cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17026/dans-28t-abgp
title: What is an Adequate Old-Age Income? (LISS Core Study)

description: Choice and other types of questions in relation to monthly spending during working life and retirement.
DOI: 10.5281/zenodo.10018590
title: enpkg_toy_dataset

description: A toy dataset for the PF1600 ENPKG data
DOI: 10.5281/zenodo.10018678
title: Tapping mode liquid CFM_AFM analysis
DOI: 10.5281/zenodo.10018679
title: Tapping mode liquid CFM_AFM analysis
DOI: 10.5281/zenodo.10018496
title: Simulation of ripple oscillations in a large interneuron network under different levels of constant external drive

description: Example simulation to be used with code on GitHub repository: https://github.com/NatalieSchieferstein/interneuron_ripples_with_ifa.git .
Simulation data was generated using pypet (pypet.readthedocs.io/) and Brian2.
Code and simulation data are Supplement to publication: 10.1101/2023.01.30.526209 .
DOI: 10.5281/zenodo.10018497
title: Simulation of ripple oscillations in a large interneuron network under different levels of constant external drive

description: Example simulation to be used with code on GitHub repository: https://github.com/NatalieSchieferstein/interneuron_ripples_with_ifa.git .
Simulation data was generated using pypet (pypet.readthedocs.io/) and Brian2.
Code and simulation data are Supplement to publication: 10.1101/2023.01.30.526209 .
DOI: 10.5281/zenodo.10018700
title: Data for: Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems

description: Data for: Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems
Please read the README.txt file before working with the data.
DOI: 10.5281/zenodo.10018264
title: enpkg_toy_dataset

description: A toy dataset for the PF1600 ENPKG data
DOI: 10.5281/zenodo.10018265
title: enpkg_toy_dataset

description: A toy dataset for the PF1600 ENPKG data
DOI: 10.5281/zenodo.10018701
title: Data for: Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems

description: Data for: Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems
Please read the README.txt file before working with the data.
DOI: 10.5281/zenodo.10018477
title: Safety, effectiveness, and skin immune response in a controlled human infection model of sand fly transmitted cutaneous leishmaniasis.

description: Safety, effectiveness, and skin immune response in a controlled human infection model of sand fly transmitted cutaneous leishmaniasis.
Vivak Parkash1, Helen Ashwin1, Shoumit Dey1, Jovana Sadlova2, Barbora Vojtkova2, Katrien Van Bocxlaer1,3, Rebecca Wiggins1, David Thompson4 Nidhi Sharma Dey1, Charles L. Jaffe5, Eli Schwartz6, Petr Volf2, Charles J. N. Lacey1, Alison M. Layton1,3 * and Paul M. Kaye1,3 *.
 
1 York Biomedical Research Institute, Hull York Medical School, University of York, York, UK
2 Department of Parasitology, Faculty of Science, Charles University, Viničná 7, Prague, Czech Republic
3 Skin Research Centre, Hull York Medical School, York, UK
4 York and Scarborough Teaching Hospitals NHS Foundation Trust, York, UK  
5 Department of Microbiology and Molecular Genetics, Kuvin Center for the Study of Infectious and Tropical Diseases, IMRIC, The Hebrew University – Hadassah Medical School, Jerusalem, Israel
6 The Center for Geographic Medicine and Tropical Diseases, Chaim Sheba Medical Center, and The School of Medicine, Tel Aviv University, Israel.
 
*Corresponding authors: paul.kaye@york.ac.uk and alison.layton@hyms.ac.uk
DOI: 10.5281/zenodo.10018476
title: Safety, effectiveness, and skin immune response in a controlled human infection model of sand fly transmitted cutaneous leishmaniasis.

description: Safety, effectiveness, and skin immune response in a controlled human infection model of sand fly transmitted cutaneous leishmaniasis.
Vivak Parkash1, Helen Ashwin1, Shoumit Dey1, Jovana Sadlova2, Barbora Vojtkova2, Katrien Van Bocxlaer1,3, Rebecca Wiggins1, David Thompson4 Nidhi Sharma Dey1, Charles L. Jaffe5, Eli Schwartz6, Petr Volf2, Charles J. N. Lacey1, Alison M. Layton1,3 * and Paul M. Kaye1,3 *.
 
