cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p95msfvf
title: Digital database of the previously published geologic map of the Boulder-Fort Collins-Greeley area, Colorado

description: This digital map shows the geographic extent of rock stratigraphic units (formations) as compiled by Colton in 1976 under the Front Range Urban Corridor Geology Program. Colton used his own geologic mapping and previously published geologic maps to compile one map having a single classification of geologic units. The resulting published color paper map (USGS Map I-855-G, Colton, 1978) was intended for land-use planning and to depict the regional geology. In 1997-1999, another USGS project designed to address urban growth issues was undertaken. This project, the USGS Front Range Infrastructure Resources Project, undertook to digitize Colton's map at 1:100,000 scale, making it useable in Geographical Information Systems (GIS). That product is described here. In general, the digitized map depicts in its western part Precambrian igneous and metamorphic rocks, Pennsylvanian and younger sedimentary rock units, major faults, and brecciated zones along an eastern strip (5-20 km wide) of the Front Range. The central and eastern parts of the map (Colorado Piedmont) show a mantle of Quaternary unconsolidated deposits and interspersed outcrops of sedimentary rock of Cretaceous or Tertiary age. A surficial mantle of unconsolidated deposits of Quaternary age is differentiated and depicted as eolium (wind-blown sand and silt), alluvium (river gravel, sand, and silt of variable composition), colluvium, and a few landslide deposits. At the mountain front, north-trending, Paleozoic and Mesozoic formations of sandstone, shale, and minor limestone dip mostly eastward and form folds, fault blocks, hogbacks and intervening valleys. Local dikes and sills of Tertiary rhyodacite and basalt intrude rocks near the range front, mostly in the Boulder area.
DOI: 10.5281/zenodo.8398240
title: PDST sensor files European eel (Anguilla anguilla) Belgium

description: <strong>Brief data description</strong> This data consists of the raw sensor data from a tagging study on European eel (<em>Anguilla anguilla</em> L.) caught and released in Nieuwpoort Belgium. The applied tags were pop-off G5 data storage tags (CEFAS Technology, Lowestoft, UK). Temperature was measured every 10 seconds and pressure (i.e. depth) every 2 seconds. The sensor data contains the raw data per eel with the tag ID as an individual eel. The tags were externally attached to eels and came off before or at a preprogrammed time, drifted to the surface, washed ashore and when found, the data could be downloaded when the tag was retrieved. Note that some recovered tags were reused hence a tag ID can occur more than once. This data is part of the eel-pdst-analysis GitHub repository: https://github.com/PieterjanVerhelst/eel-pdst-analysis. The sensor files have the following destination: eel-pdst-analysis\data\interim\sensorlogs <strong>Files</strong> Files are structured as a Frictionless Data Package. You can access all data in R via <code>https://zenodo.org/record/8398240/files/datapackage.json</code> using frictionless. <strong>More Info</strong> For more information on the data collection and analysis, see the following two research papers: Scientific Reports: https://doi.org/10.1038/s41598-021-04052-7 Science of The Total Environment: https://doi.org/10.1016/j.scitotenv.2023.167341
DOI: 10.5281/zenodo.8398239
title: PDST sensor files European eel (Anguilla anguilla) Belgium

description: <strong>Brief data description</strong> This data consists of the raw sensor data from a tagging study on European eel (<em>Anguilla anguilla</em> L.) caught and released in Nieuwpoort Belgium. The applied tags were pop-off G5 data storage tags (CEFAS Technology, Lowestoft, UK). Temperature was measured every 10 seconds and pressure (i.e. depth) every 2 seconds. The sensor data contains the raw data per eel with the tag ID as an individual eel. The tags were externally attached to eels and came off before or at a preprogrammed time, drifted to the surface, washed ashore and when found, the data could be downloaded when the tag was retrieved. Note that some recovered tags were reused hence a tag ID can occur more than once. This data is part of the eel-pdst-analysis GitHub repository: https://github.com/PieterjanVerhelst/eel-pdst-analysis. The sensor files have the following destination: eel-pdst-analysis\data\interim\sensorlogs <strong>Files</strong> Files are structured as a Frictionless Data Package. You can access all data in R via <code>https://zenodo.org/record/8398240/files/datapackage.json</code> using frictionless. <strong>More Info</strong> For more information on the data collection and analysis, see the following two research papers: Scientific Reports: https://doi.org/10.1038/s41598-021-04052-7 Science of The Total Environment: https://doi.org/10.1016/j.scitotenv.2023.167341
DOI: 10.5281/zenodo.8215091
title: CurveCurator: A recalibrated F-statistic to assess, classify, and explore significance of dose-response curves - Example Datasets

