cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bj4lm
title: CCDC 2160470: Experimental Crystal Structure Determination

description: Related Article: Thach N. Tu, Manfred Scheer|2023|Chem (Cell Press)|9|227|doi:10.1016/j.chempr.2022.10.016
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.cc2bhz61
title: CCDC 2160303: Experimental Crystal Structure Determination

description: Related Article: Thach N. Tu, Manfred Scheer|2023|Chem (Cell Press)|9|227|doi:10.1016/j.chempr.2022.10.016
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.cc2h016s
title: CCDC 2293944: Experimental Crystal Structure Determination

description: Related Article: K. Scanda, Y. Avila, L. Sánchez, R. Mojica, M. González, B. D. Moreno, Manuel Avila, E. Reguera|2023|New J.Chem.|47|21834|doi:10.1039/D3NJ04638A
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.cc2h017t
title: CCDC 2293945: Experimental Crystal Structure Determination

description: Related Article: K. Scanda, Y. Avila, L. Sánchez, R. Mojica, M. González, B. D. Moreno, Manuel Avila, E. Reguera|2023|New J.Chem.|47|21834|doi:10.1039/D3NJ04638A
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.cc2h0x0g
title: CCDC 2294775: Experimental Crystal Structure Determination

description: Related Article: Michael Fragkiadakis, Paraskevi-Kleio Anastasiou, Ioannis Volyrakis, Apostolos Pantousas, Constantinos C. Stoumpos, Constantinos G. Neochoritis|2023|Chem.Commun.|59|14411|doi:10.1039/D3CC04597H
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.cc2h0x1h
title: CCDC 2294776: Experimental Crystal Structure Determination

description: Related Article: Michael Fragkiadakis, Paraskevi-Kleio Anastasiou, Ioannis Volyrakis, Apostolos Pantousas, Constantinos C. Stoumpos, Constantinos G. Neochoritis|2023|Chem.Commun.|59|14411|doi:10.1039/D3CC04597H
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.cc2h0x2j
title: CCDC 2294777: Experimental Crystal Structure Determination

description: Related Article: Michael Fragkiadakis, Paraskevi-Kleio Anastasiou, Ioannis Volyrakis, Apostolos Pantousas, Constantinos C. Stoumpos, Constantinos G. Neochoritis|2023|Chem.Commun.|59|14411|doi:10.1039/D3CC04597H
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.cc2h0x3k
title: CCDC 2294778: Experimental Crystal Structure Determination

