cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2c77pk
title: CCDC 2181708: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2c77ql
title: CCDC 2181709: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2c77nj
title: CCDC 2181707: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2c77lg
title: CCDC 2181705: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2c77mh
title: CCDC 2181706: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2c77kf
title: CCDC 2181704: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2c77jd
title: CCDC 2181703: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2c77gb
title: CCDC 2181701: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2c77hc
title: CCDC 2181702: Experimental Crystal Structure Determination

description: Related Article: Irina K. Goncharova, Eva A. Ulianova, Roman A. Novikov, Alexander D. Volodin, Alexander A. Korlyukov, Ashot V. Arzumanyan|2022|New J.Chem.|46|18041|doi:10.1039/D2NJ03872B
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.cc2bz7cy
title: CCDC 2174010: Experimental Crystal Structure Determination

description: Related Article: Susana Herrera, Kennett I. Rivero, Alexis Guzmán, Jonathan Cedeño, Jaroslava Miksovska, Raphael G. Raptis|2022|Dalton Trans.|51|14277|doi:10.1039/D2DT01901A
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.cc2bz7f0
title: CCDC 2174012: Experimental Crystal Structure Determination

description: Related Article: Susana Herrera, Kennett I. Rivero, Alexis Guzmán, Jonathan Cedeño, Jaroslava Miksovska, Raphael G. Raptis|2022|Dalton Trans.|51|14277|doi:10.1039/D2DT01901A
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.cc2bz7h2
title: CCDC 2174014: Experimental Crystal Structure Determination

description: Related Article: Susana Herrera, Kennett I. Rivero, Alexis Guzmán, Jonathan Cedeño, Jaroslava Miksovska, Raphael G. Raptis|2022|Dalton Trans.|51|14277|doi:10.1039/D2DT01901A
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.7102159
title: Single-cell NTT-seq datasets

description: These datasets were generated using single-cell NTT-seq. Please see the publication for a full description of methods: Stuart, Tim, Stephanie Hao, Bingjie Zhang, Levan Mekerishvili, Dan Landau, Silas Maniatis, Rahul Satija, and Ivan Raimondi. 2022. “Nanobody-Tethered Transposition Allows for Multifactorial Chromatin Profiling at Single-Cell Resolution.” <em>bioRxiv</em>. doi:10.1101/2022.03.08.483436. Associated fragment files can be found on NCBI GEO: GSE212588
description: Note that the saved objects link to fragment files stored remotely on AWS servers. This enables running analyses without needing to download the entire fragment file and link it to the object locally. However, for users running more extensive analyses (re-quantifying genomic regions, for example) we recommend downloading the fragment files to your local computer and linking them to the object. For example: ``` Fragments(obj) &lt;- NULL # remove fragment file information Fragments(obj) &lt;- CreateFragmentObject(path = , cells = colnames(obj)) # add a new fragment object ```
DOI: 10.5281/zenodo.7102158
title: Single-cell NTT-seq datasets

description: These datasets were generated using single-cell NTT-seq. Please see the publication for a full description of methods: Stuart, Tim, Stephanie Hao, Bingjie Zhang, Levan Mekerishvili, Dan Landau, Silas Maniatis, Rahul Satija, and Ivan Raimondi. 2022. “Nanobody-Tethered Transposition Allows for Multifactorial Chromatin Profiling at Single-Cell Resolution.” <em>bioRxiv</em>. doi:10.1101/2022.03.08.483436. Associated fragment files can be found on NCBI GEO: GSE212588
description: Note that the saved objects link to fragment files stored remotely on AWS servers. This enables running analyses without needing to download the entire fragment file and link it to the object locally. However, for users running more extensive analyses (re-quantifying genomic regions, for example) we recommend downloading the fragment files to your local computer and linking them to the object. For example: ``` Fragments(obj) &lt;- NULL # remove fragment file information Fragments(obj) &lt;- CreateFragmentObject(path = , cells = colnames(obj)) # add a new fragment object ```
DOI: 10.5066/f7ht2nnp
title: Historical Ice Breakup Dates for Chequamegon Bay, Lake Superior (ver. 5.0, September 2022)