1 York Biomedical Research Institute, Hull York Medical School, University of York, York, UK
2 Department of Parasitology, Faculty of Science, Charles University, Viničná 7, Prague, Czech Republic
3 Skin Research Centre, Hull York Medical School, York, UK
4 York and Scarborough Teaching Hospitals NHS Foundation Trust, York, UK  
5 Department of Microbiology and Molecular Genetics, Kuvin Center for the Study of Infectious and Tropical Diseases, IMRIC, The Hebrew University – Hadassah Medical School, Jerusalem, Israel
6 The Center for Geographic Medicine and Tropical Diseases, Chaim Sheba Medical Center, and The School of Medicine, Tel Aviv University, Israel.
 
*Corresponding authors: paul.kaye@york.ac.uk and alison.layton@hyms.ac.uk
DOI: 10.5281/zenodo.10018705
title: FZIC-dataset3
DOI: 10.5281/zenodo.10018704
title: FZIC-dataset3
DOI: 10.5517/ccdc.csd.cc2d6hmr
title: CCDC 2210784: Experimental Crystal Structure Determination

description: Related Article: D. Vinci, D. Chateigner|2022|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|78|835|doi:10.1107/S2052520622009660
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.cc2dbh2b
title: CCDC 2214611: Experimental Crystal Structure Determination

description: Related Article: Jiun Wei Wu, Ryan W. Kulow, McKenna J. Redding, Alexander J. Fine, Scott M. Grayson, Quentin Michaudel|2023|ACS Polym. Au|3|259|doi:10.1021/acspolymersau.2c00060
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.cc2dbh3c
title: CCDC 2214612: Experimental Crystal Structure Determination

description: Related Article: Jiun Wei Wu, Ryan W. Kulow, McKenna J. Redding, Alexander J. Fine, Scott M. Grayson, Quentin Michaudel|2023|ACS Polym. Au|3|259|doi:10.1021/acspolymersau.2c00060
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.cc2dd0jc
title: CCDC 2216082: Experimental Crystal Structure Determination

description: Related Article: Dagmara Ziembicka, Katarzyna Gobis, Małgorzata Szczesio, Andrzej Olczak, Ewa Augustynowicz-Kopeć, Agnieszka Głogowska, Izabela Korona-Głowniak, Krzysztof Bojanowski|2023|Materials|16|448|doi:10.3390/ma16010448
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.cc2dd0lf
title: CCDC 2216084: Experimental Crystal Structure Determination

description: Related Article: Dagmara Ziembicka, Katarzyna Gobis, Małgorzata Szczesio, Andrzej Olczak, Ewa Augustynowicz-Kopeć, Agnieszka Głogowska, Izabela Korona-Głowniak, Krzysztof Bojanowski|2023|Materials|16|448|doi:10.3390/ma16010448
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.cc2dd0mg
title: CCDC 2216085: Experimental Crystal Structure Determination

description: Related Article: Dagmara Ziembicka, Katarzyna Gobis, Małgorzata Szczesio, Andrzej Olczak, Ewa Augustynowicz-Kopeć, Agnieszka Głogowska, Izabela Korona-Głowniak, Krzysztof Bojanowski|2023|Materials|16|448|doi:10.3390/ma16010448
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.cc2dd0nh
title: CCDC 2216086: Experimental Crystal Structure Determination

description: Related Article: Dagmara Ziembicka, Katarzyna Gobis, Małgorzata Szczesio, Andrzej Olczak, Ewa Augustynowicz-Kopeć, Agnieszka Głogowska, Izabela Korona-Głowniak, Krzysztof Bojanowski|2023|Materials|16|448|doi:10.3390/ma16010448
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.cc2czbnc
title: CCDC 2203903: Experimental Crystal Structure Determination

description: Related Article: Shouying Cao, Chenpeng Fan, Mengwen Lu, Meng Li, Yuhang Zhou, Hongxia Wang, Qingfang Lin, Lili Liang|2023|CrystEngComm|25|309|doi:10.1039/D2CE01350A
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.cc2czbpd
title: CCDC 2203904: Experimental Crystal Structure Determination

description: Related Article: Shouying Cao, Chenpeng Fan, Mengwen Lu, Meng Li, Yuhang Zhou, Hongxia Wang, Qingfang Lin, Lili Liang|2023|CrystEngComm|25|309|doi:10.1039/D2CE01350A
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.10018527
title: Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir: data, forecasts, and scores

