cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19768369
title: berglund2018spatial_ST_prostate

description: berglund2018spatial_ST_prostate is a spatial transcriptomics datasets, published with a study investigating tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology12. There are 14 sub-datasets in ST_ melanoma, which contains triplicates from 4 prostate cancer patients and two extra sample from patient2 and patient3. The number of spots for the 14 sub-datasets with ~17000 gene expression features are 432 (P1.1), 406 (P1.2), 629 (P1.3), 547 (P2.1), 506 (Patient2_E2), 483 (P2.3), 448 (P2.4), 627 (P3.1), 523 (P3.2), 501 (P3.3), 244(Patient3_D1), 688 (P4.1), 324 (P4.2) and 302 (P4.3). The count matrix of berglund2018spatial_ST_prostate dataset was downloaded from https://www.spatialresearch.org/resources-published-datasets/.
DOI: 10.34740/kaggle/ds/2222985
title: Dog Face Detection(YOLO Format)
DOI: 10.21227/v468-hf61
title: Simulated and real data used in MCA-SAR imaging method

description: We present the simulated and real data used in the experiments of the MCA-SAR imaging. The simulated data is the simulation echo of the existing SAR images, and the real data was collected by RADARSAT-1 in Vancouver on June 16, 2002, which is the public data taken from the book [1].[1] Cumming I G, Wong F H. Digital Signal Processing of Synthetic Aperture Radar Data: Algorithms and Implementation [M]. London, UK: Artech House, 2005.
DOI: 10.6084/m9.figshare.19919792
title: Data used in Environmental stochasticity of spatiotemporal recruitment patterns in coral reef fish (Tahiti, French Polynesia)

description: Data used in Environmental stochasticity of spatiotemporal recruitment patterns in coral reef fish (Tahiti, French Polynesia). Fish surveys, water parameters (oxygen, salinity, pH, temperature) and chemistry (nitrite, nitrate, ammonium, silicate, phosphate) across five locations of Tahiti Iti collected from March to December 2020.
DOI: 10.6084/m9.figshare.19919792.v1
title: Data used in Environmental stochasticity of spatiotemporal recruitment patterns in coral reef fish (Tahiti, French Polynesia)

description: Data used in Environmental stochasticity of spatiotemporal recruitment patterns in coral reef fish (Tahiti, French Polynesia). Fish surveys, water parameters (oxygen, salinity, pH, temperature) and chemistry (nitrite, nitrate, ammonium, silicate, phosphate) across five locations of Tahiti Iti collected from March to December 2020.
DOI: 10.25440/smu.13114661
title: Earable & IoT Dataset from: ERICA - Enabling real-time mistake detection & corrective feedback for free-weights exercises

description: Wearables or infrastructure sensors have been widely proposed for automated tracking and analysis of individual-level exercise activities. This dataset is collected as part of building a pervasive, low-cost digital personal trainer system, that supports fine-grained tracking of an individual’s free-weights exercises via a combination of (a) sensors on personal wireless ear-worn devices (‘earables’) and (b) inexpensive IoT sensors attached to exercise equipment (e.g., dumbbells). The dataset is comprised of sensor signals acquired from two 6-axis IMUs and contains a total of 324 samples for 3 different free-weight exercises performed by 27 individuals.
DOI: 10.17903/fk2/r0ut2o
title: Τεκμήρια για την Αναπαραγωγή Ανάλυσης για: "Κοστούμια, γραβάτες και μπλε κολάρα στην κάλπη: Όψεις της ταξικής ψήφου, 2014-2019"