description: Ice breakup dates of Chequamegon Bay, Lake Superior from 1911 to 2022 were compiled by Lori Evrard (USGS, GLSC, Lake Superior Biological Station, Ashland, WI). Ice breakup date is the day in spring when winter ice cover substantially leaves a water body. Local residents deem "ice breakup" as when the ice moves northeast of a line straight across Chequamegon Bay out from Ellis Avenue (State highway 13). Another way ice breakup was determined has been if you could drive a boat from the outlet of Fish Creek to Houghton Point. The ice may move back and forth over that line but the ice is breaking up, moving and melting from that date on. Ellis Avenue ends on a bluff (46.5925 degrees North, 90.8827 degrees West) that provides a clear view of Chequamegon Bay from Fish Creek to Houghton Point. Mrs. C. J. Hoskings recorded the dates from 1911 to 1980. Mr. LeRoy C. Margenau recorded the dates from 1981 to 1991. The Ashland Marina recorded the dates from 1992-1999 and 2001. Lori Evrard (USGS) recorded dates after 1999 except 2001. USGS converted each date to a consecutive day of the year value. The date of ice breakup will be updated annually to append that year's date.
DOI: 10.22003/xfel.eu-data-003483-00
title: High_Z detector tests
DOI: 10.6084/m9.figshare.21210554
title: Plot Samples

description: The samples of parameters used in the plots of the paper including the computed observables and the posterior predictive distributions
DOI: 10.6084/m9.figshare.21210554.v1
title: Plot Samples

description: The samples of parameters used in the plots of the paper including the computed observables and the posterior predictive distributions
DOI: 10.6084/m9.figshare.21210518
title: Sample Chains

description: All 5,800,000 samples from the direct Bayes Markov chain Monte Carlo calibration of the RMF model.
DOI: 10.6084/m9.figshare.21210518.v1
title: Sample Chains

description: All 5,800,000 samples from the direct Bayes Markov chain Monte Carlo calibration of the RMF model.
DOI: 10.25919/9fex-0b78
title: Parkes observations for project P574 semester 2022APRS_10

description: We request time to observe 260 pulsars on a regular basis in order to provide the accurate ephemerides necessary for the detection and characterisation of gamma-ray pulsars with the Fermi satellite. The main science goals are to increase the number of known gamma-ray pulsars (both radio loud and radio quiet), to determine accurate pulse profiles, and to characterise their high energy (phase-resolved) spectra. In the radio, the observations will also allow us to investigate: neutron stars and pulsar emission via detecting glitches and determining pulse timing parameters; and the ISM via measuring and monitoring dispersion measures, Faraday rotation measures, and scintillation. To date, we are (co-)authors on over 95 papers arising from the collaboration and P574 data, including four which use UWL observations. The data have contributed to the PhD theses of students from Bordeaux, Manchester, Oxford, Stanford, and Swinburne.
DOI: 10.25919/c22q-4n46
title: Parkes observations for project P1054 semester 2022APRS_21

description: With this proposal we ask time to continue our timing follow-up campaign of pulsars discovered with the MeerKAT telescope. Fourteen sources have been discovered in targeted observations of Fermi unidentified point sources, three in the Small Magellanic Cloud, 37 in Globular Clusters and 34 in a survey of the Galactic plane. A large fraction of the new discoveries are recycled pulsars (including at least one double neutron star system and several 'spider' binaries), or young pulsars. Timing observations have an essential role in exploiting the full potential of any pulsar discovery, allowing the precise measurement of rotational, astrometric and orbital parameters which, in turn, give us powerful tools to improve our understanding of the physics in extreme environments as well as of the population of neutron stars as a whole. The UWL receiver of the Parkes telescope is a sensitive, versatile instrument that is allowing us to successfully time these new sources, in the bright-end of TRAPUM discoveries. The UWL has also the unique advantage of allowing detailed studies of the eclipses of the so-called 'spider' pulsars, which make up about 1/3rd of the sources we aim at following-up with this project.
DOI: 10.5281/zenodo.7114530
title: pithecophaga_jefferyi_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.7114529
title: pithecophaga_jefferyi_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.6084/m9.figshare.21171346
title: LUAD_Bundled_Data_Supplement1

