cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12781671.v1
title: Additional file 3 of SOX10-regulated promoter use defines isoform-specific gene expression in Schwann cells

description: Additional file 3: Supplementary Table 2. Genes that harbor SOX10-associated transcription start sites (TSSs) and are annotated with multiple isoforms in the human RefSeq database. First column: A list of all genes that harbor a SOX10-associated TSS (reside near SOX10 and H3K4me3 ChIP-Seq peaks) and are annotated with at least two unique transcript isoforms in human RefSeq. Second column: A list of all genes that harbor a SOX10-associated TSS and are annotated with at least two unique transcript isoforms in human RefSeq that also confer unique protein-coding sequences. Third column: A list of all genes that harbor a SOX10-dependent TSS (exhibited reduced expression upon loss of SOX10 in S16 cells) and are annotated with at least two unique transcript isoforms in human RefSeq. Fourth column: A list of all genes that harbor a SOX10-dependent TSS and are annotated with at least two unique transcript isoforms in human RefSeq that also confer unique protein-coding sequences.
DOI: 10.6084/m9.figshare.12781629
title: Additional file 9 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional File 9. Multiple sequence alignment of all 6 Mus species’ V1R peptide sequences. (fasta)
DOI: 10.6084/m9.figshare.12781620
title: Additional file 6 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 6. M. spretus coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “s”: Vmn1r137 as 137-s. (fasta).
DOI: 10.6084/m9.figshare.12781623
title: Additional file 7 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 7. M. caroli coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “c”: Vmn1r137 as 137-c. (fasta).
DOI: 10.6084/m9.figshare.12781629.v1
title: Additional file 9 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional File 9. Multiple sequence alignment of all 6 Mus species’ V1R peptide sequences. (fasta)
DOI: 10.6084/m9.figshare.12781620.v1
title: Additional file 6 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 6. M. spretus coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “s”: Vmn1r137 as 137-s. (fasta).
DOI: 10.6084/m9.figshare.12781623.v1
title: Additional file 7 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 7. M. caroli coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “c”: Vmn1r137 as 137-c. (fasta).
DOI: 10.6084/m9.figshare.12781626
title: Additional file 8 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 8. M. pahari coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “p”: Vmn1r137 as 137-p. (fasta).
DOI: 10.6084/m9.figshare.12781612
title: Additional file 3 of How does sediment exposure affect corals? A systematic review protocol

description: Additional file 3. Data coding and extraction form to be used for the systematic review and meta-analysis.
DOI: 10.6084/m9.figshare.12781614
title: Additional file 4 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 4. M. spicilegus coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “z”: Vmn1r137 as 137-z. (fasta).
DOI: 10.6084/m9.figshare.12781617
title: Additional file 5 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 5. M. macedonicus coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “x”: Vmn1r137 as 137-x. (fasta).
DOI: 10.6084/m9.figshare.12781626.v1
title: Additional file 8 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 8. M. pahari coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “p”: Vmn1r137 as 137-p. (fasta).
DOI: 10.6084/m9.figshare.12781612.v1
title: Additional file 3 of How does sediment exposure affect corals? A systematic review protocol

description: Additional file 3. Data coding and extraction form to be used for the systematic review and meta-analysis.
DOI: 10.6084/m9.figshare.12781617.v1
title: Additional file 5 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 5. M. macedonicus coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “x”: Vmn1r137 as 137-x. (fasta).
DOI: 10.6084/m9.figshare.12781606
title: Additional file 1 of How does sediment exposure affect corals? A systematic review protocol

description: Additional file 1. Filled-in ROSES checklist and meta-data form for this manuscript.
DOI: 10.6084/m9.figshare.12781608
title: Additional file 2 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 2. Categorization of V1R transcripts as either putative transcript variants or gene duplicates for the 5 non-commensal Mus species sequenced.
DOI: 10.6084/m9.figshare.12781609
title: Additional file 2 of How does sediment exposure affect corals? A systematic review protocol

description: Additional file 2. Search scoping exercise and list of definitive reviews and benchmark studies.
DOI: 10.6084/m9.figshare.12781609.v1
title: Additional file 2 of How does sediment exposure affect corals? A systematic review protocol

