cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3731517
title: Raw diffraction data for structure of SARS-CoV-2 main protease with PCM-0102432 (ID: mpro-x1392 / PDB: 5RFT)

description: Raw diffraction data for mpro-x1392 / PDB ID 5RFT (see: https://www.ebi.ac.uk/pdbe/entry/pdb/5RFT) - SARS-CoV-2 main protease in complex with PCM-0102432 (SMILES:ClCC(=O)N1CC(c2ccccc2)c3ccccc3C1) collected as part of an XChem crystallographic fragment screening campaign on beamline i04-1 at Diamond Light Source. The deposited structure was automatically processed with standard Diamond tools and PanDDA, however the raw data are being made available to allow reanalysis by any interested party. For more details see: https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem.html
DOI: 10.6073/pasta/9eb31b2e15146e6a71f3fea8d3724aaa
title: Mohonk Preserve Amphibian and Water Quality Monitoring Dataset at 11 Vernal Pools from 1931-Present

description: "The Mohonk Preserve's Daniel Smiley Research Center has been monitoring species occupancy, reproductive success, and water quality of 11 vernal pools (Ski Loop, Bonticou, Terrace, Long Woodland Pool, Long Woodland Swamp, Oakwood, Sleepy Hollow, Hermits, North Mud Pond, Canaan, and Talus) on the Preserve each spring from April 1931 to May 2019 (present). This project aims to document changes in the reproductive behavior and phenology of amphibians and allow research access to historical, longitudinal records. The dataset is a paired record of amphibian occurence with environmental indicators spanning nearly 90 years of data collection. The dataset includes environmental conditions for the 730 sampling events associated with the species occurences with complete coverage air temperature and precipitation records and partial coverage for a variety of other weather and water quality measures. Species occurence data collection has included species identification and counts of live and dead adults, mated pairs, spermatophores, egg masses, juveniles, and tadpoles counts as well as a record of the level of frog calling. Weather conditions including precipitation, sky and wind codes; and water quality measurements including water temperature, pH, and depth. Collection of data was sporadic from 1931 - 1991 but has been collected consistently from 1991 to present. We also began monitoring dissolved oxygen, nitrate concentrations, and conductivity of the vernal pools using a YSI Sonde Professional Plus Instrument and turbidity using a turbidity tube in February 2018. The data collection is ongoing, as are digitization efforts, and the data package will receive periodic updates."
DOI: 10.15468/ncrffk
title: Genetic and morphologic identities of hydrozoans (Cnidaria, Hydrozoa) from reef patches of Santa Marta, Colombian Caribbean

description: This dataset contains the digitized treatments in Plazi based on the original journal article Torres-Rodríguez, Javier, Ortiz-Oyola, Daniel, Puentes-Sayo, Alejandra, Lecompte, Orlando P., Jauregui, Aminta (2020): Genetic and morphologic identities of hydrozoans (Cnidaria, Hydrozoa) from reef patches of Santa Marta, Colombian Caribbean. Zootaxa 4758 (1): 127-140, DOI: https://doi.org/10.11646/zootaxa.4758.1.5
DOI: 10.6084/m9.figshare.3761562.v1434
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.15468/ex7uxv
title: Global Register of Introduced and Invasive Species - Montserrat

description: The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified checklists of introduced (alien) and invasive alien species at the country, territory, and associated island level. The primary intention of GRIIS is to provide checklists for countries, islands and soon also for protected areas. Checklists are living entities, especially for biological invasions given the growing nature of the problem. GRIIS checklists are based on a published methodology and supported by the Integrated Publishing Tool that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 which is on-going, aims to achieve global coverage including non-party countries and all overseas territories of countries e.g. Netherlands, France and United Kingdom. Species belonging to all Kingdoms are covered as well as occurring in all environment/systems. Country/ Territory/ Island checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records as well as those under review are presented on the online GRIIS website (www.griis.org) in addition to being published through the GBIF IPT This annotated checklist is of introduced (alien) and invasive alien species known to occur in Montserrat and overseas territory of the United Kingdom
DOI: 10.5281/zenodo.3731520
title: Raw diffraction data for structure of SARS-CoV-2 main protease with PCM-0102121 (ID: mpro-x1402 / PDB: 5RFU)