description: CurveCurator is an open-source analysis platform for any dose-dependent data. It fits a classical 4-parameter equation to estimate effect potency, effect size, and the statistical significance of the observed response. 2D-thresholding efficiently reduces false positives in high-throughput experiments and separates relevant from irrelevant or insignificant hits in an automated and unbiased manner. An interactive dashboard allows users to quickly explore data locally. <br> Here, we store example dose-dependent data, parameter files, and the corresponding CurveCurator pipeline outputs (v.0.2.0). Example data sets include Kinobeads Drug-binding data (1), CTRP Viability data sets (2), and deryptM Proteomics data sets (3). The F-value matrices for developing the CurveCurator tools are deposited as well. Original data sources: (1) https://doi.org:10.1126/science.aan4368 (2) https://doi.org:10.1158/2159-8290.CD-15-0235 (3) https://doi.org:10.1126/science.ade3925
description: {"references": ["https://doi.org:10.1126/science.aan4368", "https://doi.org:10.1158/2159-8290.CD-15-0235", "https://doi.org:10.1126/science.ade3925"]}
DOI: 10.5281/zenodo.8215092
title: CurveCurator: A recalibrated F-statistic to assess, classify, and explore significance of dose-response curves - Example Datasets

description: CurveCurator is an open-source analysis platform for any dose-dependent data. It fits a classical 4-parameter equation to estimate effect potency, effect size, and the statistical significance of the observed response. 2D-thresholding efficiently reduces false positives in high-throughput experiments and separates relevant from irrelevant or insignificant hits in an automated and unbiased manner. An interactive dashboard allows users to quickly explore data locally. <br> Here, we store example dose-dependent data, parameter files, and the corresponding CurveCurator pipeline outputs (v.0.0.6). Example data sets include Kinobeads Drug-binding data (1), CTRP Viability data sets (2), and deryptM Proteomics data sets (3). The F-value matrices for developing the CurveCurator tools are deposited as well. Original data sources: (1) https://doi.org:10.1126/science.aan4368 (2) https://doi.org:10.1158/2159-8290.CD-15-0235 (3) https://doi.org:10.1126/science.ade3925
description: {"references": ["https://doi.org:10.1126/science.aan4368", "https://doi.org:10.1158/2159-8290.CD-15-0235", "https://doi.org:10.1126/science.ade3925"]}
DOI: 10.5281/zenodo.8399823
title: CurveCurator: A recalibrated F-statistic to assess, classify, and explore significance of dose-response curves - Example Datasets

description: CurveCurator is an open-source analysis platform for any dose-dependent data. It fits a classical 4-parameter equation to estimate effect potency, effect size, and the statistical significance of the observed response. 2D-thresholding efficiently reduces false positives in high-throughput experiments and separates relevant from irrelevant or insignificant hits in an automated and unbiased manner. An interactive dashboard allows users to quickly explore data locally. <br> Here, we store example dose-dependent data, parameter files, and the corresponding CurveCurator pipeline outputs (v.0.2.0). Example data sets include Kinobeads Drug-binding data (1), CTRP Viability data sets (2), and deryptM Proteomics data sets (3). The F-value matrices for developing the CurveCurator tools are deposited as well. Original data sources: (1) https://doi.org:10.1126/science.aan4368 (2) https://doi.org:10.1158/2159-8290.CD-15-0235 (3) https://doi.org:10.1126/science.ade3925
description: {"references": ["https://doi.org:10.1126/science.aan4368", "https://doi.org:10.1158/2159-8290.CD-15-0235", "https://doi.org:10.1126/science.ade3925"]}
DOI: 10.5281/zenodo.8334714
title: Supplementary Information to the Consultation on the Progress Report of the Financial Sustainability Task Force: Responses

