cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25345/c5gt5ff64
title: MassIVE Reanalysis RMSV000000354.1490 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, LRRCC1 [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/c5c24qn1t
title: MassIVE Reanalysis RMSV000000354.1486 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, CEACAM21 [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: 10.6084/m9.figshare.19204253
title: Additional file 2 of Altering the fatty acid profile of Yarrowia lipolytica to mimic cocoa butter by genetic engineering of desaturases

description: Additional file 2. Raw data.
DOI: 10.6084/m9.figshare.19204253.v1
title: Additional file 2 of Altering the fatty acid profile of Yarrowia lipolytica to mimic cocoa butter by genetic engineering of desaturases

description: Additional file 2. Raw data.
DOI: 10.6084/m9.figshare.19204256
title: Additional file 1 of Implementation Degree Assessment Sheet for Health Program in Japan by Customizing CFIR: Development and Validation

description: Additional file 1.
DOI: 10.6084/m9.figshare.19204256.v1
title: Additional file 1 of Implementation Degree Assessment Sheet for Health Program in Japan by Customizing CFIR: Development and Validation

description: Additional file 1.
DOI: 10.25345/c57940t6z
title: MassIVE Reanalysis RMSV000000354.1488 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, R3HDML [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/c53j3913q
title: MassIVE Reanalysis RMSV000000354.1487 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, PDS5B [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/c5zw18s1n
title: MassIVE Reanalysis RMSV000000354.1489 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, HGF [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/c5v40jz8p
title: MassIVE Reanalysis RMSV000000354.1482 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, SH3GL2 [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: 10.6084/m9.figshare.19204322
title: Additional file 2 of The complete chloroplast genome of Onobrychis gaubae (Fabaceae-Papilionoideae): comparative analysis with related IR-lacking clade species

description: Additional file 2: Table S4. Putative preferred codons in the IRLC plastid genomes. RSCU = relative synonymous codon usage.
DOI: 10.6084/m9.figshare.19204322.v1
title: Additional file 2 of The complete chloroplast genome of Onobrychis gaubae (Fabaceae-Papilionoideae): comparative analysis with related IR-lacking clade species

description: Additional file 2: Table S4. Putative preferred codons in the IRLC plastid genomes. RSCU = relative synonymous codon usage.
DOI: 10.6084/m9.figshare.19204394
title: Additional file 3 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 3: Dataset S1. Prediction results for Homo sapiens. Unvalidated human PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level. See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204394.v1
title: Additional file 3 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 3: Dataset S1. Prediction results for Homo sapiens. Unvalidated human PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level. See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204397
title: Additional file 4 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 4: Dataset S2. Prediction results for Saccharomyces cerevisiae. Unvalidated yeast PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level.33See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204400
title: Additional file 5 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 5: Dataset S3. Prediction results for Mus musculus. Unvalidated mouse PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level. See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204400.v1
title: Additional file 5 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 5: Dataset S3. Prediction results for Mus musculus. Unvalidated mouse PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level. See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204397.v1
title: Additional file 4 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 4: Dataset S2. Prediction results for Saccharomyces cerevisiae. Unvalidated yeast PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level.33See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204403
title: Additional file 6 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 6: Dataset S4. Prediction results for Rattus norvegicus. Unvalidated rat PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level. See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204403.v1
title: Additional file 6 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 6: Dataset S4. Prediction results for Rattus norvegicus. Unvalidated rat PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level. See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204406
title: Additional file 7 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 7: Dataset S5. Prediction results for Sus scrofa. Unvalidated pig PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level. See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204406.v1
title: Additional file 7 of Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

description: Additional file 7: Dataset S5. Prediction results for Sus scrofa. Unvalidated pig PPI predictions of the cGAN model, which was trained to predict the N100 connectivity from the N90 level, then was used to produce new predictions (~ N110) from the N100 level. See the Implementation section for more details. STRING protein identifiers are mapped to preferred gene names according to information in the STRING database.
DOI: 10.6084/m9.figshare.19204476
title: Additional file 1 of Social and geographic inequalities in water, sanitation and hygiene access in 21 refugee camps and settlements in Bangladesh, Kenya, Uganda, South Sudan, and Zimbabwe

description: Additional file 1.
DOI: 10.6084/m9.figshare.19204476.v1
title: Additional file 1 of Social and geographic inequalities in water, sanitation and hygiene access in 21 refugee camps and settlements in Bangladesh, Kenya, Uganda, South Sudan, and Zimbabwe

description: Additional file 1.
DOI: 10.6084/m9.figshare.19204481
title: Additional file 2 of Estimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach

description: Additional file 2. Nepal provincial SRB database. DOI: https://doi.org/10.6084/m9.figshare.18765881 [85].
DOI: 10.6084/m9.figshare.19204481.v1
title: Additional file 2 of Estimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach

description: Additional file 2. Nepal provincial SRB database. DOI: https://doi.org/10.6084/m9.figshare.18765881 [85].
DOI: 10.6084/m9.figshare.19204484
title: Additional file 3 of Estimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach

description: Additional file 3. SRB estimates by Nepal province from 1980 to 2016. DOI: https://doi.org/10.6084/m9.figshare.18771695 [86].
DOI: 10.6084/m9.figshare.19204484.v1
title: Additional file 3 of Estimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach

description: Additional file 3. SRB estimates by Nepal province from 1980 to 2016. DOI: https://doi.org/10.6084/m9.figshare.18771695 [86].
DOI: 10.6084/m9.figshare.19204487
title: Additional file 4 of Estimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach

description: Additional file 4. SRB projections by Nepal province from 2017 to 2050. DOI: https://doi.org/10.6084/m9.figshare.18772877 [87].
DOI: 10.6084/m9.figshare.19204487.v1
title: Additional file 4 of Estimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach

description: Additional file 4. SRB projections by Nepal province from 2017 to 2050. DOI: https://doi.org/10.6084/m9.figshare.18772877 [87].
DOI: 10.6084/m9.figshare.19204485
title: Additional file 3 of Assessment of the association between plant-based dietary exposures and cardiovascular disease risk profile in sub-Saharan Africa: a systematic review

description: Additional file 3. Excel Workbook with exclusion reasons
DOI: 10.6084/m9.figshare.19204485.v1
title: Additional file 3 of Assessment of the association between plant-based dietary exposures and cardiovascular disease risk profile in sub-Saharan Africa: a systematic review

description: Additional file 3. Excel Workbook with exclusion reasons
DOI: 10.25345/c5qb9v54d
title: MassIVE Reanalysis RMSV000000354.1491 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, PAPSS1 [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: 10.6084/m9.figshare.19204515.v1
title: Additional file 1 of FAM83A is a potential biomarker for breast cancer initiation

description: Additional file 1. It includes subjects demographics and raw data in form of tables.
DOI: 10.6084/m9.figshare.19204515
title: Additional file 1 of FAM83A is a potential biomarker for breast cancer initiation

description: Additional file 1. It includes subjects demographics and raw data in form of tables.
DOI: 10.5066/p9rw8jrh
title: Reflectance and confocal laser scanning fluorescence spectroscopy of bituminite in Kimmeridge Clay

description: This work investigates the characterization of bituminite (amorphous sedimentary organic matter) in Kimmeridge Clay source rock via confocal laser canning microscopy (CLSM) and atomic force microscopy (AFM). As part of an International Committee for Coal and Organic Petrology working group, an immature (0.42% vitrinite reflectance), organic-rich (44.1 wt.% total organic carbon content) sample of Kimmeridge Clay (sample KC-1) was distributed to multiple laboratories for CLSM characterization. Findings from AFM include the observation that surface roughening or surface flattening of bituminite are induced by differential broad ion beam (BIB) milling and are dependent on the location and scale of AFM topology measurement. This result highlights our still limited understanding of the effects of BIB milling to sedimentary organic matter and indicates the need for further research before this technique can be advanced as a standard practice in petrographic sample preparation. Collectively, the results of this study illustrate the general applicability and versatility of AFM and CLSM as tools for organic petrology research, specifically for improved understanding of the nature and properties of the bituminite maceral.
DOI: 10.25345/c5kk94c0n
title: MassIVE Reanalysis RMSV000000354.1469 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, ST8SIA4 [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/c5ft8dj5d
title: MassIVE Reanalysis RMSV000000354.1493 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, GGA1 [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/c5b27pr1k
title: MassIVE Reanalysis RMSV000000354.1494 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, ERVW-1 [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: 10.5066/p9uk9ppc
title: Argon data for Klamath Mountains

description: This dataset accompanies planned publication '40Ar/39Ar geochronology of hydrothermal activity related to orogenic gold mineralization in the Klamath Mountains, California, U.S.A.'. The Ar/Ar data are for samples that record the mineralization of the area. The geochronology provides time constraints for the mineralization studied in the manuscript. Samples were collected from the Klamath Mountains by Ryan Taylor (U.S. Geological Survey, Geophysics, and Geochemistry Science Center), who sent them to the USGS Denver Argon Geochronology Laboratory for Ar/Ar analysis.
DOI: 10.25345/c5696zx89
title: MassIVE Reanalysis RMSV000000354.1495 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, PES1 [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/c52n4zh6d
title: MassIVE Reanalysis RMSV000000354.1497 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, B3GALNT1 [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.