description: Additional file 2. Search scoping exercise and list of definitive reviews and benchmark studies.
DOI: 10.6084/m9.figshare.12781608.v1
title: Additional file 2 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 2. Categorization of V1R transcripts as either putative transcript variants or gene duplicates for the 5 non-commensal Mus species sequenced.
DOI: 10.6084/m9.figshare.12781614.v1
title: Additional file 4 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 4. M. spicilegus coding sequences of V1r genes expressed in the VNO. Gene annotations are abbreviated and contain species identifier “z”: Vmn1r137 as 137-z. (fasta).
DOI: 10.6084/m9.figshare.12781605
title: Additional file 1 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 1. Maximum likelihood gene tree of all 6 Mus species’ V1R peptide sequences. (txt)
DOI: 10.6084/m9.figshare.12781606.v1
title: Additional file 1 of How does sediment exposure affect corals? A systematic review protocol

description: Additional file 1. Filled-in ROSES checklist and meta-data form for this manuscript.
DOI: 10.6084/m9.figshare.12781605.v1
title: Additional file 1 of Distinct evolutionary trajectories of V1R clades across mouse species

description: Additional file 1. Maximum likelihood gene tree of all 6 Mus species’ V1R peptide sequences. (txt)
DOI: 10.6084/m9.figshare.12781525
title: Additional file 3 of A tentacle for every occasion: comparing the hunting tentacles and sweeper tentacles, used for territorial competition, in the coral Galaxea fascicularis

description: Additional file 3. Supplementary Excel file with transcripts assembled by Trinity, their expression levels and annotations.
DOI: 10.6084/m9.figshare.12781522
title: Additional file 2 of A tentacle for every occasion: comparing the hunting tentacles and sweeper tentacles, used for territorial competition, in the coral Galaxea fascicularis

description: Additional file 2. Supplementary interactive version of figure 3B (html file).
DOI: 10.6084/m9.figshare.12781525.v1
title: Additional file 3 of A tentacle for every occasion: comparing the hunting tentacles and sweeper tentacles, used for territorial competition, in the coral Galaxea fascicularis

description: Additional file 3. Supplementary Excel file with transcripts assembled by Trinity, their expression levels and annotations.
DOI: 10.6084/m9.figshare.12781522.v1
title: Additional file 2 of A tentacle for every occasion: comparing the hunting tentacles and sweeper tentacles, used for territorial competition, in the coral Galaxea fascicularis

description: Additional file 2. Supplementary interactive version of figure 3B (html file).
DOI: 10.6084/m9.figshare.12781402
title: Additional file 1 of An age and space structured SIR model describing the Covid-19 pandemic

description: Integration of (9)–(10) with κ = 0 $\kappa=0$ , κ as in (20) and 10 times κ as in (20). Integration of (9) with initial datum as in (10) and the parameters described above. The three integrations differ in the choice of κ, which is assigned the value 0, the values in (20) and 10 times this latter value. The file names are: kappa0.avi corresponding to κ = 0; kappa1.avi corresponding to κ as in (20) kappa2.avi corresponding to 10 times the value of κ in (20). kappa3.avi corresponding to 20 times the value of κ in (20). (ZIP 2.2 MB)
DOI: 10.6084/m9.figshare.12781408
title: Additional file 3 of An age and space structured SIR model describing the Covid-19 pandemic

description: The Effects of Spatial Movements. Integration of (8) with initial datum as in (14). The case with spatial movement is in file MovingYes.avi, while the case with no movement is in MovingNo.avi. (ZIP 2.5 MB)
DOI: 10.6084/m9.figshare.12781405
title: Additional file 2 of An age and space structured SIR model describing the Covid-19 pandemic

description: Care Homes Integration. Integration of (9) with initial datum as in (11)–(13). The file name is CareHomes.avi. (ZIP 498 kB)
DOI: 10.6084/m9.figshare.12781402.v1
title: Additional file 1 of An age and space structured SIR model describing the Covid-19 pandemic

description: Integration of (9)–(10) with κ = 0 $\kappa=0$ , κ as in (20) and 10 times κ as in (20). Integration of (9) with initial datum as in (10) and the parameters described above. The three integrations differ in the choice of κ, which is assigned the value 0, the values in (20) and 10 times this latter value. The file names are: kappa0.avi corresponding to κ = 0; kappa1.avi corresponding to κ as in (20) kappa2.avi corresponding to 10 times the value of κ in (20). kappa3.avi corresponding to 20 times the value of κ in (20). (ZIP 2.2 MB)
DOI: 10.6084/m9.figshare.12781405.v1
title: Additional file 2 of An age and space structured SIR model describing the Covid-19 pandemic