description: Περιέχει τα αρχεία δεδομένων που είναι απαραίτητα για την αναπαραγωγή ανάλυσης του άρθρου με τίτλο: "Κοστούμια, γραβάτες και μπλε κολάρα στην κάλπη: αποτυπώσεις της ταξικής ψήφου 2014-2019". Περιέχει 5 αρχεία δεδομένων: Τα δεδομένα του Ευρωβαρόμετρου από το 2014 έως και το 2019 που χρησιμοποιήθηκαν στα διαγράμματα 1 έως 4 Τον Δείκτη Ανθρώπινης Φτώχειας για τους δήμους της Περιφέρειας Αττικής Την διαφορά εκλογικών ποσοστών μεταξύ ΝΔ και ΣΥΡΙΖΑ στις εθνικές εκλογές του 2019 για κάθε δήμο της Περιφέρειας Αττικής Τα δεδομένα από το Ευρωβαρόμετρο του Δεκεμβρίου του 2019 Τον αλγόριθμο για την δημιουργία της μεταβλητής της ταξικής δομής. To άρθρο δημοσιεύτηκε στο 41o τεύχος του επιστημονικού περιοδικού Επιστήμη και Κοινωνία: Επιθεώρηση Πολιτικής και Ηθικής Θεωρίας και είναι διαθέσιμο εδώ.
DOI: 10.25919/7nzp-hy30
title: East Australian Current mooring raw data collection 2012-2013

description: The East Australian Current mooring raw data collection 2012-2013 contains all the raw instrument data files and instrument setup information, build documentation, deployment and recovery log sheets and scanned paper documentation for the deployment covering the period April, 2012 to August, 2013. Quality controlled data and gridded data products from this mooring deployment can be accessed via the links in the Related Links section of this collection record.
DOI: 10.57770/jowiji/smdqdz
title: 40478_2020_971_MOESM1_ESM.pdf

description: Additional file 1: Figure S1. BicD2 expression and cell distributions in the developing cortex subjected to BicD2 RNAi. Figure S2. Immunostaining of different markers in brain slices electroporated with Bicd2 K775X
DOI: 10.57770/jowiji/otxvca
title: 40478_2020_971_MOESM2_ESM_MovieS1.avi

description: Additional file 2: Movie S1. Wildtype BicD2 expressing neural progenitor in IZ perform a normal basally directed radial migration at E16.5. The time format is mm:ss. Scale bar = 5 μm.
DOI: 10.57770/jowiji/wdfgww
title: 40478_2020_971_MOESM3_ESM_MovieS2.avi

description: Additional file 3: Movie S2. Mutant (K775X) BicD2 expressing neural progenitor in IZ show a totally disrupted radial migration at E16.5. The time format is mm:ss. Scale bar = 5 μm.
DOI: 10.57770/jowiji
title: Replication Data for: Impairment in dynein-mediated nuclear translocation by BICD2 C-terminal truncation leads to neuronal migration defect and human brain malformation.

description: During brain development, the nucleus of migrating neurons follows the centrosome and translocates into the leading process. Defects in these migratory events, which affect neuronal migration, cause lissencephaly and other neurodevelopmental disorders. However, the mechanism of nuclear translocation remains elusive. Using whole exome sequencing (WES), we identified a novel nonsense BICD2 variant p.(Lys775Ter) (K775X) from a lissencephaly patient. Interestingly, most BICD2 missense variants have been associated with human spinal muscular atrophy (SMA) without obvious brain malformations. By in utero electroporation, we showed that BicD2 knockdown in mouse embryos inhibited neuronal migration. Surprisingly, we observed severe blockage of neuronal migration in cells overexpressing K775X but not in those expressing wild-type BicD2 or SMA-associated missense variants. The centrosome of the mutant was, on average, positioned farther away from the nucleus, indicating a failure in nuclear translocation without affecting the centrosome movement. Furthermore, BicD2 localized at the nuclear envelope (NE) through its interaction with NE protein Nesprin-2. K775X variant disrupted this interaction and further interrupted the NE recruitment of BicD2 and dynein. Remarkably, fusion of BicD2-K775X with NE-localizing domain KASH resumed neuronal migration. Our results underscore impaired nuclear translocation during neuronal migration as an important pathomechanism of lissencephaly.
DOI: 10.34740/kaggle/dsv/3716920
title: BBC News
DOI: 10.6084/m9.figshare.19919321
title: Datasets of "Authigenic clay mineral evidence for restricted, evaporitic conditions during the emergence of the Ediacaran Doushantuo Biota"

description: Comms E XRD raw data: xrdml files for XRD results showed in the manuscript; Comms E SEM data: 25% zoomed SEM-EDS mineral mapping overview images of 19 samples listed in the manuscript; Supplementary data 1: Mineralogy data for supplementary figure 1 Supplementary data 2: EPMA data for supplementary figure 2
DOI: 10.6084/m9.figshare.19919321.v2
title: Datasets of "Authigenic clay mineral evidence for restricted, evaporitic conditions during the emergence of the Ediacaran Doushantuo Biota"