description: Bundled LUAD data - Cell Types
DOI: 10.6084/m9.figshare.21171346.v2
title: LUAD_Bundled_Data_Supplement1

description: Bundled LUAD data - Cell Types
DOI: 10.6084/m9.figshare.21171346.v1
title: LUAD_Bundled_Data_Supplement1

description: Bundled LUAD data - Cell Types
DOI: 10.6084/m9.figshare.3761562.v2353
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: 10.13012/b2idb-2467544_v1
title: ShelbyvilleZooplankton

description: Data characterize zooplankton in Shelbyville Reservoir, Illinois, United States of America. Zooplankton were sampled with a conical zooplankton net (0.5m diameter mouth) when water was deeper than 2 m and by grab sample when water was shallower. Zooplankton samples were concentrated and subsampled with a Hensen-Stempel pipette following protocols described in Detmer et al. (2019). Zooplankton were identified to the lowest feasible taxonomic unit according to Pennak (1989) and Thorp and Covich (2001) and were enumerated in a 1 mL Sedgewick-Rafter cell. Subsamples were analyzed until at least 200 individuals were enumerated from each site.were counted across for each of the three main taxonomic groups (cladocerans, copepods, and rotifers). Given the variation in zooplankton concentrations at each site, this process often lead to far more than 200 individuals being counted (x̄ = 269, min = 200, max = 487). A summary of the sample size from each site can be found in Supplementary Table S2. Abundances were corrected for volume of water filtered. For rare taxa (&lt; 20 individuals per sample), all individuals were measured for length. For abundant taxa, length measurements were collected on the first 20 organisms of each abundant taxon encountered in a subsample. Dry mass was calculated from equations for microcrustaceans, rotifers, and Chaoborus sp. (Rosen ,1981; Botrell et al., 1976; Dumont and Balvay, 1979).
DOI: 10.15482/usda.adc/1527979
title: Regional epithelial cell diversity in the small intestine of pigs

description: Single cell suspensions enriched for epithelial cells were obtained from duodenum, jejunum, and ileum of a 7.5-week-old pig and subjected to single-cell RNA sequencing (scRNA-seq). scRNA-seq was performed to provide transcriptomic profiles of epithelial cells, with 695 cells annotated into 6 cell types. Deeper interrogation of data revealed previously undescribed cells in porcine intestine, and region-specific gene expression profiles within specific cell subsets. Data herein includes a .h5seurat files of the epithelial cell subsets analyzed. Files may be used to reconstruct different analyses and perform further data query. Scripts for original data analyses are found at https://github.com/USDA-FSEPRU/scRNAseqEpSI_Pilot. Raw data are available at GEO accession GSE208613. Data are available for online query at https://singlecell.broadinstitute.org/single_cell/study/SCP1936/regional....
DOI: 10.5066/p9ulam7g
title: Wildlife mortality events in counties surrounding the Chesapeake Bay recorded in the Wildlife Health Information Sharing Partnership Event Reporting System (WHISPers) from 2000-2020

description: This data set is composed of all events in the Wildlife Health Information Sharing Partnership Event Reporting System (WHISPers) between 1/1/2000 and 12/31/2020 from counties bordering the Chesapeake Bay. Relevant fields include WHSPers ID number, estimated number of animals affected, event start and end dates, states, counties, species involved, event diagnoses, etiological category of the primary cause/diagnosis, and whether concurrent algal blooms or toxins were reported at the time of the event. Additional information from NWHC case 24171is provided including: WHISPers event ID, case number, accession numbers, state, county, collection date, species, presence or absence of liver necrosis, and cause of death.
DOI: 10.5281/zenodo.7113509
title: Cerebellum spiking data during simulated saccade control