description: Care Homes Integration. Integration of (9) with initial datum as in (11)–(13). The file name is CareHomes.avi. (ZIP 498 kB)
DOI: 10.6084/m9.figshare.12781408.v1
title: Additional file 3 of An age and space structured SIR model describing the Covid-19 pandemic

description: The Effects of Spatial Movements. Integration of (8) with initial datum as in (14). The case with spatial movement is in file MovingYes.avi, while the case with no movement is in MovingNo.avi. (ZIP 2.5 MB)
DOI: 10.6084/m9.figshare.12781383
title: Additional file 1 of The engagement of psychiatrists in the assessment of euthanasia requests from psychiatric patients in Belgium: a survey study

description: Additional file 1.
DOI: 10.6084/m9.figshare.12781383.v1
title: Additional file 1 of The engagement of psychiatrists in the assessment of euthanasia requests from psychiatric patients in Belgium: a survey study

description: Additional file 1.
DOI: 10.6084/m9.figshare.12781356
title: Additional file 1 of Bioinformatics analysis combined with experiments to explore potential prognostic factors for pancreatic cancer

description: Additional file 1: Identification of differentlly expressed genes.
DOI: 10.6084/m9.figshare.12781356.v1
title: Additional file 1 of Bioinformatics analysis combined with experiments to explore potential prognostic factors for pancreatic cancer

description: Additional file 1: Identification of differentlly expressed genes.
DOI: 10.6084/m9.figshare.12781331
title: Data.xlsx

description: <b>SARS-CoV-2 was not found in pressure injury exudates of critical COVID-19 patients</b><b></b>
DOI: 10.6084/m9.figshare.12781331.v1
title: Data.xlsx

description: <b>SARS-CoV-2 was not found in pressure injury exudates of critical COVID-19 patients</b><b></b>
DOI: 10.6084/m9.figshare.12781280
title: Basic quality statistics of GridION sequencing data

description: Basic quality statistics of GridION sequencing data
DOI: 10.6084/m9.figshare.12781289
title: Quast report

description: Quast report
DOI: 10.6084/m9.figshare.12781280.v1
title: Basic quality statistics of GridION sequencing data

description: Basic quality statistics of GridION sequencing data
DOI: 10.6084/m9.figshare.12781289.v1
title: Quast report

description: Quast report
DOI: 10.6084/m9.figshare.12781256
title: COVID-19 Three Wave MTurk Data

description: This data set is from a prospective study of multiple health constructs during COVID-19.
DOI: 10.6084/m9.figshare.12781274
title: Predicted secondary metabolite biosynthetic gene clusters (smBGCs) in H. alvei A23BA genome.

description: <b>Predicted secondary metabolite biosynthetic gene clusters (smBGCs) in <i>H. alvei</i> A23BA genome.</b>
DOI: 10.6084/m9.figshare.12781250
title: Data from: Functional response and progeny production of the Madeira mealybug parasitoid, Anagyrus sp. nov. nr. sinope: The effects of host and parasitoid densities.

description: Anagyrus sp. nov. nr. sinope Noyes & Menezes is a gregarious koinobiont parasitoid of the Madeira mealybug, Phenacoccus madeirensis Green. In this study, we explored the influence of host and parasitoid densities on the functional response and progeny production of Anagyrus sp. nov. nr. sinope. In the first experiment, which was designed to detect the occurrence of mutual interference among foraging parasitoids, we exposed a constant number of mealybugs (N = 60) to varying numbers of parasitoids (P = 1, 2, 4, 8, and 20). Mutual interference among 20 parasitoids reduced the number of mealybugs parasitized and the number of progeny produced per parasitoid by 9 and 7 times, respectively, compared to 1 parasitoid. The interference constant (m) (±SE) was estimated at 0.62 ± 0.03. The presence of conspecifics increased the proportion of males in the offspring population. In the second set of experiments, the parasitoids were released alone or in groups of 2 or 4 into patches containing one of six parasitoid/mealybug ratios (1:2, 1:5, 1:10, 1:20, 1:40, and 1:60). Anagyrus sp. nov. nr. sinope exhibited a type II functional response. The estimated maximum number of mealybugs parasitized (i.e., the asymptote of functional response) over a 24-h period was reduced from 10.4 ± 0.6 when foraging alone to 8.1 ± 0.4 and 5.1 ± 0.2 when in groups of 2 and 4, respectively. The number of progeny reflected the effects of the parasitoid and host densities on the parasitism rate. The highest number of progeny was produced by the parasitoids foraging alone in patches containing the highest parasitoid/host ratio (1:60). The results of this study suggest that both the host and parasitoid densities have significant impact on the functional response and progeny production of Anagyrus sp. nov. nr. sinope.
DOI: 10.6084/m9.figshare.12781256.v1
title: COVID-19 Three Wave MTurk Data

