1b of manuscript. Results of deconvolution of in vitro mixtures.<br>Column names:Method - Method used for deconvolution<br>Mixture - In Vitro mixture name -- this corresponds to the cell type fractions in the mixtureTumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>NoiseCoefficient - Amount of noise added to the mixture<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method.<br>
DOI: 10.6084/m9.figshare.12543251
title: Diatom morphological inventories

description: Morphological inventories at genera and species level of epiphytic diatoms sampled in Mediterranean ponds.
DOI: 10.6084/m9.figshare.12543347
title: JVASP-29983 to JVASP-31368

description: JARVIS-DFT input/output files
DOI: 10.6084/m9.figshare.12543398.v1
title: Figure 1a Deconvolution Data

description: Source data underlying Figure 1a of manuscript. Results of deconvolution of in silico mixtures.<br>Column names:Method - Method used for deconvolution<br>CellType - Cell type spiked in at a particular fractionSpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method.
DOI: 10.6084/m9.figshare.12543251.v1
title: Diatom morphological inventories

description: Morphological inventories at genera and species level of epiphytic diatoms sampled in Mediterranean ponds.
DOI: 10.15156/bio/sh0842835.10fu
title: SH0842835.10FU

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/sh0842836.10fu
title: SH0842836.10FU

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/sh0842837.10fu
title: SH0842837.10FU

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/sh0842838.10fu
title: SH0842838.10FU

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.