description: This document contains the responses received in the consultation carried out by the Financial Sustainability Task Force of the EOSC Association (TF FinSust in the following) to obtain feedback on their Progress Report. The link to the Report can be found on the page about the Task Force at the website of the EOSC Association (https://www.eosc.eu/advisory-groups/financial-sustainability). The questionnaire is available in Zenodo (https://doi.org/10.5281/zenodo.8334658)
DOI: 10.5281/zenodo.8334715
title: Supplementary Information to the Consultation on the Progress Report of the Financial Sustainability Task Force: Responses

description: This document contains the responses received in the consultation carried out by the Financial Sustainability Task Force of the EOSC Association (TF FinSust in the following) to obtain feedback on their Progress Report. The link to the Report can be found on the page about the Task Force at the website of the EOSC Association (https://www.eosc.eu/advisory-groups/financial-sustainability). The questionnaire is available in Zenodo (https://doi.org/10.5281/zenodo.8334658)
DOI: 10.3886/e188621v1-142004
title: The influence of the COVID-19 among the elderly from 2016 to 2022

description: The date is mada from a total of 8 longitudinal surveys from 2016 to 2022. Physical function was assessed by weight, body mass index, body fat percentage, skeletal muscle mass index, calf circumference, grip strength, knee extension strength, the 5-times chair stand test, and the timed up & go test. Functional capacity was measured using the Tokyo Metropolitan Institute of Gerontology index of competence, cognitive function was measured using the Trail Making Test - A, and mental health was measured using the Geriatric Depression Scale.
DOI: 10.34740/kaggle/ds/3494164
title: Leveraging Data Analytics and AI in Auditing
DOI: 10.5281/zenodo.8399744
title: RNA velocity code and data of control/Vcl cKO/public CNCC

description: RNA velocity code and data of control/Vcl cKO/public CNCC
DOI: 10.5281/zenodo.8399743
title: RNA velocity code and data of control/Vcl cKO/public CNCC

description: RNA velocity code and data of control/Vcl cKO/public CNCC
DOI: 10.5517/ccdc.csd.cc23cgts
title: CCDC 1947445: Experimental Crystal Structure Determination

description: Related Article: Jiayong Zhang, Zhengjie He|2023|J.Org.Chem.|88|13102|doi:10.1021/acs.joc.3c01313
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.cc28qwws
title: CCDC 2107376: Experimental Crystal Structure Determination

description: Related Article: Neha Meena, Vikki N. Shinde, Sonam, Prakash N. Swami, Krishnan Rangan, Anil Kumar|2023|J.Org.Chem.|88|12902|doi:10.1021/acs.joc.3c00717
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.cc28qxdb
title: CCDC 2107392: Experimental Crystal Structure Determination

description: Related Article: Neha Meena, Vikki N. Shinde, Sonam, Prakash N. Swami, Krishnan Rangan, Anil Kumar|2023|J.Org.Chem.|88|12902|doi:10.1021/acs.joc.3c00717
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.cc2b52p9
title: CCDC 2149840: Experimental Crystal Structure Determination

description: Related Article: Shashank Tripathi, Monty Kumar, Ayush Shivhare, Ruchir Kant, Milind M. Deshmukh, Ajay Kumar Srivastava|2023|Org.Lett.|25|6638|doi:10.1021/acs.orglett.3c02415
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.cc2byxcl
title: CCDC 2173700: Experimental Crystal Structure Determination

description: Related Article: Mattéo Cayla, Dorian Sonet, Emilien Tarayre, Romain Bapt, Brigitte Bibal|2023|J.Org.Chem.|88|13067|doi:10.1021/acs.joc.3c01252
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.cc2byxqy
title: CCDC 2173711: Experimental Crystal Structure Determination

description: Related Article: Mattéo Cayla, Dorian Sonet, Emilien Tarayre, Romain Bapt, Brigitte Bibal|2023|J.Org.Chem.|88|13067|doi:10.1021/acs.joc.3c01252
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.cc2c7ts7
title: CCDC 2182269: Experimental Crystal Structure Determination

