cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25345/c5b853j0p
title: MassIVE Reanalysis RMSV000000354.2240 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, ARHGEF40 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c56h4cq6x
title: MassIVE Reanalysis RMSV000000354.2239 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, SLC17A3 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c52r3nx2s
title: MassIVE Reanalysis RMSV000000354.2241 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, SHC1 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5z31np1x
title: MassIVE Reanalysis RMSV000000354.2242 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, MOBKL2C [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5tb0xv75
title: MassIVE Reanalysis RMSV000000354.2244 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, MIA3 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5js9h781
title: MassIVE Reanalysis RMSV000000354.2250 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, ACOX3 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5pk0722b
title: MassIVE Reanalysis RMSV000000354.2243 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, ZSWIM2 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5f18sf46
title: MassIVE Reanalysis RMSV000000354.2248 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, SERPINA4 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c59882n0f
title: MassIVE Reanalysis RMSV000000354.2246 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, MFSD5 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c55h7bt6p
title: MassIVE Reanalysis RMSV000000354.2245 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, NFIL3 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c51v5bd58
title: MassIVE Reanalysis RMSV000000354.2217 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, BMX [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5x34ms06
title: MassIVE Reanalysis RMSV000000354.2249 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, XAGE1A [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5sb3wz6f
title: MassIVE Reanalysis RMSV000000354.2247 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, RNF135 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5nk36523
title: MassIVE MSV000088873 - Integrated changes in thermal stability and proteome abundance during altered growth and metabolic cell states.
title: This dataset is a multiplex proteomics experiment consisting of both PISA and protein abundance measurements across the transition from lof to stationary phase E.coli.
DOI: 10.25345/c5ht2gb8b
title: MassIVE Reanalysis RMSV000000354.2251 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, SFXN1 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.15468/dl.1rsbw8
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lasiurus cinereus (Palisot de Beauvois, 1796)",
 "Country is Mexico",
 "Geometry POLYGON((-106.995849 23.140359,-106.995849 20.571081,-103.677978 20.571081,-103.677978 23.140359,-106.995849 23.140359))"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000266-150422101436696/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.puq39w
title: Occurrence Download

description: A dataset containing 26213093 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Continent is South America",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 26213093 records from 2865 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000679-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.5827294
title: Data set from long-term wave, wind and response monitoring of the Bergsøysund Bridge

description: Wind, wave, displacement and acceleration data have been collected in a measurement campaign on the Bergsøysund Bridge between the years 2014 and 2018. The data set is now available in this open-access research entry, for free access and download. The data is collected in two h5-files (hierachical data format), with sampling rates 2 Hz and 10 Hz, downsampled from the raw sampling rate of 200 Hz. Note that the data has undergone some minimal signal processing and adjustment, in line with that applied to the Hardanger Bridge data described in Fenerci et al. (2021). Tools and examples for import, data visualization and initial analysis are given in the opyndata Python package available on GitHub (Kvåle, 2022). Furthermore, a document briefly describing the hierarchy and structure of the data, is given. For more details on the measurement system and the bridge, it is referred to Kvåle and Øiseth (2017).
description: {"references": ["A. Fenerci, K. Andreas Kv\u00e5le, \u00d8. Wiig Petersen, A. R\u00f8nnquist, and O. \u00d8iseth, \"Data Set from Long-Term Wind and Acceleration Monitoring of the Hardanger Bridge,\" J. Struct. Eng., vol. 147, no. 5, p. 04721003, 2021, doi: 10.1061/(asce)st.1943-541x.0002997.", "K. A. Kv\u00e5le and O. \u00d8iseth, \"Structural monitoring of an end-supported pontoon bridge,\" Mar. Struct., vol. 52, pp. 188\u2013207, Mar. 2017, doi: 10.1016/j.marstruc.2016.12.004.", "K. A. Kv\u00e5le. (2022). knutankv/opyndata: Initial release, available on Zenodo (v0.0.2). Zenodo. https://doi.org/10.5281/zenodo.5978358"]}
DOI: 10.5281/zenodo.6065165
title: Data set from long-term wave, wind and response monitoring of the Bergsøysund Bridge