description: This data publication contains zipped parquet from the Beaverdam Reservoir forecasting data assimilation experiments using the FLARE (Forecasting Lake And Reservoir Ecosystems) system: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations and meteorological data, forecasts.zip contains forecast parquet files generated from the BVR FLARE DA experiment workflow, and scores.zip contains forecast skill metrics required for analysis. Within the forecasts and scores folders, there are four runs that were conducted with different parameter tuning and uncertainty quantification. The "all_UC" folder includes forecasts run with process, driver, parameter, and initial condition uncertainty quantification. The "IC_off" folder includes forecasts run without initial conditions uncertainty included (i.e., only process, driver, and parameter uncertainty). The "constant_bad_pars" folder includes forecasts run with constant parameters (but daily updating of initial conditions) that were not tuned for Beaverdam Reservoir before forecasts were generated. Finally, the "tuned_bad_pars" folder includes forecasts that were run with daily updating of initial conditions and parameters, but the parameters started out at random values that were not tuned for Beaverdam Reservoir.
DOI: 10.5281/zenodo.7951402
title: Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir: data, forecasts, and scores

description: This data publication contains zipped parquet from the Beaverdam Reservoir forecasting data assimilation experiments using the FLARE (Forecasting Lake And Reservoir Ecosystems) system: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations and meteorological data, forecasts.zip contains forecast parquet files generated from the BVR FLARE DA experiment workflow, and scores.zip contains forecast skill metrics required for analysis.
DOI: 10.5281/zenodo.7925097
title: Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir: data, forecasts, and scores

description: This data publication contains zipped parquet from the Beaverdam Reservoir forecasting data assimilation experiments using the FLARE (Forecasting Lake And Reservoir Ecosystems) system: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations and meteorological data, forecasts.zip contains forecast parquet files generated from the BVR FLARE DA experiment workflow, and scores.zip contains forecast skill metrics required for analysis. Within the forecasts and scores folders, there are four runs that were conducted with different parameter tuning and uncertainty quantification. The "all_UC" folder includes forecasts run with process, driver, parameter, and initial condition uncertainty quantification. The "IC_off" folder includes forecasts run without initial conditions uncertainty included (i.e., only process, driver, and parameter uncertainty). The "constant_bad_pars" folder includes forecasts run with constant parameters (but daily updating of initial conditions) that were not tuned for Beaverdam Reservoir before forecasts were generated. Finally, the "tuned_bad_pars" folder includes forecasts that were run with daily updating of initial conditions and parameters, but the parameters started out at random values that were not tuned for Beaverdam Reservoir.
DOI: 10.5281/zenodo.7925098
title: Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir: data for Wander et al. BVR FLARE DA experiments

description: This data publication contains zipped parquet files for BVR FLARE DA experiments: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations and meteorological data, forecasts.zip contains forecast parquet files generated from the BVR FLARE DA experiment workflow, and scores.zip contains forecast skill metrics required for analysis.
DOI: 10.18434/m31561
title: High Temperature High Pressure U-tube Density Measurements
DOI: 10.5281/zenodo.10018711
title: A hepatitis B virus (HBV) sequence variation graph improves alignment and sample-specific consensus sequence construction
DOI: 10.5281/zenodo.10018710
title: A hepatitis B virus (HBV) sequence variation graph improves alignment and sample-specific consensus sequence construction
DOI: 10.5281/zenodo.10018597
title: Peak lists, assignments, and structures of 100 proteins determined by the ARTINA algorithm

description:  
The time-consuming and complex data analysis process constitutes a limitation for biomolecular NMR. It typically requires weeks or months of manual work of a trained expert to identify and interpret thousands of signals, recorded in a series of multidimensional NMR spectra, in order to determine the sequence-specific resonance assignments or the three-dimensional structure of a single protein. 
To solve this problem, we developed ARTINA, a machine learning-based method that uses as input only NMR spectra and the protein sequence, and delivers signal positions, resonance assignments, and structures strictly without any human intervention. Tested on a 100-protein benchmark comprising 1329 multidimensional NMR spectra, ARTINA demonstrated its ability to solve structures with 1.44 Å median RMSD to the PDB reference and to identify 91.36% correct NMR resonance assignments. 
ARTINA is freely accessible for non-commercial users at NMRtist (https://nmrtist.org), an online platform that combines deep learning, large-scale optimization, and cloud computing to offer full automation of NMR spectra analysis. Our website provides virtual storage for NMR spectra deposition together with a set of applications designed for automated peak picking, chemical shift assignment, and protein structure determination. The system can be used by non-experts and without IT infrastructure on the user's side, allowing protein NMR spectra interpretation within hours after completion of the measurements. With NMRtist, the effort for a protein assignment or structure determination by NMR essentially reduced to the preparation of the sample and the spectrum measurements.
DOI: 10.5281/zenodo.10018596
title: Peak lists, assignments, and structures of 100 proteins determined by the ARTINA algorithm

