cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4431537
title: Data set with length measurments of Machu Picchu

description: The base of a niche was considered to be a construction level where in the past the architectural module could be applied. To check this possibility the width and the distances between niches were measured in the 3D point cloud for further cosine quantogram analysis. Thus, 11 data sets were created, each corresponding to a particular sector or distinguish part of it, from the area so-called <em>zona urbana</em> in Machu Picchu site. The size of each sample depends on the amount and size of buildings in a sector, so samples vary from 44 to 244 measurements, measured in centimetre [cm].
description: supported by National Science Centre (PL) ETIUDA 3 no. 2015/16/T/HS3/00020
DOI: 10.5281/zenodo.4431536
title: Data set with length measurments of Machu Picchu

description: The base of a niche was considered to be a construction level where in the past the architectural module could be applied. To check this possibility the width and the distances between niches were measured in the 3D point cloud for further cosine quantogram analysis. Thus, 11 data sets were created, each corresponding to a particular sector or distinguish part of it, from the area so-called <em>zona urbana</em> in Machu Picchu site. The size of each sample depends on the amount and size of buildings in a sector, so samples vary from 44 to 244 measurements, measured in centimetre [cm].
description: supported by National Science Centre (PL) ETIUDA 3 no. 2015/16/T/HS3/00020
DOI: 10.5519/qd.mqv7o2wc
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (8 records)
DOI: 10.5281/zenodo.3748665
title: SIRAH-CoV2 initiative: Main Protease (PDB id:6LU7)

description: This dataset contains the trajectory of a 15 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 Main protease in its APO form (PDB id: 6LU7, Bioassembly 1). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The files 6LU7_SIRAHcg_rawdata1.tar, 6LU7_SIRAHcg_rawdata2.tar, and 6LU7_SIRAHcg_rawdata3.tar, contain all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6LU7_SIRAHcg_15us_prot.tar contains only the protein coordinates, while 6LU7_SIRAHcg_15us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6LU7_SIRAHcg_15us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6LU7_SIRAHcg_prot.prmtop 6LU7_SIRAHcg_prot.ncrst 6LU7_SIRAHcg_prot_15us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.5281/zenodo.3748664
title: SIRAH-CoV2 initiative: Main Protease (PDB id:6LU7)

description: This dataset contains the trajectory of a 15 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 Main protease in its APO form (PDB id: 6LU7, Bioassembly 1). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The files 6LU7_SIRAHcg_rawdata1.tar, 6LU7_SIRAHcg_rawdata2.tar, and 6LU7_SIRAHcg_rawdata3.tar, contain all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6LU7_SIRAHcg_15us_prot.tar contains only the protein coordinates, while 6LU7_SIRAHcg_15us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6LU7_SIRAHcg_15us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6LU7_SIRAHcg_prot.prmtop 6LU7_SIRAHcg_prot.ncrst 6LU7_SIRAHcg_prot_15us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.15468/4xkzmb
title: On a collection of freshwater and estuarine crabs (Crustacea: Brachyura) from Mindanao Island, the Philippines

description: This dataset contains the digitized treatments in Plazi based on the original journal article Lagare, Nickel Jean S., Mapi-Ot, Emmarie F., Molina, Ziljih S., Neri, Jemateo B., Nuñeza, Olga M., Mendoza, Jose Christopher E. (2020): On a collection of freshwater and estuarine crabs (Crustacea: Brachyura) from Mindanao Island, the Philippines. Zootaxa 4868 (3): 301-330, DOI: https://doi.org/10.11646/zootaxa.4868.3.1
DOI: 10.5285/b6c08649-22af-3468-e053-6c86abc0c980
title: Zooplankton abundance time series from net hauls at site L4 off Plymouth, UK between 1988-2019.