description: Comms E XRD raw data: xrdml files for XRD results showed in the manuscript; Comms E SEM data: 25% zoomed SEM-EDS mineral mapping overview images of 19 samples listed in the manuscript; Supplementary data 1: Mineralogy data for supplementary figure 1 Supplementary data 2: EPMA data for supplementary figure 2
DOI: 10.6084/m9.figshare.19919321.v1
title: Datasets of "Authigenic clay mineral evidence for restricted, evaporitic conditions during the emergence of the Ediacaran Doushantuo Biota"

description: Comms E XRD raw data: xrdml files for XRD results showed in the manuscript; Comms E SEM data: 25% zoomed SEM-EDS mineral mapping overview images of 19 samples listed in the manuscript; Supplementary data 1: Mineralogy data for supplementary figure 1 Supplementary data 2: EPMA data for supplementary figure 2
DOI: 10.6084/m9.figshare.16767220.v6
title: Supplementary Materials: High-frequency Fluctuation Intensity as a Predictor of Post-Stenotic Dilatation in Swine

description: Supplementary Materials: High-frequency Fluctuation Intensity as a Predictor of Post-Stenotic Dilatation in Swine
DOI: 10.6084/m9.figshare.19786456
title: wang2018three_STATmap

description: The data is downloaded from the link https://www.starmapresources.org/data； Here is the reference paper: Wang X, Allen WE, Wright MA, et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. <em>Science</em>. 2018;361(6400):eaat5691. doi:10.1126/science.aat5691
DOI: 10.6084/m9.figshare.19919062
title: wang2021easi_EasiFish

description: SourceURL:file:///Users/zlh/Library/Containers/com.tencent.xinWeChat/Data/Library/Application This dataset was from the EASI-FISH original paper19. The tissue is from mouse lateral hypothalamic area. It has 36423 spots and 26 genes and all the raw data are from https://janelia.figshare.com/articles/dataset/EASI-FISH_enabled_spatial_analysis_of_molecular_cell_types_in_the_lateral_hypothalamus/13749154. We provide the processed data at https://figshare.com/account/projects/139123/articles/19919062.
DOI: 10.6084/m9.figshare.19919062.v1
title: wang2021easi_EasiFish

description: SourceURL:file:///Users/zlh/Library/Containers/com.tencent.xinWeChat/Data/Library/Application This dataset was from the EASI-FISH original paper19. The tissue is from mouse lateral hypothalamic area. It has 36423 spots and 26 genes and all the raw data are from https://janelia.figshare.com/articles/dataset/EASI-FISH_enabled_spatial_analysis_of_molecular_cell_types_in_the_lateral_hypothalamus/13749154. We provide the processed data at https://figshare.com/account/projects/139123/articles/19919062.
DOI: 10.34740/kaggle/dsv/3716992
title: Polish-Ukrainian translations from Tatoeba
DOI: 10.34740/kaggle/dsv/3717030
title: Michelin Guide Restaurants 2021
DOI: 10.5281/zenodo.6592024
title: Dataset: What are the characteristics of highly-used packages? A case study on the npm ecosystem

description: With the popularity of software ecosystems, the number of open source components (a.k.a. “packages”) has been growing rapidly. Identifying high-quality and well-maintained packages from a large pool of packages to depend on is a basic and important problem, as it is beneficial for various applications, such as package recommendation, package search, etc. However, there is no systematic and comprehensive work so far that focuses on addressing this problem except in online discussions or in informal literature and interviews. To fill this gap, in this paper, we conduct a mixed qualitative and quantitative analysis to understand how developers identify and select relevant open source packages. In particular, we start by surveying 118 JavaScript developers from the npm ecosystem to qualitatively understand the factors that make a package to be highly-used within the ecosystem. The survey results show that JavaScript developers believe that highly-used packages are well-documented, receive a high number of stars on GitHub, have a large number of downloads, and do not suffer from vulnerabilities. Then, we conduct an experiment to quantitatively validate the developers' perception of the factors that make a highly-used package. In this analysis, we collect and mine historical data from 2,427 packages divided into highly-used and low-used packages. For each package in the dataset, we collect quantitative data to present the factors studied in the developers' survey. Next, we use regression analysis to quantitatively explain which of the studied factors are the most important. Our regression analysis support developers' believe about highly-used packages. In particular, the results show that highly-used packages tend to be impacted by the number of downloads, stars, and how larger is readme file of the package.
DOI: 10.5281/zenodo.5000317
title: Dataset: What are the characteristics of highly-used packages? A case study on the npm ecosystem