description: Related Article: Michael Fragkiadakis, Paraskevi-Kleio Anastasiou, Ioannis Volyrakis, Apostolos Pantousas, Constantinos C. Stoumpos, Constantinos G. Neochoritis|2023|Chem.Commun.|59|14411|doi:10.1039/D3CC04597H
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: 10.25345/c5sj1b26g
title: MassIVE MSV000093610 - Identification of complex III, NQR and SDH as pharmacologic targets in non-multiplying Pseudomonas aeruginosa cultured in urine-like conditions
title: Bacterial membrane samples (20 ug of protein) were prepared using the Filter Aided Sample Preparation protocol, employing 30 K NMWL centrifugal filter units. Samples were reduced with 20 mM dithiothreitol, followed by 20 min alkylation with 50 mM iodoacetamide. The alkylated proteins underwent three washes with 200 uL of 8 M Urea in 0.1 M Ammonium Bicarbonate (ABC) and were subsequently equilibrated three times with 0.1 M ABC prior to trypsin digestion. Proteins were digested using Trypsin at an enzyme: protein ratio of 1:50 in 50 uL of 0.1 M ABC buffer at 37C overnight. The resulting digested peptides were collected by centrifugation at 14,000 g for 20 min, followed by two elutions with 50 uL of 50 mM ABC and one elution with 50 uL of 0.5 M NaCl. The eluted peptides were desalted using C18 columns and were dried. The digested proteins were then reconstituted in a 30 uL solution of 5% acetonitrile and 0.1% formic acid buffer for LC-MS analysis.
DOI: 10.25345/c5ns0m83t
title: MassIVE MSV000093611 - Proteostasis perturbation of N-Myc by HSP70 inhibition improves treatment in neuroendocrine prostate cancer
title: N-Myc is a key driver of neuroendocrine tumors, such as neuroblastoma and neuroendocrine prostate cancer. However, N-Myc is considered undruggable because it lacks clear binding sites for small molecules. One potential way to circumvent this challenge is to identify and target the protein homeostasis proteostasis systems that maintain N-Myc levels. Here we developed a novel spontaneously indefinite prostate cancer cell line UCDCaP and its paired castration-resistant line UCDCaP-CR, which exhibits neural lineage plasticity and high levels of N-Myc protein expression. Through rapid immunoprecipitation mass spectrometry assay, we revealed that heat shock protein 70, HSP70 is a top partner for N-Myc. HSP70 is known to function in protein folding and it also coordinates with the E3 ubiquitin ligase, STIP1 homology and U-box containing protein 1, STUB1, to regulate oncoprotein degradation. We find that HSP70 binds a conserved SELILKR motif and prevents the access of STUB1 on N-Myc possibly through steric hindrance. When HSP70 dwell time on N-Myc is increased by the conformational change of HSP70, STUB1 is in close proximity with N-Myc and becomes functional to promote N-Myc ubiquitination on the K416 and K419 sites of the bHLH-LZ domain and form the poly ubiquitination chains linked by the K11 and K63 sites.
DOI: 10.5281/zenodo.10306842
title: Source data - Langerhans islets induce CCL27-driven anti-tumor immunity at the expense of glycemic control and predict chemotherapy response in pancreatic cancer
DOI: 10.5281/zenodo.10306841
title: Source data - Langerhans islets induce CCL27-driven anti-tumor immunity at the expense of glycemic control and predict chemotherapy response in pancreatic cancer
DOI: 10.5281/zenodo.10277972
title: Going beyond Top EFT - Code and Data

description: The file BeyondTopEFT.zip contains all the code and processed data for reproducing the results in the Beyond Top EFT paper.
The raw data is provided as separate tarballs.
Additional instructions can be found in the README file contained in BeyondTopEFT.zip or in the GitHub repository.
DOI: 10.5281/zenodo.10277973
title: Going beyond Top EFT - Code and Data

description: The file BeyondTopEFT.zip contains all the code and processed data for reproducing the results in the Beyond Top EFT paper.
The raw data is provided as separate tarballs.
Additional instructions can be found in the README file contained in BeyondTopEFT.zip or in the GitHub repository.
DOI: 10.34740/kaggle/dsv/7156907
title: Balochi Language to English Translation Dataset
DOI: 10.24432/c5xk7s
title: Bongabdo
DOI: 10.5281/zenodo.10307443
title: Generative AI in Education and Research: A systematic mapping and bibliometric analysis of published articles
DOI: 10.5281/zenodo.10307444
title: Generative AI in Education and Research: A systematic mapping and bibliometric analysis of published articles
DOI: 10.6084/m9.figshare.24776898
title: Condensed data associated with van der Vinne et al (2024) Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure

description: The dataset contains data presented in van der Vinne et al (2024) Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure. Data is condensed to the data presented in Figures 1 and 4 of the paper. Underlying analyses to generate the condensed data are available in the associated extended dataset.
DOI: 10.6084/m9.figshare.24776898.v1
title: Condensed data associated with van der Vinne et al (2024) Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure

description: The dataset contains data presented in van der Vinne et al (2024) Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure. Data is condensed to the data presented in Figures 1 and 4 of the paper. Underlying analyses to generate the condensed data are available in the associated extended dataset.
DOI: 10.6084/m9.figshare.24776928
title: Extended dataset associated with van der Vinne et al (2024) Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure

description: The dataset contains data presented in van der Vinne et al (2024) Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure. This dataset contains the data and analyses resulting presented in Figures 1 and 4 of the paper. A condensed version of this data is available in the associated condensed dataset.
DOI: 10.6084/m9.figshare.24776928.v1
title: Extended dataset associated with van der Vinne et al (2024) Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure

description: The dataset contains data presented in van der Vinne et al (2024) Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure. This dataset contains the data and analyses resulting presented in Figures 1 and 4 of the paper. A condensed version of this data is available in the associated condensed dataset.
DOI: 10.5281/zenodo.10304948
title: MOB-suite database v. 3.1.8

description: Contains the biomarker and plasmid databases used with the MOB-suite https://github.com/phac-nml/mob-suite
DOI: 10.5281/zenodo.3785612
title: MOB-suite database v. 3.1.8

description: Contains the biomarker and plasmid databases used with the MOB-suite https://github.com/phac-nml/mob-suite
DOI: 10.5281/zenodo.3785613
title: MOB-suite database v. 2.0.0

description: Contains the biomarker and plasmid databases used with the MOB-suite https://github.com/phac-nml/mob-suite
DOI: 10.5281/zenodo.3786915
title: MOB-suite database v. 2.0.0

description: Contains the biomarker and plasmid databases used with the MOB-suite https://github.com/phac-nml/mob-suite
DOI: 10.5281/zenodo.10307504
title: PS-CAT

description: PS-CAT: optimized structure with charge=0, spin=singlet
PS-CAT_3MC: optimized 3MC structure with charge=0, spin=triplet
PS-CAT_3pp: optimized 3pipi* structure with charge=0, spin=triplet
PS-CAT_monoanion: optimized structure with charge=-1, spin=doublet
DOI: 10.5281/zenodo.7920021
title: PS-CAT

description: PS-CAT: optimized structure with charge=0, spin=singlet
PS-CAT_3MC: optimized 3MC structure with charge=0, spin=triplet
PS-CAT_3pp: optimized 3pipi* structure with charge=0, spin=triplet
PS-CAT_monoanion: optimized structure with charge=-1, spin=doublet
DOI: 10.5281/zenodo.7920022
title: PS-CAT

description: PS-CAT: optimized structure with charge=0, spin=singlet PS-CAT_3MC: optimized structure with charge=0, spin=triplet PS-CAT_monoanion: optimized structure with charge=-1, spin=doublet
DOI: 10.5281/zenodo.10278418
title: Data for "Determining the orientation of a magnetic reconnection X line and implications for a 2D coordinate system"

description: Supporting information for "Determining the orientation of a magnetic reconnection X line and implications for a 2D coordinate system", by Denton et al. Includes a copy of the paper and previous relevant papers, the simulation data used in the paper, and the reconstruction code used in the paper. See the readme files.
DOI: 10.5281/zenodo.10278483
title: Data and Software for "Determining the orientation of a magnetic reconnection X line and implications for a 2D coordinate system"

description: Supporting information for "Determining the orientation of a magnetic reconnection X line and implications for a 2D coordinate system", by Denton et al. Includes a copy of the paper and previous relevant papers, the simulation data used in the paper, and the reconstruction code used in the paper. See the readme files.
DOI: 10.5281/zenodo.7987180
title: Data and Software for "Determining the orientation of a magnetic reconnection X line and implications for a 2D coordinate system"

description: Supporting information for "Determining the orientation of a magnetic reconnection X line and implications for a 2D coordinate system", by Denton et al. Includes a copy of the paper and previous relevant papers, the simulation data used in the paper, and the reconstruction code used in the paper. See the readme files.
DOI: 10.5281/zenodo.7057825
title: Global sea surface dimethyl sulfide dataset simulated by artificial neural network