description: Wind, wave, displacement and acceleration data have been collected in a measurement campaign on the Bergsøysund Bridge between the years 2014 and 2018. The data set is now available in this open-access research entry, for free access and download. The data is collected in two h5-files (hierachical data format), with sampling rates 2 Hz and 10 Hz, downsampled from the raw sampling rate of 200 Hz. Note that the data has undergone some minimal signal processing and adjustment, in line with that applied to the Hardanger Bridge data described in Fenerci et al. (2021). Tools and examples for import, data visualization and initial analysis are given in the opyndata Python package available on GitHub (Kvåle, 2022). Furthermore, a document briefly describing the hierarchy and structure of the data, is given. For more details on the measurement system and the bridge, it is referred to Kvåle and Øiseth (2017).
description: {"references": ["A. Fenerci, K. Andreas Kv\u00e5le, \u00d8. Wiig Petersen, A. R\u00f8nnquist, and O. \u00d8iseth, \"Data Set from Long-Term Wind and Acceleration Monitoring of the Hardanger Bridge,\" J. Struct. Eng., vol. 147, no. 5, p. 04721003, 2021, doi: 10.1061/(asce)st.1943-541x.0002997.", "K. A. Kv\u00e5le and O. \u00d8iseth, \"Structural monitoring of an end-supported pontoon bridge,\" Mar. Struct., vol. 52, pp. 188\u2013207, Mar. 2017, doi: 10.1016/j.marstruc.2016.12.004.", "K. A. Kv\u00e5le. (2022). knutankv/opyndata: Initial release, available on Zenodo (v0.0.2). Zenodo. https://doi.org/10.5281/zenodo.5978358"]}
DOI: 10.5281/zenodo.7514254
title: Data set from long-term wave, wind and response monitoring of the Bergsøysund Bridge

description: Wind, wave, displacement and acceleration data have been collected in a measurement campaign on the Bergsøysund Bridge between the years 2014 and 2018. The data set is now available in this open-access research entry, for free access and download. The data is collected in two h5-files (hierachical data format), with sampling rates 2 Hz and 10 Hz, downsampled from the raw sampling rate of 200 Hz. Note that the data has undergone some minimal signal processing and adjustment, in line with that applied to the Hardanger Bridge data described in Fenerci et al. (2021). Tools and examples for import, data visualization and initial analysis are given in the opyndata Python package available on GitHub (Kvåle, 2022). Furthermore, a document briefly describing the hierarchy and structure of the data, is given. For more details on the measurement system and the bridge, it is referred to Kvåle and Øiseth (2017).
description: {"references": ["A. Fenerci, K. Andreas Kv\u00e5le, \u00d8. Wiig Petersen, A. R\u00f8nnquist, and O. \u00d8iseth, \"Data Set from Long-Term Wind and Acceleration Monitoring of the Hardanger Bridge,\" J. Struct. Eng., vol. 147, no. 5, p. 04721003, 2021, doi: 10.1061/(asce)st.1943-541x.0002997.", "K. A. Kv\u00e5le and O. \u00d8iseth, \"Structural monitoring of an end-supported pontoon bridge,\" Mar. Struct., vol. 52, pp. 188\u2013207, Mar. 2017, doi: 10.1016/j.marstruc.2016.12.004.", "K. A. Kv\u00e5le. (2022). knutankv/opyndata: Initial release, available on Zenodo (v0.0.2). Zenodo. https://doi.org/10.5281/zenodo.5978358"]}
DOI: 10.5281/zenodo.7695674
title: Data set from long-term wave, wind and response monitoring of the Bergsøysund Bridge