description: Raw diffraction data for mpro-x1402 / PDB ID 5RFU (see: https://www.ebi.ac.uk/pdbe/entry/pdb/5RFU) - SARS-CoV-2 main protease in complex with PCM-0102121 (SMILES:ClCC(=O)N1CCN(CC1)S(=O)(=O)c2ccc(Cl)s2) collected as part of an XChem crystallographic fragment screening campaign on beamline i04-1 at Diamond Light Source. The deposited structure was automatically processed with standard Diamond tools and PanDDA, however the raw data are being made available to allow reanalysis by any interested party. For more details see: https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem.html
DOI: 10.5281/zenodo.3731521
title: Raw diffraction data for structure of SARS-CoV-2 main protease with PCM-0102121 (ID: mpro-x1402 / PDB: 5RFU)

description: Raw diffraction data for mpro-x1402 / PDB ID 5RFU (see: https://www.ebi.ac.uk/pdbe/entry/pdb/5RFU) - SARS-CoV-2 main protease in complex with PCM-0102121 (SMILES:ClCC(=O)N1CCN(CC1)S(=O)(=O)c2ccc(Cl)s2) collected as part of an XChem crystallographic fragment screening campaign on beamline i04-1 at Diamond Light Source. The deposited structure was automatically processed with standard Diamond tools and PanDDA, however the raw data are being made available to allow reanalysis by any interested party. For more details see: https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem.html
DOI: 10.21227/sj8m-tj95
title: Aerial Lidar Dataset of an Indoor Stockpile Warehouse

description: Dataset of rosbags collected during autonomous drone flight inside a warehouse of stockpiles. PCD files created using reconstruction method proposed by article
DOI: 10.25573/serc.12043335
title: Dataset: Influence of Wind-Driven Inundation and Coastal Geomorphology on Sedimentation in Two Microtidal Marshes, Pamlico River Estuary, NC

description: Marsh sediment accumulation is predominately a combination of in situ organic accumulation and mineral sediment input during inundation. Within the Pamlico River Estuary (PRE), marsh inundation is dependent upon event (e.g., storms) and seasonal wind patterns due to minimal astronomical tides (&lt;10 cm). A better understanding of the processes controlling sediment deposition and, ultimately, marsh accretion is needed to forecast marsh sustainability with changing land usage, climate, and sea level rise. This study examines marsh topography, inundation depth, duration of inundation, and wind velocity to identify relationships between short-term deposition (tile-based) and long-term accumulation (<sup>210</sup>Pb and <sup>137</sup>Cs) recorded within and adjacent to the PRE. The results of this study indicate (1) similar sedimentation patterns between the interior marsh and shore-side marsh at different sites regardless of elevation, (2) increased sedimentation (one to two orders of magnitude, 0.04-4.54 g m<sup>-2</sup> day<sup>-1</sup>) within the interior marsh when the water levels exceeded the adjacent topography (e.g., storm berm), and (3) that short-term sea level changes can have direct effects on sediment delivery to interior marshes in wind-driven estuarine systems.
DOI: 10.25573/serc.12043335.v1
title: Dataset: Influence of Wind-Driven Inundation and Coastal Geomorphology on Sedimentation in Two Microtidal Marshes, Pamlico River Estuary, NC

description: Marsh sediment accumulation is predominately a combination of in situ organic accumulation and mineral sediment input during inundation. Within the Pamlico River Estuary (PRE), marsh inundation is dependent upon event (e.g., storms) and seasonal wind patterns due to minimal astronomical tides (&lt;10 cm). A better understanding of the processes controlling sediment deposition and, ultimately, marsh accretion is needed to forecast marsh sustainability with changing land usage, climate, and sea level rise. This study examines marsh topography, inundation depth, duration of inundation, and wind velocity to identify relationships between short-term deposition (tile-based) and long-term accumulation (<sup>210</sup>Pb and <sup>137</sup>Cs) recorded within and adjacent to the PRE. The results of this study indicate (1) similar sedimentation patterns between the interior marsh and shore-side marsh at different sites regardless of elevation, (2) increased sedimentation (one to two orders of magnitude, 0.04-4.54 g m<sup>-2</sup> day<sup>-1</sup>) within the interior marsh when the water levels exceeded the adjacent topography (e.g., storm berm), and (3) that short-term sea level changes can have direct effects on sediment delivery to interior marshes in wind-driven estuarine systems.
DOI: 10.5281/zenodo.3731768
title: Protein Graphs Dataset from PDB

