cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc1zwxj9
title: CCDC 1844082: Experimental Crystal Structure Determination

description: Related Article: Giada Truccolo, Zeno Tessari, Jacopo Tessarolo, Silvio Quici, Lidia Armelao, Marzio Rancan|2018|Dalton Trans.|47|12079|doi:10.1039/C8DT02693A
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.cc1zxwzr
title: CCDC 1845026: Experimental Crystal Structure Determination

description: Related Article: Pargol Daneshmand, Leena Pinon, Frank Schaper|2018|Dalton Trans.|47|10147|doi:10.1039/C8DT02140F
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.cc1zxx0t
title: CCDC 1845027: Experimental Crystal Structure Determination

description: Related Article: Pargol Daneshmand, Leena Pinon, Frank Schaper|2018|Dalton Trans.|47|10147|doi:10.1039/C8DT02140F
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.cc1zxx4y
title: CCDC 1845031: Experimental Crystal Structure Determination

description: Related Article: Pargol Daneshmand, Leena Pinon, Frank Schaper|2018|Dalton Trans.|47|10147|doi:10.1039/C8DT02140F
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.cc1zxx2w
title: CCDC 1845029: Experimental Crystal Structure Determination

description: Related Article: Pargol Daneshmand, Leena Pinon, Frank Schaper|2018|Dalton Trans.|47|10147|doi:10.1039/C8DT02140F
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.cc1zxx71
title: CCDC 1845034: Experimental Crystal Structure Determination

description: Related Article: Pargol Daneshmand, Leena Pinon, Frank Schaper|2018|Dalton Trans.|47|10147|doi:10.1039/C8DT02140F
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.cc1zjy7p
title: CCDC 1833533: Experimental Crystal Structure Determination

description: Related Article: Samim Khan, Santiago Herrero, Rodrigo González-Prieto, Michael. G. B. Drew, Snehasis Banerjee, Shouvik Chattopadhyay|2018|New J.Chem.|42|13512|doi:10.1039/C8NJ02612B
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.cc1zyn2n
title: CCDC 1845742: Experimental Crystal Structure Determination

description: Related Article: Roxana Lorenz, Elisabeth Kaifer, Hubert Wadepohl, Hans-Jörg Himmel|2018|Dalton Trans.|47|11016|doi:10.1039/C8DT02176G
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.cc1zyn1m
title: CCDC 1845741: Experimental Crystal Structure Determination

description: Related Article: Roxana Lorenz, Elisabeth Kaifer, Hubert Wadepohl, Hans-Jörg Himmel|2018|Dalton Trans.|47|11016|doi:10.1039/C8DT02176G
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.cc25mmxc
title: CCDC 2014873: Experimental Crystal Structure Determination

description: Related Article: Aline Chevalier, Artem Osypenko, Jean-Marie Lehn, Daniel Meyer|2020|Chemical Science|11|11468|doi:10.1039/D0SC04098C
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.cc27clgp
title: CCDC 2066722: Experimental Crystal Structure Determination

description: Related Article: Bharti Mohan, Mukesh Choudhary|2021|J.Mol.Struct.|1246|131246|doi:10.1016/j.molstruc.2021.131246
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.cc25d26w
title: CCDC 2007597: Experimental Crystal Structure Determination

description: Related Article: Sabarni Dutta, Tanmoy kumar Ghosh, Prithwish Mahapatra, Ashutosh Ghosh|2020|Inorg.Chem.|59|14989|doi:10.1021/acs.inorgchem.0c01733
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.7193812
title: FrenchPiezo: the French mainland groundwater level multivariate time series

description: <strong>FrenchPiezo </strong>is the French mainland multivariate time series dataset of groundwater levels (a.k.a piezometric levels) across the French mainland. The dataset contains 1026 multivariate time series, each made of 3 dimensions which are: the piezometric level (<strong>p</strong>), the precipitation (<strong>t</strong><strong>p</strong>), the evapotranspiration (<strong>e</strong>). Each time series is identified by a code (<strong>bss</strong>) which is the identifier of the piezometer used to measure the piezometric level. The measurements are sampled daily from January 2015 to January 2021, corresponding to 2221 days. The piezometric levels are collected from Hub'Eau, the French free API for accessing water data. The climate data <strong>tp </strong>and <strong>e </strong>are collected from the Copernicus ERA5 archive using their free API. These data are in the file <em>dataset_2015_2021.csv</em><strong> </strong>in which time series with more than 50 missing values have been dropped. The file <em>dataset_2015_2021_nomissing_linear.csv</em> is the same dataset in which missing values have been imputed using linear interpolation. In addition to the climate data, information about the nature of the soil where each time series is collected are downloaded from <em>BDLISA</em> and are given in the file <em>dataset_stations.csv </em>. BDLISA classifies soils as hydrologic entities (EH), characterized by a set of attributes described here: More information on how we created the dataset, the scripts used to collect the data, and some experiments on forecasting the future values of groundwater levels using global and local foresting methods can be found on our GitHub page.
DOI: 10.5281/zenodo.7193811
title: FrenchPiezo: the French mainland groundwater level multivariate time series