description: Ongoing zooplankton research at the Plymouth Marine Laboratory has established a time series of zooplankton species since 1988 at L4, a coastal station off Plymouth, UK. Weekly samples are collected by vertical net hauls (WP2 net, mesh 200 µm; UNESCO 1968) from the sea floor (approximately 50 m) to the surface and stored in 4% buffered formalin. Results presented are n/m3 mean values from two replicate hauls made on each sampling timepoint. Some of the zooplankton analysis has been to the level of "major taxonomic groups" only, and a number of different analysts have participated over the years. The level of expertise has generally been consistent, but the user should be aware that levels of taxonomic discrimination may vary during the course of the data-set, please see metadata table for more information on this and the description document regarding complexities of the dataset. It is encouraged that users of the data maintain contact with originators of the dataset to prevent misuse or misunderstanding of the data provided due to the complex nature and temporal coverage of the data provided.
DOI: 10.15468/dvgf5r
title: Two new Atemnus species (Pseudoscorpiones: Atemnidae) from Xinjiang, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Zhao, Lingchen, Gao, Zhizhong, Zhang, Feng (2020): Two new Atemnus species (Pseudoscorpiones: Atemnidae) from Xinjiang, China. Zootaxa 4869 (2): 264-274, DOI: https://doi.org/10.11646/zootaxa.4869.2.6
DOI: 10.6084/m9.figshare.12520589
title: Serotonergic Effects on Interoception

description: <b>Summary Data:</b><br> intero_vis_CITALOPRAM.xlsx is the coded task and demographic data, with legend.<br><b>Raw Data:</b><b><br></b>disc_data_long.xlsx = interoception task data<br>dots_data_long.xlsx = visual task data<br>
DOI: 10.6084/m9.figshare.12520589.v3
title: Serotonergic Effects on Interoception

description: <b>Summary Data:</b><br> intero_vis_CITALOPRAM.xlsx is the coded task and demographic data, with legend.<br><b>Raw Data:</b><b><br></b>disc_data_long.xlsx = interoception task data<br>dots_data_long.xlsx = visual task data<br>
DOI: 10.6084/m9.figshare.12520589.v2
title: Serotonergic Effects on Interoception

description: <b>Summary Data:</b><br> interoception_and_visual_CIT.xlsx is the coded task and demographic data, with legend.<br><b>Raw Data:</b><b><br></b>disc_data_long.xlsx = interoception task data<br>dots_data_long.xlsx = visual task data<br>
DOI: 10.6084/m9.figshare.13568438
title: Example data for Dendritic localization of mRNA in Drosophila Mushroom Body Output Neurons

description: Example data for https://github.com/qnano/smFISHlearning.
DOI: 10.6084/m9.figshare.13568438.v2
title: Example data for Dendritic localization of mRNA in Drosophila Mushroom Body Output Neurons

description: Example data for https://github.com/qnano/smFISHlearning.
DOI: 10.6084/m9.figshare.13568438.v1
title: Example data

description: Example data for https://github.com/qnano/smFISHlearning.
DOI: 10.5281/zenodo.3751583
title: SIRAH-CoV2 initiative: Apo ADP ribose phosphatase of NSP3 from SARS CoV-2 (PDB id: 6W02)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 ADP ribose phosphatase of NSP3 from SARS CoV-2 in its APO form (PDB id: 6W02, Bioassembly 1). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The file 6W02_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W02_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6W02_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W02_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6W02_SIRAHcg_prot.prmtop 6W02_SIRAHcg_prot.ncrst 6W02_SIRAHcg_prot_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Exequiel Barrera (ebarrera@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.5281/zenodo.3751582
title: SIRAH-CoV2 initiative: Apo ADP ribose phosphatase of NSP3 from SARS CoV-2 (PDB id: 6W02)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 ADP ribose phosphatase of NSP3 from SARS CoV-2 in its APO form (PDB id: 6W02, Bioassembly 1). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The file 6W02_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W02_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6W02_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W02_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6W02_SIRAHcg_prot.prmtop 6W02_SIRAHcg_prot.ncrst 6W02_SIRAHcg_prot_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Exequiel Barrera (ebarrera@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.5281/zenodo.3714949
title: Online Aerosol Chemical Characterization by Extractive Electrospray Ionization − Ultrahigh-Resolution Mass Spectrometry (EESI-Orbitrap)