description: This dataset contains the protein graphs constructed from PDB, the Protein Data Bank (www.rcsb.org/pdb), used in the paper: Nilothpal Talukder and <strong>Mohammed J. Zaki</strong>. <strong>A distributed approach for graph mining in massive networks.</strong> <em>Data Mining and Knowledge Discovery: Special Issue on ECML/PKDD 2016 Journal Track Papers</em>, 30(5):1024–1052, 2016. URL: http://link.springer.com/article/10.1007/s10618-016-0466-x. The format of graphs is as follows: t # GID v VID VLABEL e VID1 VID2 ELABEL where GID is a graph identifier (integer) VID is a vertex identifier (integer) with VLABEL its vertex label (integer) VID1 VID2 denotes an edge between the two vertices, with ELABEL the edge label (integer)
description: {"references": ["Nilothpal Talukder and\u00a0Mohammed J. Zaki.\u00a0A distributed approach for graph mining in massive networks.\u00a0Data Mining and Knowledge Discovery: Special Issue on ECML/PKDD 2016 Journal Track Papers, 30(5):1024\u20131052, 2016. URL:\u00a0http://link.springer.com/article/10.1007/s10618-016-0466-x."]}
DOI: 10.5281/zenodo.3731769
title: Protein Graphs Dataset from PDB

description: This dataset contains the protein graphs constructed from PDB, the Protein Data Bank (www.rcsb.org/pdb), used in the paper: Nilothpal Talukder and <strong>Mohammed J. Zaki</strong>. <strong>A distributed approach for graph mining in massive networks.</strong> <em>Data Mining and Knowledge Discovery: Special Issue on ECML/PKDD 2016 Journal Track Papers</em>, 30(5):1024–1052, 2016. URL: http://link.springer.com/article/10.1007/s10618-016-0466-x. The format of graphs is as follows: t # GID v VID VLABEL e VID1 VID2 ELABEL where GID is a graph identifier (integer) VID is a vertex identifier (integer) with VLABEL its vertex label (integer) VID1 VID2 denotes an edge between the two vertices, with ELABEL the edge label (integer)
description: {"references": ["Nilothpal Talukder and\u00a0Mohammed J. Zaki.\u00a0A distributed approach for graph mining in massive networks.\u00a0Data Mining and Knowledge Discovery: Special Issue on ECML/PKDD 2016 Journal Track Papers, 30(5):1024\u20131052, 2016. URL:\u00a0http://link.springer.com/article/10.1007/s10618-016-0466-x."]}
DOI: 10.21227/b814-8b80
title: Process Industrial IoT data

description: IoT data from a semi-conductor production line, which contains 589 production monitoring points (i.e. regarded as features) and 1963 data records.
DOI: 10.21227/rbz3-x873
title: Process Industrial IoT data

description: IoT data from a semi-conductor production line, which contains 589 production monitoring points (i.e. regarded as features) and 1963 data records.
DOI: 10.5281/zenodo.3731786
title: Data and analyses related to Pound et al. 2020 "Temperature affects susceptibility of intertidal limpets to bird predation" Journal of Experimental Biology

description: Data and analyses for the publication "Temperature affects susceptibility of intertidal limpets to bird predation". Rachel J. Pound, Luke P. Miller, Felicia A. King, Jennifer L. Burnaford. Journal of Experimental Biology 2020 : jeb.213595 doi: 10.1242/jeb.213595
DOI: 10.5281/zenodo.3731787
title: Data and analyses related to Pound et al. 2020 "Temperature affects susceptibility of intertidal limpets to bird predation" Journal of Experimental Biology

description: Data and analyses for the publication "Temperature affects susceptibility of intertidal limpets to bird predation". Rachel J. Pound, Luke P. Miller, Felicia A. King, Jennifer L. Burnaford. Journal of Experimental Biology 2020 : jeb.213595 doi: 10.1242/jeb.213595
DOI: 10.5281/zenodo.3731789
title: An Evaluation of Citizen Science Smartphone Apps for Inland Water Quality Assessment

description: To support the paper with the above title. This paper presents a field study of the HydroColor (HC) and EyeOnWater (EOW) smartphone Apps to evaluate water quality for inland waters in Eastern Australia. The file here contains the raw data upon which the analysis is based. It includes detailed measurements at 32 sites, covering inland waters with a large range in sediment and algal concentrations.
description: Refer to paper (title above) for full details of data collection and analysis.
DOI: 10.5281/zenodo.3724831
title: RosettaAntibody generated models for a dataset of 49 antibody-Fv structures