description: <strong>FrenchPiezo </strong>is the French mainland multivariate time series dataset of groundwater levels (a.k.a piezometric levels) across the French mainland. The dataset contains 1026 multivariate time series, each made of 3 dimensions which are: the piezometric level (<strong>p</strong>), the precipitation (<strong>t</strong><strong>p</strong>), the evapotranspiration (<strong>e</strong>). Each time series is identified by a code (<strong>bss</strong>) which is the identifier of the piezometer used to measure the piezometric level. The measurements are sampled daily from January 2015 to January 2021, corresponding to 2221 days. The piezometric levels are collected from Hub'Eau, the French free API for accessing water data. The climate data <strong>tp </strong>and <strong>e </strong>are collected from the Copernicus ERA5 archive using their free API. These data are in the file <em>dataset_2015_2021.csv</em><strong> </strong>in which time series with more than 50 missing values have been dropped. The file <em>dataset_2015_2021_nomissing_linear.csv</em> is the same dataset in which missing values have been imputed using linear interpolation. In addition to the climate data, information about the nature of the soil where each time series is collected are downloaded from <em>BDLISA</em> and are given in the file <em>dataset_stations.csv </em>. BDLISA classifies soils as hydrologic entities (EH), characterized by a set of attributes described here: More information on how we created the dataset, the scripts used to collect the data, and some experiments on forecasting the future values of groundwater levels using global and local foresting methods can be found on our GitHub page.
DOI: 10.5281/zenodo.7194946
title: gymnarchus_niloticus_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7194945
title: gymnarchus_niloticus_zanfona_1.fasta.gz

description: .
DOI: 10.13020/przg-dp88
title: Data related to Genetic diversity fuels gene discovery for tobacco and alcohol use

description: We conducted a meta-analysis of 60 genome wide association studies (GWAS) in up to 3.4 million participants from four major ancestries on nicotine and substance use. Specifically, we targeted different stages and kinds of substance use from initiation (smoking initiation and age of regular smoking initiation) to regular use (drinks per week and cigarettes per day) to cessation (smoking cessation). Here we present the final set of filtered meta-analysis summary statistics and polygenic risk score weights excluding 23andMe. As per requirement and to ease dissemination of our results for other scientific endeavors, we are sharing our results here to facilitate downloading.
description: Files include summary statistics for associations with each phenotype: Drinks per week, Cigarettes per day, Smoking initiation, Smoking cessation, and Age of initiation. Details for each file can be found in the readme file or in the article's Supplementary Text.
DOI: 10.5281/zenodo.5225650
title: Copilot CWE Scenarios Dataset

description: The dataset and source code and result generation framework used in the paper 'Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions'. It includes 89 different scenarios.
DOI: 10.5281/zenodo.5225651
title: Copilot CWE Scenarios Dataset

description: The dataset and source code and result generation framework used in the paper 'Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions'. It includes 89 different scenarios.
DOI: 10.5281/zenodo.7194967
title: leptatherina_wallacei_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7194966
title: leptatherina_wallacei_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7126163
title: Remote internal wave forcing of regional ocean simulations near the U.S. West Coast

description: This dataset contains data from ROMS simulations near the U.S. West Coast with realistic atmospheric forcing, tidal forcing and remote internal wave forcing. FS800b has remote internal wave forcing while FS800a does not have remote internal wave forcing at the open boundaries. The ROMS simulations have 4-km horizontal resolution and 60 sigma-layers. All data is along the local x- and y- axis of the rotated C-grid. Data is stored in netcdf format. We also include the altimeter dataset (see Buijsman et al., 2020; doi: 10.1016/j.ocemod.2020.101656) used in validating the semidiurnal internal tides.
DOI: 10.5281/zenodo.7192649
title: Remote internal wave forcing of regional ocean simulations near the U.S. West Coast

