cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8183202
title: ATG9A regulates dissociation of recycling endosomes from microtubules leading to formation of influenza A virus liquid condensates - MAIN FIGURES

description: Metadata for the manuscript entitled "ATG9A regulates dissociation of recycling endosomes from microtubules leading to formation of influenza A virus liquid inclusions" - MAIN FIGURES
DOI: 10.5517/ccdc.csd.cc2cbh7g
title: CCDC 2184825: Experimental Crystal Structure Determination

description: Related Article: Aleksandra Mrzygłód, Rafał Januszewski, Julia Duszczak, Michał Dutkiewicz, Maciej Kubicki, Beata Dudziec|2023|Inorg.Chem.Front.|10|4587|doi:10.1039/D3QI00500C
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.
DOI: 10.5281/zenodo.8190097
title: ReLandProject/MosulDrownedLandscapes: Journal Submission Version

description: Data and code version submitted to the journal. Updated to account for changes in libraries/api.
DOI: 10.5281/zenodo.8190098
title: ReLandProject/MosulDrownedLandscapes: Journal Submission Version

description: Data and code version submitted to the journal. Updated to account for changes in libraries/api.
DOI: 10.5281/zenodo.8183201
title: ATG9A regulates dissociation of recycling endosomes from microtubules leading to formation of influenza A virus liquid condensates - MAIN FIGURES

description: Metadata for the manuscript entitled "ATG9A regulates dissociation of recycling endosomes from microtubules leading to formation of influenza A virus liquid inclusions" - MAIN FIGURES
DOI: 10.5281/zenodo.8190146
title: TCGA Kidney Renal Clear Cell Carcinoma (KIRC) Clinical Data

description: <strong>Abstract:</strong> The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about KIRC. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. <strong>Inspiration:</strong> This dataset was uploaded to UBRITE for GTKB project. <strong>Instruction:</strong> The survival and phenotype data were merged into one file. Empty columns were removed. Columns with the same value for every sample were also removed. <strong>Acknowledgments:</strong> Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 <strong>U-BRITE last update: </strong>07/13/2023
description: UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical
description: {"references": ["Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]}
DOI: 10.5517/ccdc.csd.cc2dzzcr
title: CCDC 2234305: Experimental Crystal Structure Determination

description: Related Article: Li-Xiang Guo, Yao Gao, Pei Zhang, Jian-Hui Yang, Bin Liu|2023|Dalton Trans.|52|10099|doi:10.1039/D3DT01302B
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.
DOI: 10.5517/ccdc.csd.cc2dzzft
title: CCDC 2234307: Experimental Crystal Structure Determination

description: Related Article: Li-Xiang Guo, Yao Gao, Pei Zhang, Jian-Hui Yang, Bin Liu|2023|Dalton Trans.|52|10099|doi:10.1039/D3DT01302B
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.
DOI: 10.5281/zenodo.8190145
title: TCGA Kidney Renal Clear Cell Carcinoma (KIRC) Clinical Data

description: <strong>Abstract:</strong> The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about KIRC. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. <strong>Inspiration:</strong> This dataset was uploaded to UBRITE for GTKB project. <strong>Instruction:</strong> The survival and phenotype data were merged into one file. Empty columns were removed. Columns with the same value for every sample were also removed. <strong>Acknowledgments:</strong> Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 <strong>U-BRITE last update: </strong>07/13/2023
description: UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical
description: {"references": ["Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]}
DOI: 10.5517/ccdc.csd.cc2dzzgv
title: CCDC 2234308: Experimental Crystal Structure Determination

description: Related Article: Li-Xiang Guo, Yao Gao, Pei Zhang, Jian-Hui Yang, Bin Liu|2023|Dalton Trans.|52|10099|doi:10.1039/D3DT01302B
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.
DOI: 10.5517/ccdc.csd.cc2dzzhw
title: CCDC 2234309: Experimental Crystal Structure Determination

description: Related Article: Li-Xiang Guo, Yao Gao, Pei Zhang, Jian-Hui Yang, Bin Liu|2023|Dalton Trans.|52|10099|doi:10.1039/D3DT01302B
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.
DOI: 10.5517/ccdc.csd.cc2dzz8n
title: CCDC 2234302: Experimental Crystal Structure Determination