description: This repository contains data generated by simulating the cerebellum spiking neural network for saccade motor control. Please refer to the article at https://doi.org/10.1101/2022.03.14.483471. Please check the journal of PLOS computational biology for the published version of this article. The python scripts will generate plots by going through the data folder. In order to do so, please unzip the datasets manually and put them in a folder called "data". In case of queries or any problems, please email me at : hari.kalidindi@uclouvain.be
DOI: 10.5281/zenodo.7078539
title: EDEN2020 Ovine Brain Dataset for Fluid-Solid Interaction between Interstitial Fluid and Axons

description: This Dataset has been created to be able to share all data related to the study of Fluid-Solid Interaction between Interstitial Fluid and Axons. The dataset is the source used for studies included in scientific publications that constitute some of the main outputs of the EDEN2020 project. The two folders contain the model and database created throughout this research. Comsol Model contains the COMSOL models for parallel flow and perpendicualr flow. Figure Data contains all the data used to draw the Figures.
DOI: 10.5281/zenodo.7078538
title: EDEN2020 Ovine Brain Dataset for Fluid-Solid Interaction between Interstitial Fluid and Axons

description: This Dataset has been created to be able to share all data related to the study of Fluid-Solid Interaction between Interstitial Fluid and Axons. The dataset is the source used for studies included in scientific publications that constitute some of the main outputs of the EDEN2020 project. The two folders contain the model and database created throughout this research. Comsol Model contains the COMSOL models for parallel flow and perpendicualr flow. Figure Data contains all the data used to draw the Figures.
DOI: 10.5281/zenodo.7113780
title: Cerebellum spiking data during simulated saccade control

description: This repository contains data generated by simulating the cerebellum spiking neural network for saccade motor control. Please refer to the article at https://doi.org/10.1101/2022.03.14.483471. Please check the journal of PLOS computational biology for the published version of this article (inpress). The python scripts will generate plots by going through the data folder. In order to do so, please unzip the datasets manually and put them in a folder called "data". In case of queries or any problems, please email me at: hari.kalidindi@uclouvain.be
DOI: 10.5281/zenodo.7114520
title: Cerebellum spiking data during simulated saccade control

description: This repository contains data generated by simulating the cerebellum spiking neural network for saccade motor control. Please refer to the article at https://doi.org/10.1101/2022.03.14.483471. Please check the journal of PLOS computational biology for the published version of this article (inpress). The python scripts will generate plots from the simulation datasets. In order to do so, please unzip the datasets and put each of the data subfolders into the current folder along with the plotting scripts. The spiking neuronal circuit datasets have been generated using the NEST spiking neural network library (https://www.nest-simulator.org/), in .gdf format. Users can refer to the presented python scripts to understand how to read from and plot the data. Additionally, for interested users, the trained PF-PC synaptic weights from saccade simulations are also available as EXCEL files in the same dataset folders. In case of queries or any problems, please email me at the email id given in the article linked above.
DOI: 10.5281/zenodo.7113508
title: Cerebellum spiking data during simulated saccade control

description: This repository contains data generated by simulating the cerebellum spiking neural network for saccade motor control. Please refer to the article at https://doi.org/10.1101/2022.03.14.483471. Please check the journal of PLOS computational biology for the published version of this article (inpress). The python scripts will generate plots from the simulation datasets. In order to do so, please unzip the datasets and put each of the data subfolders into the current folder along with the plotting scripts. The spiking neuronal circuit datasets have been generated using the NEST spiking neural network library (https://www.nest-simulator.org/), in .gdf format. Users can refer to the presented python scripts to understand how to read from and plot the data. Additionally, for interested users, the trained PF-PC synaptic weights from saccade simulations are also available as EXCEL files in the same dataset folders. In case of queries or any problems, please email me at the email id given in the article linked above.
DOI: 10.6084/m9.figshare.21210656
title: Cerebrospinal fluid metabolomes data set

description: These are the metabolomics and clinical data sets derived from patients.