description: This dataset contains data from ROMS simulations near the U.S. West Coast with realistic atmospheric forcing, tidal forcing and remote internal wave forcing. FS800b has remote internal wave forcing while FS800a does not have remote internal wave forcing at the open boundaries. The ROMS simulations have 4-km horizontal resolution and 60 sigma-layers. All data is along the local x- and y- axis of the rotated C-grid. Data is stored in netcdf format. We also include the altimeter dataset (see Buijsman et al., 2020; doi: 10.1016/j.ocemod.2020.101656) used in validating the semidiurnal internal tides.
DOI: 10.5281/zenodo.7194987
title: wirenia_argentea_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7194986
title: wirenia_argentea_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.20304078
title: montevideo_sewage_AMR

description: Scripts and datasest to reproduce paper figures and analyses.
DOI: 10.6084/m9.figshare.20304078.v2
title: montevideo_sewage_AMR

description: Scripts and datasest to reproduce paper figures and analyses.
DOI: 10.6084/m9.figshare.20304078.v1
title: montevideo_sewage_AMR

description: Scripts and datasest to reproduce paper figures and analyses.
DOI: 10.6069/nefv-6k43
title: Dynamic acylome reveals metabolite driven modifications in Syntrophomonas wolfei

description: Syntrophomonas wolfei is an anaerobic syntrophic microbe that degrades short-chain fatty acids to acetate, hydrogen, and/or formate. This thermodynamically unfavorable process proceeds through a series of reactive acyl-Coenzyme A species (RACS). In other prokaryotic and eukaryotic systems, the production of intrinsically reactive metabolites correlates with acyl-lysine modifications, which have been shown to play a significant role in metabolic processes. Analogous studies with syntrophic bacteria, however, are relatively unexplored and we hypothesize that highly abundant acylations could exist in S. wolfei proteins, corresponding to the RACS derived from degrading fatty acids. Here, by mass spectrometry-based proteomics (LC-MS/MS), we characterize and compare acylome profiles of two S. wolfei subspecies grown on different carbon substrates. Because modified S. wolfei proteins are sufficiently abundant to analyze post-translational modifications (PTMs) without antibody enrichment, we could identify types of acylations comprehensively, observing six types (acetyl-, butyryl-, 3-hydroxybutyryl-, crotonyl-, valeryl-, and hexanyl-lysine), two of which have not been reported in any system previously. All of the acyl-PTMs identified correspond directly to RACS in fatty acid degradation pathways. A total of 369 sites of modification were identified on 237 proteins. Structural studies and in vitro acylation assays of a heavily modified enzyme, acetyl-CoA transferase, provided insight on the potential impact of these acyl-protein modifications. The extensive changes in acylation-type, abundance, and modification sites with carbon substrate suggest that protein acylation by RACS may be an important regulator of syntrophy.
DOI: 10.5281/zenodo.7120941
title: 3D tissue cytometry analysis files for, "An atlas of healthy and injured cell states and niches in the human kidney"

description: This deposit contains the supporting records of analysis for 3D cytometry presented in, "An atlas of healthy and injured cell states and niches in the human kidney". Contents: 1) a collection of .zip files contains the 3D tissue cytometry files for tissue analyzed in the preprint doi: 10.1101/2021.07.28.454201. This collection includes the individual tissue specimens, XX-XXXX.zip, further described in detail in "Supplementary Table 2. 3D imaging and spatial transcriptomic experiments." 2) neighborhoods by specimen as indicated above and calculated by Volumetric Tissue Exploration and Analysis (VTEA) for a radius of 50 voxels(accounting for anisotropy of voxels) or ~25 um as described in the methods of the preprint, doi: 10.1101/2021.07.28.454201. 3) R environment file (.RData as a .zip file) for regenerating analysis from code at: https://github.com/KPMP/Cell-State-Atlas-2022 Contents of XX-XXXX.zip files: 1) maximum projections as used in the manuscript (all archived at kpmp.org)<br> 2) .obx and a .tif file which includes the segmented objects and associated measurements for use by VTEA (https://vtea.wiki/)<br> 3) .csv file including all the segmented objects and associated measurements<br> 4) .csv file including the neighborhood analysis results also found in the combined .zip file<br> 5) folder of ImageJ/FIJI folder which includes the expert ROIs and the pixel-wise consensus of ROIs drawn by experts used in cell classification strategy outlined in the methods<br> 6) folder of VTEA gate files and images of gating .png files used to label objects and used in cell classification strategy outlined in the methods of doi: 10.1101/2021.07.28.454201 Please address any concerns or questions to the authors listed in the deposit or manuscript, doi: 10.1101/2021.07.28.454201.
DOI: 10.5281/zenodo.7120940
title: 3D tissue cytometry analysis files for, "An atlas of healthy and injured cell states and niches in the human kidney"