description: These datasets are the raw data presented in the presented work of "Online Aerosol Chemical Characterization by Extractive Electrospray Ionization − Ultrahigh-Resolution Mass Spectrometry (EESI-Orbitrap)" in <em>Environmental Science & Technology Journal</em>, doi:10.1021/acs.est.9b07090. Abstract: Current mass spectrometry techniques for the online measurement of organic aerosol (OA) composition are subjected to either thermal/ionization-induced artifacts or limited mass resolving power, hindering accurate molecular characterization. Here, we combined the soft ionization capability of extractive electrospray ionization (EESI) and the ultrahigh mass resolution of Orbitrap for real-time, near-molecular characterization of OAs. Detection limits as low as tens of ng m<sup>−3</sup> with linearity up to hundreds of μg m<sup>−3</sup> at 0.2 Hz time resolution were observed for single- and mixed-component calibrations. The performance of the EESI-Orbitrap system was further evaluated with laboratory-generated secondary OAs (SOAs) and filter extracts of ambient particulate matter. The high mass accuracy and resolution (140 000 at <em>m/z</em> 200) of the EESI-Orbitrap system enable unambiguous identification of the aerosol components’ molecular composition and allow a clear separation between adjacent peaks, which would be significantly overlapping if a medium-resolution (20 000) mass analyzer was used. Furthermore, the tandem mass spectrometry (MS<sup>2</sup>) capability provides valuable insights into the compound structure. For instance, the MS<sup>2</sup> analysis of ambient OA samples and lab-generated biogenic SOAs points to specific SOA precursors in ambient air among a range of possible isomers based on fingerprint fragment ions. Overall, this newly developed and characterized EESI-Orbitrap system will advance our understanding of the formation and evolution of atmospheric aerosols. Structure of the datasets: The raw data are separated into individual file of excel format for the figures. Simulation data from Figure 4 can be generated using the matlab code named <em>Figure4PeakSimulation.m.</em>
description: Raw mass spectrometric data can be requested by contacting corresponding authors (Matthieu Riva: matthieu.riva@ircelyon.univ-lyon1.fr and Imad El Haddad: imad.el-haddad@psi.ch).
DOI: 10.5281/zenodo.3714948
title: Online Aerosol Chemical Characterization by Extractive Electrospray Ionization − Ultrahigh-Resolution Mass Spectrometry (EESI-Orbitrap)

description: These datasets are the raw data presented in the presented work of "Online Aerosol Chemical Characterization by Extractive Electrospray Ionization − Ultrahigh-Resolution Mass Spectrometry (EESI-Orbitrap)" in <em>Environmental Science & Technology Journal</em>, doi:10.1021/acs.est.9b07090. Abstract: Current mass spectrometry techniques for the online measurement of organic aerosol (OA) composition are subjected to either thermal/ionization-induced artifacts or limited mass resolving power, hindering accurate molecular characterization. Here, we combined the soft ionization capability of extractive electrospray ionization (EESI) and the ultrahigh mass resolution of Orbitrap for real-time, near-molecular characterization of OAs. Detection limits as low as tens of ng m<sup>−3</sup> with linearity up to hundreds of μg m<sup>−3</sup> at 0.2 Hz time resolution were observed for single- and mixed-component calibrations. The performance of the EESI-Orbitrap system was further evaluated with laboratory-generated secondary OAs (SOAs) and filter extracts of ambient particulate matter. The high mass accuracy and resolution (140 000 at <em>m/z</em> 200) of the EESI-Orbitrap system enable unambiguous identification of the aerosol components’ molecular composition and allow a clear separation between adjacent peaks, which would be significantly overlapping if a medium-resolution (20 000) mass analyzer was used. Furthermore, the tandem mass spectrometry (MS<sup>2</sup>) capability provides valuable insights into the compound structure. For instance, the MS<sup>2</sup> analysis of ambient OA samples and lab-generated biogenic SOAs points to specific SOA precursors in ambient air among a range of possible isomers based on fingerprint fragment ions. Overall, this newly developed and characterized EESI-Orbitrap system will advance our understanding of the formation and evolution of atmospheric aerosols. Structure of the datasets: The raw data are separated into individual file of excel format for the figures. Simulation data from Figure 4 can be generated using the matlab code named <em>Figure4PeakSimulation.m.</em>
description: Raw mass spectrometric data can be requested by contacting corresponding authors (Matthieu Riva: matthieu.riva@ircelyon.univ-lyon1.fr and Imad El Haddad: imad.el-haddad@psi.ch).
DOI: 10.15468/h3u4u2
title: A new species of the Rhinella margaritifera (Laurenti 1768) species group (Anura Bufonidae) from southern Brazilian Amazonia