description: Related Article: Li-Xiang Guo, Yao Gao, Pei Zhang, Jian-Hui Yang, Bin Liu|2023|Dalton Trans.|52|10099|doi:10.1039/D3DT01302B
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.
DOI: 10.5517/ccdc.csd.cc2dzz9p
title: CCDC 2234303: Experimental Crystal Structure Determination

description: Related Article: Li-Xiang Guo, Yao Gao, Pei Zhang, Jian-Hui Yang, Bin Liu|2023|Dalton Trans.|52|10099|doi:10.1039/D3DT01302B
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.
DOI: 10.5517/ccdc.csd.cc2dzzbq
title: CCDC 2234304: Experimental Crystal Structure Determination

description: Related Article: Li-Xiang Guo, Yao Gao, Pei Zhang, Jian-Hui Yang, Bin Liu|2023|Dalton Trans.|52|10099|doi:10.1039/D3DT01302B
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.
DOI: 10.5517/ccdc.csd.cc2dzzds
title: CCDC 2234306: Experimental Crystal Structure Determination

description: Related Article: Li-Xiang Guo, Yao Gao, Pei Zhang, Jian-Hui Yang, Bin Liu|2023|Dalton Trans.|52|10099|doi:10.1039/D3DT01302B
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.
DOI: 10.5281/zenodo.8190154
title: TCGA Lower Grade Glioma (LGG) Clinical Data

description: <strong>Abstract:</strong> The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about LGG. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. <strong>Inspiration:</strong> This dataset was uploaded to UBRITE for GTKB project. <strong>Instruction:</strong> The survival and phenotype data were merged into one file. Empty columns were removed. Columns with the same value for every sample were also removed. <strong>Acknowledgments:</strong> Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 <strong>U-BRITE last update: </strong>07/13/2023
description: UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical
description: {"references": ["Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]}
DOI: 10.5281/zenodo.8190153
title: TCGA Lower Grade Glioma (LGG) Clinical Data

description: <strong>Abstract:</strong> The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about LGG. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. <strong>Inspiration:</strong> This dataset was uploaded to UBRITE for GTKB project. <strong>Instruction:</strong> The survival and phenotype data were merged into one file. Empty columns were removed. Columns with the same value for every sample were also removed. <strong>Acknowledgments:</strong> Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 <strong>U-BRITE last update: </strong>07/13/2023
description: UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical
description: {"references": ["Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]}
DOI: 10.5281/zenodo.8190127
title: TCGA Head & Neck Squamous Cell Carcinoma (HNSC) Clinical Data

description: <strong>Abstract:</strong> The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about HNSC. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. <strong>Inspiration:</strong> This dataset was uploaded to UBRITE for GTKB project. <strong>Instruction:</strong> The survival and phenotype data were merged into one file. Empty columns were removed. Columns with the same value for every sample were also removed. <strong>Acknowledgments:</strong> Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 <strong>U-BRITE last update: </strong>07/13/2023
description: UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical
description: {"references": ["Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]}
DOI: 10.5281/zenodo.8190126
title: TCGA Head & Neck Squamous Cell Carcinoma (HNSC) Clinical Data

description: <strong>Abstract:</strong> The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about HNSC. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. <strong>Inspiration:</strong> This dataset was uploaded to UBRITE for GTKB project. <strong>Instruction:</strong> The survival and phenotype data were merged into one file. Empty columns were removed. Columns with the same value for every sample were also removed. <strong>Acknowledgments:</strong> Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 <strong>U-BRITE last update: </strong>07/13/2023
description: UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical
description: {"references": ["Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]}
DOI: 10.34943/81b33b28-5da4-4944-9047-b16b5ea15b6c
title: Barkley Canyon Junction Box Deployed 2020-06-01

description: The OceanWorks Junction Box JB-09 was deployed on 2020-06-01 at Barkley Canyon. Barkley Canyon is a submarine canyon located on the continental shelf and slope break. Features include exposed gas hydrates and their associated ecosystems. Accumulation and movement of sediment, upwelling, and plankton blooms are studied in this area. This device is a Junction Box. Junction Boxes supply power and communications to deployed instruments. Junction boxes have a number of serial and ethernet ports, including 400V ethernet ports that enable connections to other junction boxes and high-voltage instruments. Junction boxes can convert high voltages to lower voltages (15V, 24V or 48V) required by many instruments. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.