description:  
The time-consuming and complex data analysis process constitutes a limitation for biomolecular NMR. It typically requires weeks or months of manual work of a trained expert to identify and interpret thousands of signals, recorded in a series of multidimensional NMR spectra, in order to determine the sequence-specific resonance assignments or the three-dimensional structure of a single protein. 
To solve this problem, we developed ARTINA, a machine learning-based method that uses as input only NMR spectra and the protein sequence, and delivers signal positions, resonance assignments, and structures strictly without any human intervention. Tested on a 100-protein benchmark comprising 1329 multidimensional NMR spectra, ARTINA demonstrated its ability to solve structures with 1.44 Å median RMSD to the PDB reference and to identify 91.36% correct NMR resonance assignments. 
ARTINA is freely accessible for non-commercial users at NMRtist (https://nmrtist.org), an online platform that combines deep learning, large-scale optimization, and cloud computing to offer full automation of NMR spectra analysis. Our website provides virtual storage for NMR spectra deposition together with a set of applications designed for automated peak picking, chemical shift assignment, and protein structure determination. The system can be used by non-experts and without IT infrastructure on the user's side, allowing protein NMR spectra interpretation within hours after completion of the measurements. With NMRtist, the effort for a protein assignment or structure determination by NMR essentially reduced to the preparation of the sample and the spectrum measurements.
DOI: 10.25345/c5474727v
title: MassIVE MSV000093143 - EttA alleviates early ribosome stalling events induced by acidic residues
title: In this study we have used an unbiased approach to determine the impact of the ettA deletion (delta ettA) on the physiology of E. coli. The gene deletion creates a hypersensitivity to salt when the bacteria are grown on carbon sources metabolized by the TCA cycle. This phenotype is due to the reduced translation of several genes of the TCA cycle and of genes involved in stress responses. In this work we have systematically compared three strains MG1655 WT, delta ettA and the delta ettA complemented with an exogenous chromosomal copy of ettA (CettA). Label-Free mass spectrometry studies performed on light (S15) and heavy (S150) fractions of proteins extracts from cultures grown in MMAA-NaCl medium, identified several protein expression changes in the delta ettA strain compared to the WT or the CettA strains.
DOI: 10.5281/zenodo.10018901
title: Histochemical staining of shell biomolecules
DOI: 10.5281/zenodo.10018900
title: Histochemical staining of shell biomolecules
DOI: 10.5281/zenodo.10018811
title: FZIC-dataset4
DOI: 10.5281/zenodo.10018810
title: FZIC-dataset4
DOI: 10.5281/zenodo.10018897
title: Supplementary Data
DOI: 10.5281/zenodo.10018896
title: Supplementary Data
DOI: 10.5281/zenodo.10018898
title: Adsorption_Mineral_BLGProtein_Ionic solutions
DOI: 10.5281/zenodo.10018887
title: Adsorption_Mineral_BLGProtein_Ionic solutions
DOI: 10.5281/zenodo.10018888
title: Adsorption_Mineral_BLGProtein_Ionic solutions
DOI: 10.6084/m9.figshare.24347464
title: 20231019_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.6084/m9.figshare.24347464.v1
title: 20231019_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.5517/ccdc.csd.cc2930gx
title: CCDC 2118058: Experimental Crystal Structure Determination

description: Related Article: Somnath Bhattacharya, Jianfeng Zhu, Jens Müller |2022|Polymer|242|124477|doi:10.1016/j.polymer.2021.124477
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.cc2930hy
title: CCDC 2118059: Experimental Crystal Structure Determination

description: Related Article: Somnath Bhattacharya, Jianfeng Zhu, Jens Müller |2022|Polymer|242|124477|doi:10.1016/j.polymer.2021.124477
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.cc2930jz
title: CCDC 2118060: Experimental Crystal Structure Determination

description: Related Article: Somnath Bhattacharya, Jianfeng Zhu, Jens Müller |2022|Polymer|242|124477|doi:10.1016/j.polymer.2021.124477
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.cc2cznbc
title: CCDC 2204203: Experimental Crystal Structure Determination

description: Related Article: Yusuke Ishigaki, Reina Fukagawa, Kazuma Sugawara, Takashi Harimoto, Takanori Suzuki |2022|Chem.Asian J.|17|e202200914|doi:10.1002/asia.202200914
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.