description: This dataset contains (1) the matched and binned data used for constructing an artificial neural network (ANN) model to simulate the sea surface concentration of dimethyl sulfide (DMS); (2) the simulated global daily sea surface concentrations of DMS ranging from 2005 to 2014 by ANN model and the calculated total transfer velocities (Kt) and sea-to-air fluxes; (3) the simulated global monthly sea surface concentrations of DMS ranging from 2005 to 2100 by ANN model and CMIP6 ensemble and the calculated Kt and sea-to-air fluxes; (4) the yearly mean DMS concentration of each grid in different sensitivity experiments exploring the roles different variables play in driving DMS future changes. The input variables of this ANN model include chlorophyll <em>a</em>, sea surface temperature (SST), mixed layer depth (MLD), nitrate, phosphate, silicate, dissolved oxygen (DO), downward short-wave radiation (DSWF), and sea surface salinity (SSS). The future projections (2015-2100) are subjected into two Shared Socioeconomic Pathway scenarios SSP2-4.5 and SSP5-8.5. The spatial resolution of the simulated dataset is 1°×1°. The units of DMS concentration, Kt, and flux are nmol L<sup>–1</sup>, m s<sup>–1</sup>, and μmol S m<sup>–2</sup> d <sup>–1</sup>, respectively. Compared with the previous version (v1.0), this version is based on an updated ANN model after adjusting the data match-up between satellite and in-situ chlorophyll <em>a</em> for ANN training. In addition, the historical simulation based on CMIP6 only covers the time period from 2005 to 2014, which was from 1850 to 2014 for v1.0.
description: Questions and requests can be addressed to: sqzhou17@fudan.edu.cn.
DOI: 10.6084/m9.figshare.24450445
title: Data for "Machine Learning Design of Perovskite Catalytic Properties"

description: This Figshare repository contains data for the paper "Machine Learning Design of Perovskite Catalytic Properties" by Ryan Jacobs, Jian Liu, Harry Abernathy and Dane Morgan, to be published (2023).
DOI: 10.5281/zenodo.10277428
title: CTD+ hydrographic measurement results from Admiralty Bay, Antarctica from February 2022 to February 2023

description: The dataset contains CTD+ measurement results from Admiralty Bay on King George Island. It consists of data on conductivity, salinity, temperature, pH, turbidity, optical dissolved oxygen (ODO), fluorescent Dissolved Organic Matter (fDOM), chlorophyll A, and Phycoerythrin, measured from February 2022 to February 2023.
This dataset is a continuation of a larger measurement campaign described in: 
Osińska, M., Wójcik-Długoborska, K. A., & Bialik, R. J. (2023). Annual hydrographic variability in Antarctic coastal waters infused with glacial inflow. Earth System Science Data, 15(2). https://doi.org/10.5194/essd-15-607-2023
which can be found at:
Osińska, M., Wójcik-Długoborska, K. A., & Bialik, R. J. (2022). Water conductivity, salinity, temperature, turbidity, pH, fluorescent dissolved organic matter (fDOM), optical dissolved oxygen (ODO), chlorophyll a and phycoerythrin measurements in Admiralty Bay, King George Island, from Dec 2018 to Jan 2022. PANGAEA. https://doi.org/https://doi.org/10.1594/PANGAEA.947909
DOI: 10.5281/zenodo.10277429
title: CTD+ hydrographic measurement results from Admiralty Bay, Antarctica from February 2022 to February 2023

description: The dataset contains CTD+ measurement results from Admiralty Bay on King George Island. It consists of data on conductivity, salinity, temperature, pH, turbidity, optical dissolved oxygen (ODO), fluorescent Dissolved Organic Matter (fDOM), chlorophyll A, and Phycoerythrin, measured from February 2022 to February 2023.
This dataset is a continuation of a larger measurement campaign described in: 
Osińska, M., Wójcik-Długoborska, K. A., & Bialik, R. J. (2023). Annual hydrographic variability in Antarctic coastal waters infused with glacial inflow. Earth System Science Data, 15(2). https://doi.org/10.5194/essd-15-607-2023
which can be found at:
Osińska, M., Wójcik-Długoborska, K. A., & Bialik, R. J. (2022). Water conductivity, salinity, temperature, turbidity, pH, fluorescent dissolved organic matter (fDOM), optical dissolved oxygen (ODO), chlorophyll a and phycoerythrin measurements in Admiralty Bay, King George Island, from Dec 2018 to Jan 2022. PANGAEA. https://doi.org/https://doi.org/10.1594/PANGAEA.947909
DOI: 10.7274/24732666
title: Super-resolution (SR) Fluorescence Microscopy dataset