description: <strong>Structures of antibody-Fv domains computationally generated by RosettaAntibody based on the protocol of </strong>Weitzner, Jeliazkov, Lyskov et al.<strong> (Nature Protocols 12, 401–416, 2017). There are 49 antibody targets, with about 2800 decoy structures provided per antibody. A table is also provided with the H3-loop rmsd of each structure from the experimental crystal structure.</strong> <strong>These structures can be used to evaluate whether a score function can identify the near-native structures from the pool of decoys. These structures can also be used for comparison with other sets of structures generated by other antibody structure prediction programs.</strong> <strong>The research study on this set is unpublished and a manuscript is under preparation. Please cite Jeliazkov, Frick, Zhou & Gray, “Robustification of RosettaAntibody and Rosetta SnugDock,” in preparation, 2020.</strong> <strong>The homology modeling stage of RosettaAntibody was run with stringent homolog exclusion settings, excluding CDR templates of over 95% identity and FR templates of over 90% identity. The H3 modeling stage was run as described by Weitzner, Jeliazkov, Lyskov et al. (Nature Protocols 12, 401–416, 2017). </strong> <strong>The set of 49 antibody-Fv domains was originally compiled by Marze et al. (Protein Eng. Des. Sel. 29(10), 409-418, 2016). The dataset was first used to evaluate CDR-H3 loop rmsds in Weitzner and Gray (J. Immunology 198(1):505-515, 2017).</strong> <strong>The dataset can be extracted on a linux interface using: </strong> <strong> tar -xvzf decoys_rosettaantibody_20200323.tar.gz </strong> <strong>When extracted the output comprises RosettaAntibody generated models for 49 antibodies in the format:</strong> <strong>&lt;Antibody pdb id&gt; / model-&lt;id 1&gt;.relaxed_&lt;id 2&gt;.pdb.gz</strong> <strong>The Rosetta "ref2015" scores (ref2015_score) and rmsd of the H3 loop (h3_rmsd) for every model (model) is provided in model_scores_and_rmsds.txt . RMSDs are calculated with respect to the corresponding crystal structure (pdb id) over all heavy atoms in the h3 loop (93–102 in Chothia numbering) after superposition of the framework residues. ID 1 comes from the homology model source (lower is better). ID 2 indicates the loop model.</strong> <strong>The decoy PDB files contain additional metrics following the ATOM records such as VH–VL relative orientation metrics (from Marze et al.) and per-residue Rosetta scores. Caveat: the “RMS” values reported within the decoy files were calculated against the input homology model and not the crystal structures (whereas the model_rmsds.txt file contains the H3 rmsds w.r.t. crystal).</strong>
description: {"references": ["Protein Eng Des Sel. 2016 Oct; 29(10): 409\u2013418.", "doi: https://doi.org/10.1101/2020.02.09.940254"]}
DOI: 10.5281/zenodo.3724832
title: RosettaAntibody generated models for a dataset of 49 antibody-Fv structures

description: <strong>Structures of antibody-Fv domains computationally generated by RosettaAntibody based on the protocol of </strong>Weitzner, Jeliazkov, Lyskov et al.<strong> (Nature Protocols 12, 401–416, 2017). There are 49 antibody targets, with about 2800 decoy structures provided per antibody. A table is also provided with the H3-loop rmsd of each structure from the experimental crystal structure.</strong> <strong>These structures can be used to evaluate whether a score function can identify the near-native structures from the pool of decoys. These structures can also be used for comparison with other sets of structures generated by other antibody structure prediction programs.</strong> <strong>The research study on this set is unpublished and a manuscript is under preparation. Please cite Jeliazkov, Frick, Zhou & Gray, “Robustification of RosettaAntibody and Rosetta SnugDock,” in preparation, 2020.</strong> <strong>The homology modeling stage of RosettaAntibody was run with stringent homolog exclusion settings, excluding CDR templates of over 95% identity and FR templates of over 90% identity. The H3 modeling stage was run as described by Weitzner, Jeliazkov, Lyskov et al. (Nature Protocols 12, 401–416, 2017). </strong> <strong>The set of 49 antibody-Fv domains was originally compiled by Marze et al. (Protein Eng. Des. Sel. 29(10), 409-418, 2016). The dataset was first used to evaluate CDR-H3 loop rmsds in Weitzner and Gray (J. Immunology 198(1):505-515, 2017).</strong> <strong>The dataset can be extracted on a linux interface using: </strong> <strong> tar -xvzf decoys_rosettaantibody_20200323.tar.gz </strong> <strong>When extracted the output comprises RosettaAntibody generated models for 49 antibodies in the format:</strong> <strong>&lt;Antibody pdb id&gt; / model-&lt;id 1&gt;.relaxed_&lt;id 2&gt;.pdb.gz</strong> <strong>The Rosetta "ref2015" scores (ref2015_score) and rmsd of the H3 loop (h3_rmsd) for every model (model) is provided in model_scores_and_rmsds.txt . RMSDs are calculated with respect to the corresponding crystal structure (pdb id) over all heavy atoms in the h3 loop (93–102 in Chothia numbering) after superposition of the framework residues. ID 1 comes from the homology model source (lower is better). ID 2 indicates the loop model.</strong> <strong>The decoy PDB files contain additional metrics following the ATOM records such as VH–VL relative orientation metrics (from Marze et al.) and per-residue Rosetta scores. Caveat: the “RMS” values reported within the decoy files were calculated against the input homology model and not the crystal structures (whereas the model_rmsds.txt file contains the H3 rmsds w.r.t. crystal).</strong>
description: {"references": ["Protein Eng Des Sel. 2016 Oct; 29(10): 409\u2013418.", "doi: https://doi.org/10.1101/2020.02.09.940254"]}
DOI: 10.17632/7hycyc59tb.2
title: Data for: Toddlers’ Word Learning through Overhearing: Others’ Attention Matters