description: Related Article: Mattéo Cayla, Dorian Sonet, Emilien Tarayre, Romain Bapt, Brigitte Bibal|2023|J.Org.Chem.|88|13067|doi:10.1021/acs.joc.3c01252
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.cc2c7tt8
title: CCDC 2182270: Experimental Crystal Structure Determination

description: Related Article: Mattéo Cayla, Dorian Sonet, Emilien Tarayre, Romain Bapt, Brigitte Bibal|2023|J.Org.Chem.|88|13067|doi:10.1021/acs.joc.3c01252
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.cc2c7tv9
title: CCDC 2182271: Experimental Crystal Structure Determination

description: Related Article: Mattéo Cayla, Dorian Sonet, Emilien Tarayre, Romain Bapt, Brigitte Bibal|2023|J.Org.Chem.|88|13067|doi:10.1021/acs.joc.3c01252
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.cc2d08tj
title: CCDC 2204807: Experimental Crystal Structure Determination

description: Related Article: Mattéo Cayla, Dorian Sonet, Emilien Tarayre, Romain Bapt, Brigitte Bibal|2023|J.Org.Chem.|88|13067|doi:10.1021/acs.joc.3c01252
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: 10.25592/uhhfdm.13411
title: Single mutation protein structure pairs extracted from the PDB with MicroMiner

description: This page provides the single mutation data extracted with MicroMiner from the PDB. The data contains amino acid pairs in protein structures from the PDB, exemplifying single mutations’ local structural changes for single chains and pairs for protein–protein interfaces. Mutations to non-standard residues are also provided.<br> See the MicroMiner publication for details: <em>Sieg, J.; Rarey, M. Searching similar local 3D micro-environments in protein structure databases with MicroMiner, 2023 (accepted in Briefings in Bioinformatics)</em> <strong>Data content:</strong> <strong>pdb_all_monomer.tsv</strong> all single mutations in monomer/single chains 255853767 pairs/lines 15GB <strong>filtered_single_mutations_pdb_monomer.tsv</strong> redundancy and similarity filtered pdb_all_monomer.tsv 4868765 pairs/lines 324MB <strong>single_mutations_pdb_monomer_non_standard_aa.tsv</strong> only single mutations containing non-standard in monomer/single chains 350969 pairs/lines 21MB <strong>pdb_all_ppi.tsv</strong> all single mutations at PPIs 45752145 pairs/lines 2.7GB <strong>filtered_single_mutations_pdb_ppi.tsv</strong> redundancy and similarity filtered pdb_all_ppi.tsv 799130 pairs/lines 54MB <strong>single_mutations_pdb_ppi_non_standard_aa.tsv</strong> only single mutations containing non-standard residues at PPIs 114671 pairs/lines 6.9MB A row in the TSV files describes the residue position of the single mutation in the wild-type (query) and mutant (hit). Multiple local structural and sequential similarity measures are provided, computed from the residue 3D micro-environments. The column fullSeqId contains the global sequence similarity. The first two rows of a TSV file look this: <pre><code class="language-bash">queryName queryChain queryAA queryPos hitName hitChain hitAA hitPos siteIdentity siteBackBoneRMSD siteAllAtomRMSD nofSiteResidues alignmentLDDT fullSeqId 10GS A CYS 47 2J9H A ALA 48 0.938 0.223 0.431 16.0 0.996 0.976 0.976</code></pre> <em>queryName</em>: query PDB-ID <em>queryChain</em>: query chain ID <em>queryAA</em>: query amino acid type (three letter code) <em>queryPos</em>: query sequence position of the amino acid residue <em>hitName</em>: hit PDB-ID <em>hitChain</em>: hit chain ID <em>hitAA</em>: hit amino acid type (three letter code) <em>hitPos</em>: hit sequence position of the amino acid residue <em>siteIdentity</em>: sequence identity of the aligned micro-environments <em>siteBackBoneRMSD</em>: Calpha-RMSD of the aligned micro-environments <em>siteAllAtomRMSD</em>: all-atom-RMSD of the aligned micro-environments <em>nofSiteResidues</em>: number of residues in the micro-environments <em>alignmentLDDT</em>: mean LDDT score of all residues in the aligned micro-environments <em>fullSeqId</em>: global sequence identity of the query chain and hit chain (as specified by the chain IDs) <pre><code>This work was supported by the German Federal Ministry of Education and Research as part of de.NBI [grant number 031L0105] and protP.S.I. [grant number 031B0405B].</code></pre>
DOI: 10.25592/uhhfdm.13410
title: Single mutation protein structure pairs extracted from the PDB with MicroMiner