description: With the popularity of software ecosystems, the number of open source components (a.k.a. “packages”) has been growing rapidly. Identifying high-quality and well-maintained packages from a large pool of packages to depend on is a basic and important problem, as it is beneficial for various applications, such as package recommendation, package search, etc. However, there is no systematic and comprehensive work so far that focuses on addressing this problem except in online discussions or in informal literature and interviews. To fill this gap, in this paper, we conduct a mixed qualitative and quantitative analysis to understand how developers identify and select relevant open source packages. In particular, we start by surveying 118 JavaScript developers from the npm ecosystem to qualitatively understand the factors that make a package to be highly-used within the ecosystem. The survey results show that JavaScript developers believe that highly-used packages are well-documented, receive a high number of stars on GitHub, have a large number of downloads, and do not suffer from vulnerabilities. Then, we conduct an experiment to quantitatively validate the developers' perception of the factors that make a highly-used package. In this analysis, we collect and mine historical data from 2,427 packages divided into highly-used and low-used packages. For each package in the dataset, we collect quantitative data to present the factors studied in the developers' survey. Next, we use regression analysis to quantitatively explain which of the studied factors are the most important. Our regression analysis support developers' believe about highly-used packages. In particular, the results show that highly-used packages tend to be impacted by the number of downloads, stars, and how larger is readme file of the package.
DOI: 10.6084/m9.figshare.19915003
title: vickovic2019high_HDST_MouseOlfactoryBulb

description: Spatial and molecular characteristics determine tissue function, yet high-resolution methods to capture both concurrently are lacking. Here,this is the processed H5ad file of the high-definition spatial transcriptomics, which captures RNA from histological tissue sections on a dense, spatially barcoded bead array. For details and file descriptions, please go to github repo at: <sub>https://github.com/broadinstitute/hdst.</sub>
DOI: 10.6084/m9.figshare.19915003.v1
title: vickovic2019high_HDST_MouseOlfactoryBulb

description: Spatial and molecular characteristics determine tissue function, yet high-resolution methods to capture both concurrently are lacking. Here,this is the processed H5ad file of the high-definition spatial transcriptomics, which captures RNA from histological tissue sections on a dense, spatially barcoded bead array. For details and file descriptions, please go to github repo at: <sub>https://github.com/broadinstitute/hdst.</sub>
DOI: 10.34740/kaggle/dsv/3716990
title: Mechanical Keyboards Subreddit
DOI: 10.6084/m9.figshare.19919420
title: Supplementary table 3.xlsx

description: Supplementary Table 3. The p value of linkage disequilibrium (LD) between all pairs of 29 microhaplotype loci in 96 unrelated Han Chinese from our study.
DOI: 10.6084/m9.figshare.19919420.v1
title: Supplementary table 3.xlsx

description: Supplementary Table 3. The p value of linkage disequilibrium (LD) between all pairs of 29 microhaplotype loci in 96 unrelated Han Chinese from our study.
DOI: 10.6084/m9.figshare.19919417
title: Supplementary Table 2.xlsx

description: Supplementary Table 2. The p value of HWE of the population from our study.
DOI: 10.6084/m9.figshare.19919417.v2
title: Supplementary Table 2.xlsx

description: Supplementary Table 2. The p value of HWE of the population from our study.
DOI: 10.6084/m9.figshare.19919417.v1
title: Supplementary Table 2.xlsx

description: Supplementary Table 2. The p value of HWE of the population from our study.
DOI: 10.6084/m9.figshare.19919414
title: Supplementary table 1.xlsx