description: This data set is from a prospective study of multiple health constructs during COVID-19.
DOI: 10.6084/m9.figshare.12781181
title: Gene clusters potentially associated with environmental adaptation, bioremediation, biocontrol, and plant-growth promotion in H. alvei A23BA

description: Gene clusters potentially associated with environmental adaptation, bioremediation, biocontrol, and plant-growth promotion in <i>H. alvei</i> A23BA
DOI: 10.6084/m9.figshare.12781181.v1
title: Gene clusters potentially associated with environmental adaptation, bioremediation, biocontrol, and plant-growth promotion in H. alvei A23BA

description: Gene clusters potentially associated with environmental adaptation, bioremediation, biocontrol, and plant-growth promotion in <i>H. alvei</i> A23BA
DOI: 10.6084/m9.figshare.12781193
title: Composition of ultra-minimal substrate medium

description: Composition of ultra-minimal substrate medium
DOI: 10.6084/m9.figshare.12781193.v1
title: Composition of ultra-minimal substrate medium

description: Composition of ultra-minimal substrate medium
DOI: 10.6084/m9.figshare.12781151
title: dna-sequences.fasta

description: The datasets of five Copepod associated bacteriobiome were used for the meta-analysis to predict the important Operational taxonomic unit (OUTs) and potential metabolic functions. The dataset presented here was QIIME2 analysed sequence dataset.<br>
DOI: 10.6084/m9.figshare.12781157
title: Biom file

description: Biom file generated from the meta-analysis<br>
DOI: 10.6084/m9.figshare.12781157.v1
title: Biom file

description: Biom file generated from the meta-analysis<br>
DOI: 10.6084/m9.figshare.12781151.v1
title: dna-sequences.fasta

description: The datasets of five Copepod associated bacteriobiome were used for the meta-analysis to predict the important Operational taxonomic unit (OUTs) and potential metabolic functions. The dataset presented here was QIIME2 analysed sequence dataset.<br>
DOI: 10.6084/m9.figshare.12781064
title: raw data for quantification of D12 and D18/19 immunocytochemistry

description: Underlying data for quantification graphs shown in Figure 3<br>cppipe files: CellProfiler v.3.1.9 was used to generate the pipelines for each image set (one differentiation protocol, 3 channels, 2 timepoints).<br>quantification.xlsx: The raw data generated after running the pipelines were copied to a spreadsheet. 'Cells / Nuclei (%)' column shows the percentage of cells positive for SOX2 at D12 and TBR2 at D18/19. 'Intracellular APOE / Cells (%)' column shows the percentage of intracellular APOE-positive cells amongst SOX2- and TBR2-positive cells. These 2 columns are presented as bar graphs on Figure 3 of the manuscript.<br>
DOI: 10.6084/m9.figshare.12781064.v1
title: raw data for quantification of D12 and D18/19 immunocytochemistry

description: Underlying data for quantification graphs shown in Figure 3<br>cppipe files: CellProfiler v.3.1.9 was used to generate the pipelines for each image set (one differentiation protocol, 3 channels, 2 timepoints).<br>quantification.xlsx: The raw data generated after running the pipelines were copied to a spreadsheet. 'Cells / Nuclei (%)' column shows the percentage of cells positive for SOX2 at D12 and TBR2 at D18/19. 'Intracellular APOE / Cells (%)' column shows the percentage of intracellular APOE-positive cells amongst SOX2- and TBR2-positive cells. These 2 columns are presented as bar graphs on Figure 3 of the manuscript.<br>
DOI: 10.6084/m9.figshare.12780992
title: Online Calculatar of the Nomogram for Predicting Clinical Outcome in Unilateral Primary Aldosteronism