description: We created a small dataset - the diffraction limited to super-resolution (DL2SR) dataset - that is dedicated to estimate the super-resolution intensity from a diffracton limited fluorescence microscopy intensity images. The dataset consists of training and testing parts. 15 FOV's of BPAE cells fluorescence microscopy intensity images obtained with custom-built two-photon microscope. We use 1 FOV DL images for testing. These images are captured with excitation wavelength of 800 nm and power levels 6 mW. Each FOV contains 50 images of different noise realizations. Hence training dataset: 15 FOV's -&gt; 750 images and testing dataset: 1 FOV -&gt; 50 images Target images are geenrated using SRRF method using ImageJ plugin.
DOI: 10.7274/24732666.v1
title: Super-resolution (SR) Fluorescence Microscopy dataset

description: We created a small dataset - the diffraction limited to super-resolution (DL2SR) dataset - that is dedicated to estimate the super-resolution intensity from a diffracton limited fluorescence microscopy intensity images. The dataset consists of training and testing parts. 15 FOV's of BPAE cells fluorescence microscopy intensity images obtained with custom-built two-photon microscope. We use 1 FOV DL images for testing. These images are captured with excitation wavelength of 800 nm and power levels 6 mW. Each FOV contains 50 images of different noise realizations. Hence training dataset: 15 FOV's -&gt; 750 images and testing dataset: 1 FOV -&gt; 50 images Target images are geenrated using SRRF method using ImageJ plugin.
DOI: 10.6084/m9.figshare.24777081
title: Criticality supports cross-frequency cortical-thalamic information transfer during conscious states

description: Included are data and code for generating the main figures in Toker et al "Criticality supports cross-frequency cortical-thalamic information transfer during conscious states." Also included are configuration files to generate our waking, anesthesia, and seizure simulations. The configuration files can be run using NFTSim, which can be downloaded at https://github.com/BrainDynamicsUSYD/nftsim.
DOI: 10.6084/m9.figshare.24777081.v1
title: <b>Criticality supports cross-frequency </b><b>cortical-thalamic information </b><b>transfer during conscious states</b>

description: Included are data and code for generating the main figures in Toker et al "Criticality supports cross-frequency cortical-thalamic information transfer during conscious states." Also included are configuration files to generate our waking, anesthesia, and seizure simulations. The configuration files can be run using NFTSim, which can be downloaded at https://github.com/BrainDynamicsUSYD/nftsim.
DOI: 10.5281/zenodo.10307817
title: Quantum critical phase of FeO spans conditions of Earth's lower mantle

description: The tables here represent the Source Data for figures in the manuscript titled "Quantum critical phase of FeO spans conditions of Earth's mantle base".
DOI: 10.5281/zenodo.10307816
title: Quantum critical phase of FeO spans conditions of Earth's lower mantle

description: The tables here represent the Source Data for figures in the manuscript titled "Quantum critical phase of FeO spans conditions of Earth's mantle base".
DOI: 10.5281/zenodo.7763503
title: Orthoptera observations, Pyrenees, summer 2021

description: This repository contains the observations of Orthoptera and associated metadata, which were collected as part of a project to investigate the relationship between elevation and the elevational range over which Orthoptera are found, in the Pyrenees. Orthoptera were recorded in the Catalan Pyrenees in the summer of 2021 at three different locations. This repository contains the data and metadata resulting from these surveys, as well as human and machine-readable descriptions of the data files.
description: This dataset is made available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. For full details see https://creativecommons.org/licenses/by/4.0/