description: Supplementary Table 1. The specific genotype profiles of 36 microhaplotype loci for 96 unrelated Shandong Han Chinese from our study.
DOI: 10.6084/m9.figshare.19919414.v2
title: Supplementary table 1.xlsx

description: Supplementary Table 1. The specific genotype profiles of 36 microhaplotype loci for 96 unrelated Shandong Han Chinese from our study.
DOI: 10.6084/m9.figshare.19919414.v1
title: Supplementary table 1.xlsx

description: Supplementary Table 1. The specific genotype profiles of 36 microhaplotype loci for 96 unrelated Shandong Han Chinese from our study.
DOI: 10.6084/m9.figshare.19786291
title: maynard2021transcriptome_10X_Human_DLPFC

description: Processed data are downloaded from the Globus endpoint ‘jhpce#HumanPilot10x’ that is also listed at http://research.libd.org/globus. The raw data provided through Globus include all the FASTQ files and raw image files. Here is the article : Maynard, K.R., Collado-Torres, L., Weber, L.M. <em>et al.</em> Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex. <em>Nat Neurosci</em> <strong>24,</strong> 425–436 (2021).
DOI: 10.6084/m9.figshare.19919422
title: Additional file 10 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 10. Galaxy workflow file for word2Vec descriptor-based ML modeling. Ready to use Galaxy workflow file to reproduce ML modeling based on word2Vec descriptors.
DOI: 10.6084/m9.figshare.19919422.v1
title: Additional file 10 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 10. Galaxy workflow file for word2Vec descriptor-based ML modeling. Ready to use Galaxy workflow file to reproduce ML modeling based on word2Vec descriptors.
DOI: 10.6084/m9.figshare.19919434.v1
title: Additional file 3 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 3. Non-anti-cancer peptides. FASTA file containing 138 non-Anti-Cancer Peptides collected from previously published experimental studies.
DOI: 10.6084/m9.figshare.19919431
title: Additional file 2 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 2. Anti-cancer peptides. FASTA file containing 138 Anti-Cancer Peptides collected from previously published experimental studies.
DOI: 10.6084/m9.figshare.19919437
title: Additional file 4 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 4. Class labeled ACPs and non-ACPs. Tabular file containing class labeled ACPs and non-ACPs.
DOI: 10.6084/m9.figshare.19919431.v1
title: Additional file 2 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 2. Anti-cancer peptides. FASTA file containing 138 Anti-Cancer Peptides collected from previously published experimental studies.
DOI: 10.6084/m9.figshare.19919440
title: Additional file 5 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 5. Word Vector Model. A pre-calculated word-vector model to calculate word2vec descriptors.
DOI: 10.6084/m9.figshare.19919434
title: Additional file 3 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 3. Non-anti-cancer peptides. FASTA file containing 138 non-Anti-Cancer Peptides collected from previously published experimental studies.
DOI: 10.6084/m9.figshare.19919440.v1
title: Additional file 5 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 5. Word Vector Model. A pre-calculated word-vector model to calculate word2vec descriptors.
DOI: 10.6084/m9.figshare.19919449.v1
title: Additional file 8 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 8. Galaxy workflow file for figures. Ready to use Galaxy workflow file to reproduce peptide library analysis and figures, presented in the manuscript.
DOI: 10.6084/m9.figshare.19919437.v1
title: Additional file 4 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 4. Class labeled ACPs and non-ACPs. Tabular file containing class labeled ACPs and non-ACPs.
DOI: 10.6084/m9.figshare.19919452
title: Additional file 9 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 9. Galaxy workflow file for ML modeling. Ready to use Galaxy workflow file to reproduce ML modeling based on CTD, GearyAuto and MoranAuto descriptors.
DOI: 10.6084/m9.figshare.19919452.v1
title: Additional file 9 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 9. Galaxy workflow file for ML modeling. Ready to use Galaxy workflow file to reproduce ML modeling based on CTD, GearyAuto and MoranAuto descriptors.
DOI: 10.6084/m9.figshare.19919449
title: Additional file 8 of PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

description: Additional file 8. Galaxy workflow file for figures. Ready to use Galaxy workflow file to reproduce peptide library analysis and figures, presented in the manuscript.