description: This dataset contains the digitized treatments in Plazi based on the original journal article Ávila, Robson Waldemar, Morais, Drausio Honorio, Perez, Renata, Pansonato, André, Carvalho, Vinicius Tadeu De, Rojas, Rommel R., Gordo, Marcelo, Farias, Izeni Pires (2020): A new species of the Rhinella margaritifera (Laurenti 1768) species group (Anura Bufonidae) from southern Brazilian Amazonia. Zootaxa 4868 (3): 368-388, DOI: https://doi.org/10.11646/zootaxa.4868.3.3
DOI: 10.34740/kaggle/dsv/1842798
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.3754643
title: SIRAH-CoV2 initiative: NSP9 RNA binding protein (PDBid:6W4B)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 NSP9 RNA binding protein (PDB id: 6W4B, Bioassembly 1). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The file 6W4B_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W4B_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6W4B_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W4B_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6W4B_SIRAHcg_prot.prmtop 6W4B_SIRAHcg_prot.ncrst 6W4B_SIRAHcg_prot_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.5281/zenodo.3754642
title: SIRAH-CoV2 initiative: NSP9 RNA binding protein (PDBid:6W4B)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 NSP9 RNA binding protein (PDB id: 6W4B, Bioassembly 1). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The file 6W4B_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W4B_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6W4B_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W4B_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6W4B_SIRAHcg_prot.prmtop 6W4B_SIRAHcg_prot.ncrst 6W4B_SIRAHcg_prot_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.5281/zenodo.4436658
title: Full information on the eORCA1 grid (mesh_mask) used in IPSL-CM6A-LR configuration

description: eORCA1.2_mesh_mask.nc : This file contains all relevant information on the eORCA1 grid used in the NEMO_v3.6_STABLE configuration of the oceanic module of the IPSL-CM6A-LR climate model. See https://www.nemo-ocean.eu/wp-content/uploads/NEMO_book.pdf for more details on the grid. eORCA_R1_bathy_meter_v2.2.nc: This file contains the bathymetry of the eORCA1 configuration used in IPSL-CM6A-LR.
description: additional information available upon request: julie.deshayes@locean.ipsl.fr
DOI: 10.5281/zenodo.4436657
title: Full information on the eORCA1 grid (mesh_mask) used in IPSL-CM6A-LR configuration

description: eORCA1.2_mesh_mask.nc : This file contains all relevant information on the eORCA1 grid used in the NEMO_v3.6_STABLE configuration of the oceanic module of the IPSL-CM6A-LR climate model. See https://www.nemo-ocean.eu/wp-content/uploads/NEMO_book.pdf for more details on the grid. eORCA_R1_bathy_meter_v2.2.nc: This file contains the bathymetry of the eORCA1 configuration used in IPSL-CM6A-LR.
description: additional information available upon request: julie.deshayes@locean.ipsl.fr