description: This deposit contains the supporting records of analysis for 3D cytometry presented in, "An atlas of healthy and injured cell states and niches in the human kidney". Contents: 1) a collection of .zip files contains the 3D tissue cytometry files for tissue analyzed in the preprint doi: 10.1101/2021.07.28.454201. This collection includes the individual tissue specimens, XX-XXXX.zip, further described in detail in "Supplementary Table 2. 3D imaging and spatial transcriptomic experiments." 2) neighborhoods by specimen as indicated above and calculated by Volumetric Tissue Exploration and Analysis (VTEA) for a radius of 50 voxels(accounting for anisotropy of voxels) or ~25 um as described in the methods of the preprint, doi: 10.1101/2021.07.28.454201. 3) R environment file (.RData as a .zip file) for regenerating analysis from code at: https://github.com/KPMP/Cell-State-Atlas-2022 Contents of XX-XXXX.zip files: 1) maximum projections as used in the manuscript (all archived at kpmp.org)<br> 2) .obx and a .tif file which includes the segmented objects and associated measurements for use by VTEA (https://vtea.wiki/)<br> 3) .csv file including all the segmented objects and associated measurements<br> 4) .csv file including the neighborhood analysis results also found in the combined .zip file<br> 5) folder of ImageJ/FIJI folder which includes the expert ROIs and the pixel-wise consensus of ROIs drawn by experts used in cell classification strategy outlined in the methods<br> 6) folder of VTEA gate files and images of gating .png files used to label objects and used in cell classification strategy outlined in the methods of doi: 10.1101/2021.07.28.454201 Please address any concerns or questions to the authors listed in the deposit or manuscript, doi: 10.1101/2021.07.28.454201.
DOI: 10.14469/hpc/11431
title: TS4 from alex for C-O break, rotamer6, Def2-SVPP, 2,6-diipr-B-Ph instead of B-OMe, G = -1159.822229, DG = 14.9

description: Gaussian 16 (C01) calculation
DOI: 10.17037/data.00003114
title: Field entomology data from Ethiopian trachoma population survey and laboratory transmission experiments for Musca sorbens and Chlamydia trachomatis

description: A population-based survey of 247 households was conducted in Shashemane district, Oromia Region, Ethiopia, between April and June 2018. Households were positively selected to include at least one child aged 1–9 years, resident on the day of enumeration. These datasets contain entomology from this survey; including fly-eye contact data, fly positivity for Chlamydia trachomatis and other entomological data (fly species, sex). Experiments were also conducted in the London School of Hygiene & Tropical Medicine to investigate transmission of Chlamydia trachomatis by Musca sorbens, those data are reported here.
description: Field data: Per household, fly contacts on two children aged 2-9 years were observed for ten minutes. If children were unavailable or there were not two children aged 2-9 years, children aged &gt;9 years were observed (with a preference for the youngest), if no children were present adults were observed. Fly contact observations were made outside in a shady area, and two entomological field workers tallied fly-eye, -nose and -mouth contacts. The face was filmed (using a tripod-mounted Nikon D7200 single-lens reflex camera) for the 10-min observation period. Flies landing on individual’s faces were caught, killed, and transported on ice to our local laboratory as previously described. The observed child sat on a chair and for 15 minutes, or until 10 nets were used, flies landing on the child’s face were disturbed and caught in a sterile net. In the laboratory, flies were identified with keys as M. sorbens, M. domestica, ‘other’ (clearly another species) or ‘unknown’ (unidentifiable) using dissecting microscopes. Musca sorbens and M. domestica were sexed; flies were temporarily stored at -20˚C before transfer to a -80˚C freezer, where they were stored until DNA extraction and testing. Laboratory data: Internal and external recovery of Ct DNA was tested using six female flies (experiment 1), six male flies (experiment 2), and six males/six females (experiment 3). Musca sorbens (broad frons), colonised in 2018, were reared at the London School of Hygiene & Medicine according to previously published methods. Flies of known and uniform age were starved of food (milk/sugar) and water prior to feeding experiments. After starving, surviving flies were put into individual containers covered by a square of mesh with a small hole in the middle plugged with cotton wool. In a microbiological safety cabinet, flies were fed aliquots of Chlamydia trachomatis culture (culture lysate containing EB at approximately 1000 EB/uL) by pipette through the hole in the mesh. All samples were stored immediately in sterile tubes at -20oC. DNA extraction, PCR quantification and load estimation was performed as for the field samples.
DOI: 10.5281/zenodo.7195049
title: oenothera_biennis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7195048
title: oenothera_biennis_zanfona_1.fasta.gz

description: .