description: Wind, wave, displacement and acceleration data have been collected in a measurement campaign on the Bergsøysund Bridge between the years 2014 and 2018. The data set is now available in this open-access research entry, for free access and download. The data is collected in two h5-files (hierachical data format), with sampling rates 2 Hz and 10 Hz, downsampled from the raw sampling rate of 200 Hz. Note that the data has undergone some minimal signal processing and adjustment, in line with that applied to the Hardanger Bridge data described in Fenerci et al. (2021). Tools and examples for import, data visualization and initial analysis are given in the opyndata Python package available on GitHub (Kvåle, 2022). Furthermore, a document briefly describing the hierarchy and structure of the data, is given. For more details on the measurement system and the bridge, it is referred to Kvåle and Øiseth (2017). The updated, copyrighted version of the appended preprint is published by ASCE with the following DOI: 10.1061/JSENDH/STENG-12095.
description: {"references": ["A. Fenerci, K. Andreas Kv\u00e5le, \u00d8. Wiig Petersen, A. R\u00f8nnquist, and O. \u00d8iseth, \"Data Set from Long-Term Wind and Acceleration Monitoring of the Hardanger Bridge,\" J. Struct. Eng., vol. 147, no. 5, p. 04721003, 2021, doi: 10.1061/(asce)st.1943-541x.0002997.", "K. A. Kv\u00e5le and O. \u00d8iseth, \"Structural monitoring of an end-supported pontoon bridge,\" Mar. Struct., vol. 52, pp. 188\u2013207, Mar. 2017, doi: 10.1016/j.marstruc.2016.12.004.", "K. A. Kv\u00e5le. (2022). knutankv/opyndata: Initial release, available on Zenodo (v0.0.2). Zenodo. https://doi.org/10.5281/zenodo.5978358"]}
DOI: 10.5281/zenodo.8051200
title: dendraster_excentricus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8051199
title: dendraster_excentricus_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23291594
title: <strong>Alterations and Correlations of Gut Microbiota and Fecal Metabolome Characteristics in a Rabbit Model of Intervertebral Disc Degeneration</strong>

description: Fecal DNA was extracted from 16 fecal samples (8 rabbit models with IDD and 8 sex- and age-matched healthy controls) and analyzed by high-throughput 16S rDNA sequencing. The fecal samples were also analyzed by liquid chromatography–mass spectrometry (LC–MS)-based metabolomics. Multivariate analyses were conducted for the relationship between the omics data and IDD, including principal coordinate analysis (PCoA), principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA), and hierarchical cluster analysis (HCA). Linear discriminant analysis effect size (LEfSe) was employed for biomarker discovery. Moreover, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the differential metabolites. The potential correlation between differential gut microbiota and metabolites was then assessed.
DOI: 10.6084/m9.figshare.23291594.v1
title: <strong>Alterations and Correlations of Gut Microbiota and Fecal Metabolome Characteristics in a Rabbit Model of Intervertebral Disc Degeneration</strong>

description: Fecal DNA was extracted from 16 fecal samples (8 rabbit models with IDD and 8 sex- and age-matched healthy controls) and analyzed by high-throughput 16S rDNA sequencing. The fecal samples were also analyzed by liquid chromatography–mass spectrometry (LC–MS)-based metabolomics. Multivariate analyses were conducted for the relationship between the omics data and IDD, including principal coordinate analysis (PCoA), principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA), and hierarchical cluster analysis (HCA). Linear discriminant analysis effect size (LEfSe) was employed for biomarker discovery. Moreover, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the differential metabolites. The potential correlation between differential gut microbiota and metabolites was then assessed.
DOI: 10.7910/dvn/xagjwk
title: Replication Data for: Parental Investment, School Choice, and the Persistent Benefits of Intervention in Early Childhood

description: Replication Data
DOI: 10.5281/zenodo.8001876
title: Temperature nowcasting verification dataset

description: Verification files for the Verif program. See https://github.com/WFRT/verif for details.
DOI: 10.5281/zenodo.8001875
title: Temperature nowcasting verification dataset

description: Verification files for the Verif program. See https://github.com/WFRT/verif for details.
DOI: 10.5281/zenodo.8001886
title: Precipitation short-range forecasting verification dataset

description: Verification files for the Verif program. See https://github.com/WFRT/verif for details.
DOI: 10.5281/zenodo.8001885
title: Precipitation short-range forecasting verification dataset

description: Verification files for the Verif program. See https://github.com/WFRT/verif for details.
DOI: 10.5281/zenodo.8001888
title: Wind speed short-range forecasting verification dataset

description: Verification files for the Verif program. See https://github.com/WFRT/verif for details.
DOI: 10.5281/zenodo.8001887
title: Wind speed short-range forecasting verification dataset

description: Verification files for the Verif program. See https://github.com/WFRT/verif for details.
DOI: 10.5517/ccdc.csd.cc2dz89z
title: CCDC 2233621: Experimental Crystal Structure Determination

description: Related Article: Jun Yang, Pan Zhang, Zeyuan Shen, Yi Zhou, Zhi-Xiang Yu|2023|Chem (Cell Press)|9|1477|doi:10.1016/j.chempr.2023.01.020
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.