description: This page provides the single mutation data extracted with MicroMiner from the PDB. The data contains amino acid pairs in protein structures from the PDB, exemplifying single mutations’ local structural changes for single chains and pairs for protein–protein interfaces. Mutations to non-standard residues are also provided.<br> See the MicroMiner publication for details: <em>Sieg, J.; Rarey, M. Searching similar local 3D micro-environments in protein structure databases with MicroMiner, 2023 (accepted in Briefings in Bioinformatics)</em> <strong>Data content:</strong> <strong>pdb_all_monomer.tsv</strong> all single mutations in monomer/single chains 255853767 pairs/lines 15GB <strong>filtered_single_mutations_pdb_monomer.tsv</strong> redundancy and similarity filtered pdb_all_monomer.tsv 4868765 pairs/lines 324MB <strong>single_mutations_pdb_monomer_non_standard_aa.tsv</strong> only single mutations containing non-standard in monomer/single chains 350969 pairs/lines 21MB <strong>pdb_all_ppi.tsv</strong> all single mutations at PPIs 45752145 pairs/lines 2.7GB <strong>filtered_single_mutations_pdb_ppi.tsv</strong> redundancy and similarity filtered pdb_all_ppi.tsv 799130 pairs/lines 54MB <strong>single_mutations_pdb_ppi_non_standard_aa.tsv</strong> only single mutations containing non-standard residues at PPIs 114671 pairs/lines 6.9MB A row in the TSV files describes the residue position of the single mutation in the wild-type (query) and mutant (hit). Multiple local structural and sequential similarity measures are provided, computed from the residue 3D micro-environments. The column fullSeqId contains the global sequence similarity. The first two rows of a TSV file look this: <pre><code class="language-bash">queryName queryChain queryAA queryPos hitName hitChain hitAA hitPos siteIdentity siteBackBoneRMSD siteAllAtomRMSD nofSiteResidues alignmentLDDT fullSeqId 10GS A CYS 47 2J9H A ALA 48 0.938 0.223 0.431 16.0 0.996 0.976 0.976</code></pre> <em>queryName</em>: query PDB-ID <em>queryChain</em>: query chain ID <em>queryAA</em>: query amino acid type (three letter code) <em>queryPos</em>: query sequence position of the amino acid residue <em>hitName</em>: hit PDB-ID <em>hitChain</em>: hit chain ID <em>hitAA</em>: hit amino acid type (three letter code) <em>hitPos</em>: hit sequence position of the amino acid residue <em>siteIdentity</em>: sequence identity of the aligned micro-environments <em>siteBackBoneRMSD</em>: Calpha-RMSD of the aligned micro-environments <em>siteAllAtomRMSD</em>: all-atom-RMSD of the aligned micro-environments <em>nofSiteResidues</em>: number of residues in the micro-environments <em>alignmentLDDT</em>: mean LDDT score of all residues in the aligned micro-environments <em>fullSeqId</em>: global sequence identity of the query chain and hit chain (as specified by the chain IDs) <pre><code>This work was supported by the German Federal Ministry of Education and Research as part of de.NBI [grant number 031L0105] and protP.S.I. [grant number 031B0405B].</code></pre>
DOI: 10.5281/zenodo.8399469
title: Macroevolutionary Origins of Comparative Development

description: <strong>Replication package for "Macroevolutionary Origins of Comparative Development" by Ideen A. Riahi, 2023. </strong>
DOI: 10.5281/zenodo.8399470
title: Macroevolutionary Origins of Comparative Development

description: <strong>Replication package for "Macroevolutionary Origins of Comparative Development" by Ideen A. Riahi, 2023. </strong>