description: Online Calculatar of the Nomogram for Predicting Clinical Outcome in Unilateral Primary Aldosteronism
DOI: 10.6084/m9.figshare.12781004.v1
title: Nomogram-Based Preoperative Score for Predicting Clinical Outcome in Unilateral Primary Aldosteronism

description: <b>Nomogram-Based Preoperative Score for Predicting Clinical Outcome in Unilateral Primary Aldosteronism </b>
DOI: 10.6084/m9.figshare.12780992.v1
title: Online Calculatar of the Nomogram for Predicting Clinical Outcome in Unilateral Primary Aldosteronism

description: Online Calculatar of the Nomogram for Predicting Clinical Outcome in Unilateral Primary Aldosteronism
DOI: 10.6084/m9.figshare.12780872
title: Determinants of COVID-19 mortality in the United States dataset(BrainX)

description: With the current COVID-19 pandemic, there have been various principal questions left unanswered. In response to these vital questions, many leading health professionals and researchers have brought forward new datasets. <br>This data set uses several trusted sources to provide reliable information relating to the socioeconomic, racial, weather, healthcare resource utilization and travel data from all of the 50 states of the United States of America including District of Columbia in one dataset. The dataset includes numerous possible determinants of COVID-19 spread and mortality, all organized in a simple spreadsheet.COVID-19 positive rates and mortality in the dataset were obtained from https://covidtracking.com/data. All the data is accurate as of April 30,2020, reported through the sources.<br>Two researchers collected data from available resources which include governmental and non-governmental sources.(See article and source table references below).<br>With this dataset, explainable machine learning models showing relationship of these determinants with COVID-19 mortality in the United States cases were created.<br>Reference: Mathur P, Sethi T, Mathur A, et al. Explainable machine learning models to understand determinants of COVID-19 mortality in the United States. <i>medRxiv. </i>2020:2020.2005.2023.20110189.(Source table for the dataset is available as supplemental to this article.)<br>This particular dataset was created for the purpose of continuing research into COVID-19. However, there are many other uses for this large dataset. With information from all 50 states and the District of Columbia, many US statistics can be compared.The data from this dataset can also be used to make new datasets with different purposes. <br>
DOI: 10.6084/m9.figshare.12780872.v1
title: COVID-19 project BrainX_Tav_May4.csv

description: With the current COVID-19 pandemic, there have been various principal questions left unanswered. In response to these vital questions, multiple leading health professionals and researchers have brought forward a new data set. <br>This data set uses several trusted sources to provide reliable information relating to the socioeconomic, racial, weather, healthcare resource utilization and travel data from all the 50 states of the United States of America including District of Columbia in one dataset. The dataset includes numerous possible determinants of COVID-19 spread and mortality, all organized in a simple spreadsheet. With data from all fifty states covering over four general categories and twenty-two specific contributing factors, everything is available in one place. COVID-19 positive rates and mortality in the dataset were obtained from https://covidtracking.com/data. All the data is accurate as of April 30,2020 as reported through the sources.<br>Two researchers collected data from available resources from the reliable governmental and non-governmental sources.(See article and source table references below).<br>With this dataset, explainable machine learning models showing relationship of these determinants with COVID-19 mortality in the United States cases were created. Ref: Mathur P, Sethi T, Mathur A, et al. Explainable machine learning models to understand determinants of COVID-19 mortality in the United States. <i>medRxiv. </i>2020:2020.2005.2023.20110189. Source table for the dataset is available as supplemental to this article.<br>This particular dataset was created for the purpose of continuing research into COVID-19. However, there are many other uses for this large dataset. With information from all 50 states and the District of Columbia, many US statistics can be compared to other statistics or countries. The data from this dataset can also be used to make new datasets with different purposes. <br>
DOI: 10.6084/m9.figshare.12780836
title: WikiTalk - Training and test sets

description: Training and test sets extracted from WikiTalk dataset (https://snap.stanford.edu/data/wiki-Talk.htmll)
DOI: 10.6084/m9.figshare.12780827
title: CollegeMsg - Training and test sets

description: Training and test sets extracted from CollegeMsg dataset (https://snap.stanford.edu/data/CollegeMsg.html)