description: Data for article Toddler's word learning through overhearing: Joint attention matters. Data for target selection is binary (1 = target selected, 0 = non-target selected).
DOI: 10.14469/hpc/7076
title: Michael 1,4 addition, Reactant wB97XD/Def2-TZVPP with one formyl group replaced by methoxy G = -516.742828

description: Gaussian Calculation
DOI: 10.5281/zenodo.3731318
title: Raw diffraction data for structure of SARS-CoV-2 main protease with Z979145504 (ID: mpro-x1235 / PDB: 5RFC)

description: Raw diffraction data for mpro-x1235 / PDB ID 5RFC (see: https://www.ebi.ac.uk/pdbe/entry/pdb/5RFC) - SARS-CoV-2 main protease in complex with Z979145504 (SMILES:COC(=O)NC=1SC(C)=NC1C=2C=CC=CC2) collected as part of an XChem crystallographic fragment screening campaign on beamline i04-1 at Diamond Light Source. The deposited structure was automatically processed with standard Diamond tools and PanDDA, however the raw data are being made available to allow reanalysis by any interested party. For more details see: https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem.html
DOI: 10.5281/zenodo.3731317
title: Raw diffraction data for structure of SARS-CoV-2 main protease with Z979145504 (ID: mpro-x1235 / PDB: 5RFC)

description: Raw diffraction data for mpro-x1235 / PDB ID 5RFC (see: https://www.ebi.ac.uk/pdbe/entry/pdb/5RFC) - SARS-CoV-2 main protease in complex with Z979145504 (SMILES:COC(=O)NC=1SC(C)=NC1C=2C=CC=CC2) collected as part of an XChem crystallographic fragment screening campaign on beamline i04-1 at Diamond Light Source. The deposited structure was automatically processed with standard Diamond tools and PanDDA, however the raw data are being made available to allow reanalysis by any interested party. For more details see: https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem.html
DOI: 10.14469/hpc/7077
title: Michael 1,4 addition, Reactant wB97XD/Def2-TZVPP with one formyl group replaced by cyano G = -494.491432

description: Gaussian Calculation
DOI: 10.5281/zenodo.3706875
title: Code and data sets for "DeepLC can predict retention times for peptides that carry as-yet unseen modifications"

description: Code used to prepare the data sets, calibrate retention times, generate DeepLC models, make predictions, and generate the figures. See README.md for more information on how to use these files and reproduce the results reported in the manuscript titled "DeepLC can predict retention times for peptides that carry as-yet unseen modifications".
DOI: 10.14469/hpc/7078
title: Michael 1,4 addition, TS2 wB97XD/Def2-TZVPP with one formyl group replaced by nitro IRC

description: Gaussian Calculation
DOI: 10.5281/zenodo.3731903
title: Earthquake Data around the Palu-Koro fault

description: This earthquake data is used in my paper about stress on the Palu-Koro fault.
DOI: 10.5281/zenodo.3731899
title: IO Islamic 3062. Tawârîkh-i-Râjahâi-Nâgpûr, Annals of the Marattah Râjahs of Nâgpûr

description: IO Islamic 3062. Tawârîkh-i-Râjahâi-Nâgpûr, Annals of the Marattah Râjahs of Nâgpûr
DOI: 10.5281/zenodo.3731898
title: IO Islamic 3062. Tawârîkh-i-Râjahâi-Nâgpûr, Annals of the Marattah Râjahs of Nâgpûr

description: IO Islamic 3062. Tawârîkh-i-Râjahâi-Nâgpûr, Annals of the Marattah Râjahs of Nâgpûr
DOI: 10.5281/zenodo.3731901
title: IO Islamic 2895. Historical documents Relating to the Marattah Power in India

description: IO Islamic 2895. Historical documents Relating to the Marattah Power in India
DOI: 10.5281/zenodo.3731900
title: IO Islamic 2895. Historical documents Relating to the Marattah Power in India

description: IO Islamic 2895. Historical documents Relating to the Marattah Power in India